1 THE RELATIONSHIPS OF HANDHELD CO MPUTER USE, ANXIETY, AND SELFEFFICACY AMONG PUBLIC HEALTH EMPLOYEES By MICHAEL WAYNE SCHMOYER A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2007
2 Michael Wayne Schmoyer
3 To all who gave me mountains of patience, oc eans of support, and the heavens to seek, making this dream possible
4 ACKNOWLEDGMENTS I would especially like to thank my a dvisor Dr. W. William Chen for his unyielding support and guidance. While he readily acknowledge d that I needed to explore on my own to determine â€œwhat I really wanted to study,â€ he wa s adept at letting me know when it was time to focus my energies on what I had discovered lack ing within the research literature. What I probably most enjoyed about having Dr. Chen involved in my academic career was his obvious concern for the welfare of those of us in the de partmentâ€™s graduate students. Many of us had the opportunity to consult with Dr. Chen relating to our professional fu tures, share the richness of his lectures, and sample the delectable cuisine in his home. I greatly appreciate Dr. Chenâ€™s mentorship, sincerity, and patience over the course of my entire ex perience at the University of Florida. Perhaps one of my favorite smiles to see in the Florida Gym was owned by Dr. Jill Varnes. Dr. Varnes has been a delight to know both as an instructor, committee member, and friend. Because of Dr. Varnesâ€™ worksite health promotion class, I discovered a great interest in the wellbeing of employees that served as the impetus for my dissertation. Furthermore, as a result of her tutelage, I became the point of contact for worksi te health promotion issues for my division at CDC. I greatly appreciate Dr. Varn esâ€™ ability to help me state th e words that are etched in my mind, realize what is most important in life, and celebrate that I love to dance with my wife. Dr. J.J. Sheu is so passionate about his work a nd that of his students, it is no surprise that he is an obvious favorite in the halls of the department. I greatly appreciate the opportunities that Iâ€™ve had to talk with Dr. Sheu about technology a nd its relation to health education. I supremely appreciate his dedication and self less devotion to helping me with my statistical analyses and interpretation of my study resu lts; in fact, I undoubtedly owe Dr . Sheu as much Kim Chi as he would like me to bring him from Buford Highway!
5 It was Dr. Rick Ferdigâ€™s counc il that led me to realize that this disserta tion transcended solely handheld computers and actu ally related to other technol ogical devices associated with professional portability. Because of this insight , I was able to explor e implications not only within my study, but the public health field as a whole. I also appreciate that Dr. Ferdig was willing to work with a student who he barely kne w within a course of study that was finished geographically distant from the cam pus . . . especially as he wa s in the midst of successfully gaining tenure within his depart ment. I hope we stay in touch. I also wanted to acknowledge and thank Dr. Bob Weiler for his support and guidance through my academic career at the University of Florida. Dr. Weile r was instrumental in helping me realize that thereâ€™s more to health education than just teaching, and that it takes a necessary passion to be a researcher in the academic field. I wish Dr. Weiler the best of luck in his future pursuits. I also want to thank all of the past and current faculty and staff in the Department of Health Education and Behavior. Jo Anne and Janice made my life as a teaching assistant much more enjoyable than it probably should have been. Dr s. Dodd, Fagerberg, James, and Pigg, especially went out of their way to both support me in my career endeavors and/ or provide preparatory guidance for working in the fields of health education and public health. I also want to thank my colleagues and s upervisors in the Division of Adolescent and School Health at the Centers for Disease Cont rol and Prevention. I was graciously provided flexible work hours, financial support (via my Individual Learning Account), academic consolations, and an unwavering demand to always â€œkeep my eye on the prize.â€ Finally, I am especially indebted to my brilliant and beautiful wife Lori . . . who has never known me not to be a student; for the past five and a half years she has had to endure me
6 working on my education every other Friday, ev ery Saturday, and some Sunday evenings. In fact, I believe that in the time it took us to drive from my dissert ation defense in Gainesville to our home in Atlanta, she had already planned our weekends for the next year! She unceasingly supported me in the hard times, forced me to cel ebrate the great times, and provided me â€œthe space I needed to get things doneâ€ for many years. Lori is my lover, my number one fan, my mentor, my colleague, my teacher, my coach, my guru, my American Idol, and my best-est [sic] friend. Iâ€™ll never be able to fully acknowledge her for the treasure she has been, is, and will undoubtedly grow even more to be.
7 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................4 LIST OF TABLES................................................................................................................. ..........9 LIST OF FIGURES................................................................................................................ .......10 ABSTRACT....................................................................................................................... ............11 CHAPTER 1 INTRODUCTION..................................................................................................................13 Significance of the Study...................................................................................................19 Purpose of the Study..........................................................................................................20 Problem Statement.............................................................................................................20 Research Questions............................................................................................................21 Definition of Terms...........................................................................................................21 Delimitations of the Study.................................................................................................23 Limitations.................................................................................................................... .....24 2 REVIEW OF THE LITERATURE........................................................................................25 Use of Handheld Computers..............................................................................................25 HHCs among Public Health Employees.....................................................................29 Public Health Employees...........................................................................................43 Anxiety in the Workplace..................................................................................................49 Stress as it Relates to Anxiety....................................................................................49 Anxiety.......................................................................................................................54 Social Cognitive Theory and Self-Efficacy.......................................................................58 Background of Social Cognitive Theory....................................................................58 Computer Self-Efficacy..............................................................................................60 Summary........................................................................................................................ ....62 3 METHODOLOGY.................................................................................................................65 Research Design................................................................................................................65 Instrument Development...................................................................................................65 Pilot Test..................................................................................................................... .......67 Procedures..................................................................................................................67 The Final Instrument..................................................................................................68 Survey Administration................................................................................................69 Participants.................................................................................................................70 Data Collection Procedure..........................................................................................71 Data Analysis..............................................................................................................73
8 Summary........................................................................................................................ ....74 4 RESULTS........................................................................................................................ .......75 Demographic Profile of the Respondents..........................................................................75 Research Questions One and Two.....................................................................................77 Handheld Computer (HHC) Self-Efficacy Scale.......................................................77 Handheld Computer (HHC) Anxiety Scale................................................................78 Research Question Three...................................................................................................78 Research Question Four.....................................................................................................79 Research Question Five.....................................................................................................79 Summary........................................................................................................................ ....80 5 CONCLUSIONS, DISCUSSI ON, RECOMMENDATIONS................................................88 Summary........................................................................................................................ ....88 Discussion...................................................................................................................90 HHC Use....................................................................................................................91 HHC Anxiety..............................................................................................................94 HHC Self-Efficacy.....................................................................................................96 Implications for Training with HHCs.........................................................................98 Limitations.................................................................................................................... ...100 Sample Size..............................................................................................................100 WBFs........................................................................................................................102 Conclusions.................................................................................................................... ..102 Recommendations............................................................................................................103 APPENDIX A INSTRUMENT....................................................................................................................106 B LETTER OF INFORMED CONSENT................................................................................112 C LETTER ONE..................................................................................................................... .114 D LETTER TWO.....................................................................................................................115 E LETTER THREE.................................................................................................................116 F LETTER FOUR....................................................................................................................117 G INSTITUTIONAL REVIEW BOARD APPROVAL..........................................................118 LIST OF REFERENCES.............................................................................................................119 BIOGRAPHICAL SKETCH.......................................................................................................136
9 LIST OF TABLES Table page 4-1 Demographics by gender, age, years in public health, education, work setting, and professional affiliation of 462 res ponding public health employees.................................81 4-2 Frequency of usersâ€™ experience with software applications when using a HHC, laptop computer, and desktop computer (N=232).............................................................83 4-3 Perceived competence using a HHC, usi ng a laptop computer, and using a desktop computer....................................................................................................................... .....83 4-4 Summary of item analysis for the 30 HHC self-efficacy items (alpha=0.951).................84 4-5 Summary of item analysis for the six HHC anxiety items (alpha=0.828).........................86
10 LIST OF FIGURES Figure page Figure 2-1. Existence of an individualâ€™s phys iological and emotiona l state (i.e., feeling anxiety) and how it relates to those judgme nts that are made in determining selfefficacy and resultant behavior..........................................................................................64 Figure 4-1. Average weekly hours of use of desktop, handheld, and laptop computers..............87
11 Abstract of Dissertation Pres ented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy THE RELATIONSHIPS OF HANDHELD CO MPUTER USE, ANXIETY, AND SELFEFFICACY AMONG PUBLIC HEALTH EMPLOYEES By Michael Wayne Schmoyer May 2007 Chair: W. William Chen Major: Health and Human Performance With the emerging global focus on e-health, there is an increasing trend of using technological devices (such as handheld computers) in public health as tools to move virtually across geographic barriers to bett er transfer their knowledge, skill s, and care to constituents. However, the literature currently shows an abse nce of studies pertaini ng to handheld computer (HHC) use in public health, and a corresponding vacancy of data relating to psychological impact (e.g., HHC associated anxiety and self -efficacy) that are associated with employee productivity. A total of 4913 pub lic health employees were contacted for this Web-based exploratory research study; the 466 useable questionnaires ex ceeded the minimum number of cases needed to achieve power for statistical analyses concer ning the sampled population. This study investigated employeesâ€™ use of HHCs, HHC self-efficacy, HHC anxiety, and their relationships to one another. This study estab lished an instrument in which every scale that comprised it was reliable (HHC self-effi cacy scale alpha=0.951; HHC anxiety scale alpha=0.828) and demonstrated each item as s howing good internal consistency. The 55-item instrument consisted of 19 demographic/usag e items, 30 HHC self-efficacy items, and 6 HHC anxiety items. Results showed a statistically significant positive relationship between hours of using an HHC and HHC self-efficacy (r=.209, p<. 01) supporting that as HHC use increases,
12 there is an increase in reported HHC self-efficacy. Results also s howed a statistically significant negative relationship between hours of using an HHC and HHC anxiety (r= -.185, p<.01) supporting that as HHC use increases, there is a decrease in reported HHC anxiety. Analyses showed that the HHC self-efficacy scale was corr elated with those items in the HHC anxiety scale (r= -.830, p<.01) supporting that as HHC se lf-efficacy increased, there was a corresponding decrease in HHC anxiety. This study demonstrat ed that people who use HHCs more often have greater HHC self-efficacy and less associated HHC anxiety. Results of this study can encourage future research and provide public health with a tool that examines the use and impact of HHCs on employees. Furthermore, this study provides the impetus to es tablish HHCs as one agent that promotes professional portability in public health and implications for its use.
13 CHAPTER 1 INTRODUCTION In the fall of 2001, the United States Presid entâ€™s Management Council approved the Office of Management and Budget (OMB) and other fe deral agencies the establishment of the 24 EGovernment Initiatives. These initiatives are geared towards providing electronic (including online) solutions to citizens, businesses, and government employees in the areas of taxation, laws, training, funding, employment, and public hea lth (e.g., disaster response). The incentive for developing the initiatives was to identify promisi ng practices in order to decrease duplication, increase efficiency, and improve th e delivery of government services ( E-Government Act of 2002; Public Law No: 107-347). The E-Government Act of 2002 supports many other technology-related init iatives including the Government Paper Elimination Act of 1998 (Public Law No: 105-277), the Government Performance Results Act (GPRA) of 1993 (Public Law No: 103-62), and specifically, the Clinger-Cohen Act of 1996 (Public Law No: 104-208). The Clinger-Cohen Act of 1996 , a combination of two technology-re lated Acts, states that federal agencies must link informational technology (IT) i nvestments to agency accomplishments. In the public health field (federal, state, and local levels), the linkage of technology mirrors the federal requirements to link IT with strong outcomes. C onsequently, many in public health are using IT tools such as computers, Global Positioning Syst ems (GPS), and the Internet to facilitate a focused, more evidence-based impact within their targeted audiences. However, it is not known what relationship some IT tools, in particular handheld computers (HHCs), are having on the individua l public health employeeâ€™s confidence and anxiety associated with using th e device. In this dissertation, th e author will examine the use of HHCs among public health employees and its relati onships with two constr ucts related to HHC use: anxiety and self-efficacy.
14 Furthermore, with the emerging global focus on e-health (Eysenbach, 2001), more research is needed to address the use of HHCs (as one technology example) in the context of a resource that addresses professional portability. Gol dberg, Sharman, Bell, Ho and Patil (2005) define professional portability as â€œthe ease with which health-care prof essionals can move in person or virtually across barriers, and among and between ju risdictions, to transfer their knowledge, skills, and care (p.230).â€ HHCs provide th e potential to share best pract ices between educational and health-related institutions, as we ll as to develop guidelines that can be communicated and tested in the field. HHCs allow public health employ ees to engage in s upported structured and unstructured communication relati ng to public health policy, progr am practice, and professional development. Currently, there is a need for c oordinated, multidisciplinar y research, like this study, that examines how technology addresses pr ofessional portability (Goldberg et al., 2005). Additionally, key issues related to technology usage and barriers to that usage need to be identified and addressed (McAlearney, Schw eikhart, & Medow, 2004). HHCs serve as an emerging vehicle that can likely al low public health professionals th e ability to share and utilize information across spatial and temporal barriers. There are many advantages gained by using HHCs. The newest HHCs have the ability to retrieve quickly and store larg e quantities of data, including graphics or pictures, perform mathematical calculations at lightening speeds, provide voice recording for quick reminders, and finding support materials for problem solving and patient management using the latest information from national clearinghouses of info rmation, such as the U.S. Centers for Disease Control and Prevention (CDC) and the U.S. National Institutes of Health (NIH), that can enhance evidence-based public health practices (Taylo r, 2005). Currently ther e are several devices available in different operat ing systems. Just like deskt opâ€™s computing power improves
15 dramatically each year, HHCs also have increasi ng capabilities: significantly sharper screens, faster processors, and higher volume of extern al memory. Some devices even have built-in camera, MP3 player, cellular phone service, Global Positioning Systems (GPS) service, and wireless Internet capability (Luo, 2004; Hill ebrand, 2006). In fact , Microsoft CEO Steve Ballmer suggested the benefits of the global spre ad of technology are only starting to be felt: â€œComputers will see . . . listen . . . understand. Computers will help the world grow smaller and help people to collaborate in new waysâ€ (Slagle, 2006). While HHCs have the potential to be an instrume ntal tool in public heal th that can serve as a channel for professional porta bility, it is unclear how HHCs im pact the overall health and productivity of the actual employee. Currently, th e majority of the literature relating to HHC usage is relegated to clinicians, educators, and business executives. It is unclear as to what HHC applications may be useful to public heath empl oyees or how they adopt and use HHCs. It is likely that rapid access to information probably repr esents the single most visible and widespread effect of HHCs in public hea lth and health care today (Cim ono & Bakken, 2005). By using HHCs, public health employees gain the ability to not only have acces s to (and share) data, but at the same time also be able to obtain new inform ation updates relating to guidelines, strategies, and promising practices that can be used to prev ent both infectious and ch ronic diseases. Specific applications of HHCs in the public health field may include Serving as a conduit for employeeâ€™s profe ssional development through online/downloaded training, Replacing the multitude of physical references th at public health employees have to either bring into the field or stor e in their physical office, Communicating with other staff via voice, email, or other type of electronic communication, Obtaining updated epidemiological data,
16 Conducting online literature searches, Monitoring real-time surveillance data, Reviewing policies/legislation databases from the federal, state, or local level, and Sharing documents and spreadsheets w ith other professionals in the field. Unfortunately, there is currently no validat ed instrument that assesses HHC usage specifically among public health employees. It is also unclear as to wh at relationship, if any, handheld computers have on a public health empl oyeeâ€™s anxiety and self-e fficacy related to use of the technology. Another potential advantage for those in public health who utilize a HHC is the ability to store and transmit large amounts of data through a number of different mechanisms. Taylor (2005) and others (Al-Ubaydli & Paton, 2006) described the use of flash memory in the form of removable cards, such as memory sticks, secure digital (SD) cards, a nd compact flash cards similar to those used in digital cameras offeri ng potentially unlimited data storage for the HHC. While it appears that clinical providers are begi nning to take advantage of portable data storage (Honeybourne, Sutton, & Ward, 2006), it is unclear as to whether or not those in public health are taking advantage of this â€œdat a portabilityâ€ in term s of surveillance, conducting health risk appraisals, or evaluating program ming indicatorsâ€”all of which are mainstays in the public health field. In addition to serving as an effective medium for storing data, HHCs have the ability to transmit data to other devices. HHCs can use a wi reless feature to â€œbeamâ€ information to other compatible HHCs, printers, or systems using an infrared transceiver port. Many of the newer HHCs can use wireless technology to access inform ation from a local area network (LAN) or wireless local area network (WLAN).
17 Currently, the literature shows a clear absence of HHC wireless applications being used in the public health field, as well as a corresponding vacancy of HHC applicati on use in general. It is unclear not only whether or not public hea lth employees consider HHCs useful, but also whether or not HHC use relates to its associated anxiety and self-efficacy and ultimately their productivity. Anxiety is â€œa normal state of apprehension, tension, and uneasine ss in response to a real or perceived threat.â€ Although anxi ety is considered a normal res ponse to temporary periods of stress or uncertain situations, it is possible that prolonged, intens e, or inappropria te periods of anxiety may impair daily functioning then, in turn, becomes an anxiety disorder (USDHHS, 2006). Anxiety has been increasing sharply in th e workplace (HSC, 2004) and in the nation as a whole (Kessler, Chiu, Demler, Walters, 2005). At the individual employee level, general anxiety has been found to lead to impaired work pe rformance (Haslam, Atkinson, Brown & Haslam, 2005), accidents, absenteeism, and a host of othe r psychological and physiological symptoms. At the organizational level there are likely to be effects on productivity (Kar asek & Theorell, 1990), staff morale, accidents (Haslam et al., 2005), abse nces, and staff turnover (Maslach, Schaufeli & Leiter, 2001; Siegrist, 1996; Turner, Wheaton & Lloyd, 1995). In regards to computer-related anxiety, there are concerns that computers in general may relate to anxiety of individual employee (Arnetz, 1996; Berg et al., 1990; Berg et al., 1992; Carmichael & Roberts, 1992; Ericson & Kallen, 1986; Helge, 2001; Marriot & Stuchly, 1986; Mill er & Duncan, 1988; Hunting et al., 1981; Nielsen, 1982; Pascarelli & Kella, 1993; Sc hnorr et al., 1991). Additionally, research has found that higher le vels of computer a nxiety were linked to less interest in computers in general (Czaja et al, 2006; Ellis & Allaire, 1999). As a result, public health employees that are required to use computers (i ncluding HHCs) but have high level of computer
18 anxiety may have difficulty performing their jobs right. Currently, there is an absence in the published scientific literature pertaining to anxiety specifically associated with HHCs. As with HHC-related anxiety, there is also an apparent void in the literature relating to HHC use and its associated self-efficacy. The concept of self-efficacy is based on Banduraâ€™s Social Cognitive Theory (SCT) (1982). In essence, SCT suggests that two types of forces guide a behavior and beliefs about oneâ€™s ab ility to perform that behavior; these beliefs about oneâ€™s ability are called self-efficacy. Many variab les have been shown to infl uence an individualâ€™s selfefficacy with information technology in genera l, including gender, age, education level, computer ownership, computer experience (Mah ar, Henderson, & Deane, 1997; Marakas, Yi, & Johnson, 1998), professional orientation (S mith, Conway, & Karsh, 1999), training, organizational support, management support, en couragement (Henderson et al., 1995), and computer attitudes (Ogletree & Williams, 1990). It is thought that many of these variables are associated with computers specifically (Cassi dy & Eachus, 2002); howev er, it is unknown if these variables are also associated with HHCs. Self-efficacy beliefs have repeatedly been repo rted as a major factor in understanding the frequency and success with which individuals use computers. Additionally, computer selfefficacy is reported as an important predictor of computer anxiety (Czaja, Charness, Fisk, Hertzog, Nair, Rogers, Sharit, 2006). Compeau & Higgins (1995) found that individuals with high self-efficacy used computers more, enjoye d them more, and experienced less computer anxiety. Others found that computer self-efficacy beliefs affected whether individuals chose to use computers irrespective of their beliefs abou t the value of doing so (Hill, Smith, and Mann, 1987). However, there is currently a gap in the literature relating to HHC use and the relationship
19 (if any) with self-efficacy. Add itionally, while little is known as to whether or not increased HHC self-efficacy relates to decreas ed anxiety, it seems logical that such a decrease would exist. According to Bandura (1977), theoretically an individualâ€™s physiological and emotional state (i.e., feeling anxiety) relates to those judgm ents that are made in determining self-efficacy and resultant behavior. Consequently, by decrea sing an individualâ€™s an xiety (through improving self-efficacy), a desirable behavior performance (e.g., increased productivity) may be obtained. Significance of the Study HHCs are a tool that is becoming pervasive within the professional world. While they originally were used almost ex clusively in corporate and the c linical sector, usage has expanded to include other realms including education a nd public health. With its larger storage and advancing performance in graphs and videos, it is expected health educators will soon be incorporating HHCs as part of their planni ng, assessment, implementation, and evaluation process. This study assessed public health empl oyeesâ€™ HHC usage, self-efficacy, anxiety related to HHC usage, and their relationships. Results of this sentinel study can become the basis for future studies and provide the public health field with a tool that determines the psychological impact of HHCs and a resultant probable effect on productivity. Furtherm ore, this study provides the necessary initial steps to establish HHCs as an agent that promotes pr ofessional portability in the field of public health and implicati ons to the use in health education.
20 Purpose of the Study More now than ever, employers promote the use of IT tools while adopting worksite health promotion and disease prevention efforts in order to increase productivity, morale, and retention. Most of these programs seek to reduce behavioral (i.e., anxiety and/or low self-efficacy) risk factors to improve employeeâ€™s health and th ereby lower health car e costs (Aldana, 1998; Pelletier, 1996; Directors of Health Promotion and Education, 2006; Kolbe, Tirozzi, Marx, Bobbitt-Cooke, Riedel, Jones & Schmoyer, 2006). Employers seek to create work environments that support healthy lifestyle s and overall employee health. As physical and psychological symptoms of anxiety have been often reported to impair work performance, it is in the best interest of public hea lth employers to focus on addressing bo th HHC-associated anxiety and selfefficacy while implementing/requiring HHCs at wo rk to ensure optimal employee performance. This is especially important considering that e-health in general, and the use of HHCs specifically, are growing in the professional field and the emerge nce of new technologies makes it likely that there will be new forms of dema nds on the employeesâ€™ health (Hesketh & Neal, 1999). Problem Statement The purpose of this study is to assess pub lic health employeesâ€™ use of HHCs and the corresponding HHC self-efficacy and HHC anxiety re lated to their usage. Specifically, this study is designed to Develop a reliable and valid instrument to measure use of HHCs; Determine if there is an association between HHC use and HHC self-efficacy among public health employees; Determine if there is an association be tween HHC use and HHC anxiety among public health employees; and Determine if there is an association between HHC self-efficacy and HHC anxiety.
21 Research Questions The purpose of this study will be to evaluate the following research questions: Is every scale that comprised the instrument reliable? What results regarding each scale and each it em within the scale of the instrument does item analysis show? Is there an association between HHC us e and HHC self-efficacy among public health employees? Is there an association between HHC use and HHC anxiety among public health employees? Is there an association between HHC self -efficacy and HHC anxiety among public health employees? Definition of Terms Anxiety: Anxiety is â€œa normal state of apprehen sion, tension, and uneasiness in response to a real or perceived threat.â€ Although anxiety is considered a normal response to temporary periods of stress or uncertain s ituations, it is possible that prol onged, intense, or inappropriate periods of anxiety may impair daily functioning then, in turn, becomes an anxiety disorder (USDHHS, 2006). HHC anxiety: The definition of HHC anxiety has been modified from computer anxiety in general to be defined as the ability of comput er work to induce a psychophysiological arousal pattern in sensitive workers (Arnetz, 1996; Arnetz, 1997; Berg et al., 1992). HHC Use: For the purposes of this study, HHC us e is indicative of HHC use for jobrelated tasks. HIPAA: Privacy determines who should have acce ss, what constitutes the patientsâ€™ rights to confidentiality, and what constitutes inapprop riate access to health re cords. Confidentiality establishes how the records or systems that hold those reco rds should be protected from inappropriate access. Security is the means by which privacy and confidentiality are measured.
22 In 1996, the Health Information Portability a nd Accountability Act (HIPAA) was passed by the US Congress to amend the Internal Revenue Code of 1986 to improve porta bility and continuity of health insurance coverage in the group and in dividual markets, to combat waste, fraud, and abuse in health insurance and health care de livery, to promote the use of medical savings accounts, to improve access to long-term care services and coverage, to simplify the administration of health insurance, and for other purposes. (Laskin & Davis, 2004; USDHHS, 2006). HHC: A personal digital assistant known as a handheld device that allows electronic management via software programs or applicat ions such as but not limited to calendar, contact/address book, memos/notes, various textbooks including medical health care, personally created files under popular software programs (s uch as Word, Excel, PowerPoint), games, connection to the Internet with wireless capab ility, digital photography, MP3 capability (music files) and phone capability. (Armour, 2004). OS/Platform: Known as the operating system that suppor ts files. PC or desktops are either Windows or Apple platform. HHCs use either Palm OS or Microsoft Windows CE. The operating systems are not fully compatible at this time for the sharing of applications between different platforms; limited inform ation sharing may occur (Armour, 2004). Public health: The sum of all official (government al and non-governmental) efforts to promote, protect, and preserve the peopl eâ€™s health (McKenzie & Pinger, 1997, p.4). Self-efficacy: Self-efficacy refers to the judgments an individual makes about his or her capabilities to mobilize, cognitive resources, and courses of action needed to orchestrate future performance on a specific task (Ban dura, 1986; Gist & Mitchell, 1992).
23 HHC self-efficacy: HHC self-efficacy has been modified from computer self-efficacy in general to refer to the judgment s an individual makes about his or her capabilities to mobilize, cognitive resources, and courses of action needed to orchestrate future performance on a specific task in relation to the use of HHCs (Bandur a, 1986; Brosnan, 1998; Gi st & Mitchell, 1992). Synchronize: The connection of the HHC with the desktop or laptop computer via a portable cable, base, or infrared port that allo ws communication between the two devices. The communication allows the sharing of informati on between two devices. Software applications are typically downloaded to the PC/desktop and then transferred by synchronization/hot synching with the HHC. Applications will update the HHC with the most current information available each time a user synchs their HHC to a computer connected to the Internet (Armour, 2004). Tablet PC: It has the power and func tionality of a conventiona l laptop computer, coupled with a fold-flat or detachable touch-sensitive scre en. It also has the ability to record handwritten notes and diagrams (Hoppe, Join er, Milrad, & Sharples, 2003). Delimitations of the Study The following delimitations should be considered in this study. The study focuses on HHCs only. Study participants include volunteer public heal th employees who are affiliated with the Society for Public Health Education (SOPHE ), the Directors of Health Promotion and Education (DHPE), and the National Associa tion of Chronic Diseas e Directors (NACDD). The study focuses on three fact ors that are related to HHC usage among public health employees including: 1) the extent of public health employeesâ€™ reported HHC usage, 2) the extent of public health empl oyeesâ€™ reported HHC self-efficacy, and 3) the extent of public health employeesâ€™ reported HHC anxiety. Data was collected durin g calendar years 2006 and 2007.
24 Limitations This study is limited by: the subjects being drawn exclusively from the memberships of three national nongovernmental organizations. those subjects who are member s of the three nati onal non-governmental organizations and are listed on the organizationsâ€™ email listserv. the use of self-report instruments. the use of an online survey.
25 CHAPTER 2 REVIEW OF THE LITERATURE This study will assess public health empl oyeesâ€™ use of HHCs and the corresponding HHC self-efficacy and HHC anxiety. This literature review will addre ss stress and anxiety in the workplace, self-efficacy as a construct related to facilitating behavior, HHCs in the health field, and the population of public health employees. Furthermore, an overview of Social Cognitive Theory, self-efficacy, anxiety, and the relatio nship between the two is also presented. Use of Handheld Computers The term HHC, sometimes referred to as a Pers onal Digital Assistant, PDA, or Palm Pilot, is assigned to a wide variety of small pocket-size d computers. Similar to a desktop computer, the core of a HHC is built around a microprocesso r. Although the current typical/conventional desktop computer microprocessor is rated at ove r 1 GHz, the typical HHC processor operates at lower, energy-conservative speeds of betw een 200 MHz MHz (CNet Reviews, 2007; Flanders et al., 2003; ZDNet, 2006). However, ther e are currently HHCs that are as fast as 624 MHz (Hillebrand, 2006). Instead of a monitor, the output or display is made of an energy efficient, flat panel display similar to those used on notebook computers. HHCs commonly feature applica tions referred to as personal information management (PIM) programs that consist of an address book, a date book with alarm clock and digital agenda planner, a memo or document composer, and a remi nder or â€˜to-doâ€™ list (Fla nders et al., 2003). In addition, todayâ€™s HHCs offer many of the feat ures that are found on a desktop or laptop computer. Word processing, spreadsheets, pres entational software, and many other computer programs are available for a HHC. As a result, HHCs often have seamless compatibility with such software as the Microsoft Office Suite (Word, Excel, Outlook, and PowerPoint) and HTML files (Daniels & Salisbury, 2003; Luo, 2004). A dditionally, other potential functions of HHCs
26 may include gaming, MP3 listening, digital camera, cell phone, Global Positioning Systems (GPS), external keyboards, voice recording, Bluetooth capability, developing and practicing presentations, Wireless-Fidelity (WiFi) readines s, and/or a barcode read erâ€”all of which have been found to be used and useful in many areas of the workforce, incl uding education, business, and health care (Bernhardt et al., 2001; Bri ggs, 2004; Hirani et al., 2005; McCombs, 2004; Smartphone & Pocket PC, 2006; Thomas, 2003; Thomas, 2004-2; Volsko, 2004). Furthermore, HHCs seem to be well suited for many tasks that relate to public health employees as well as others because they are portable, able to mainta in complex databases, st ore both text and graphic image data, and can accurately, reliably, and secu rely transmit data (often wirelessly) to a desktop computer data base (Kotler, 2004). Currently, digital communication can travel through serial, USB, Ethernet, Bluetooth , infrared, General Packet Radio Service (GPRS) , and other types of connections (Daniels & Salisbury, 2003; Duncan & Shabot, 2000; Hira ni et al., 2005; Ng & Yeo, 2004). HHCs with wireless capabilities could poten tially unlock a world of possibi lities in the public, including communication of subject data from a care-recei ver to public health employee, public health field employee to nurse, and nurse to clinician without the public hea lth field employee ever leaving the care-receiver (Felkey & Fox, 2003; Peterson, 2004; Thomas, 2004-2). In general, HHCs can be purchased with one of two main operating systemsâ€”the Windows CE operating systems produced by Microsof t (often referred to as Pocket PC) or the Palm Operating System (Palm OS) produced by Palm Source. The display on the Windows CE system looks similar to the display on deskt op computers that use Windows OS; the Palm OS display is unique (Eastes, 2004). Bo th types of devices have simila r features, such as the ability to beam data to another HHC or to an infrar ed port on a peripheral or laptop computer. Both
27 types of devices have a built-in keyboard and many have the ability to attach a full-sized keyboard to the HHC. Both OSs have a handwriting recognition system that allows the device to convert script into text. While there are many similarities between both the Pocket PC and the Palm, there are some marked differences as well. Originally, th e benefits of the Palm OS included simplicity, ease of use, reliability, practicality, and a seem ingly endless amount of software availability (Peterson, 2004; Suliburk, 2003). This is no longer the case; the Palm OS and Pocket PCs are now almost identical in functiona l capacity. It is no longer just Pocket PC HHCs that have more advanced multimedia capabilities and networking ability (Suliburk, 2003). In recent years, the differences between the OSs have become much narrower; furthermore, Palm has recently released a device that runs th e Windows OS (Hillebrand, 2006). Regardless of the manufacturer, all HHCs have several features in common: they are small, lightweight, and battery operated; they have a liquid crystal disp lay and touch screen, input is done with a keyboard or a handheld pen or stylus on a miniature, touch-sensitive keyboard or writing area for handwriting recogni tion; and they have an access port and software that allows data to be written to and r ead from a desktop computer. History of handheld computers. Considering the large amount of technology that is associated with HHCs, it is hard to believe that they have been around for over thirty years. A graduate student named Alan Kay at the Univer sity of Utah conceived a portable wireless computer in the 1970s; unfortunately, the c oncept never progressed beyond the prototype (Flanders et al., 2003). Initial de signs started out as a simple address book and calculator-like units to powerful hybrid computers with co lor displays, handwriting recognition, multimedia support, and wireless network capabilities (Fland ers et al., 2003). The early HHC devices, such
28 as the Casio Business Online Scheduling System (Casio Boss), had limited memory and input methods (Luo, 2004). They did not offer more than a paper-based personal information manager. John Sculley, the president of Apple Computers, first used the term â€˜HHCâ€™ in the early 1990s (Taylor, 2005). With the development of soft ware that could be in stalled on a device, the Apple Newton MessagePad provided more capabili ty than did devices like the Casio Boss (Flanders et al., 2003; Luo, 2004). The Newton, in concept, was ahead of its time, when the Apple product first entered the market in 1993 (Shipman & Morton, 2001). Innovative to its design was the absence of a conventional keyboard and the use of a stylus, a touch screen, an early form of handwriting recognition, and infrared capabilities (Flanders et al., 2003). However, the Newtonâ€™s rather large size, expense, and poor recognition of handw riting were significant shortcomings. These devices were not widely adop ted by either the general public or the medical community. But in the mid-1990s, there was a resurgence of HHC use with the introduction of new HHC operating systems (Volsko, 2004). Palm Com puting deserves credit for starting this phenomenon with the introducti on of the Palm Pilot in 1996 (Luo, 2004). This device had a similar handwriting recognition cap ability as the Newton, although it was much smaller, cheaper, faster, and lighter (Flanders et al ., 2003). The Palm Pilot is often the name that has been used as a generic term to describe all HHCs that use Pa lm OS. The correct name, however, is a Palm HHC (Laskin & Davis, 2004). This well-designed device was small, easy to use, could backup information on the desktop computer, and offered character recognition. According to Cain (2003), the market is now quickly expanding beyond the use of HHCs as an â€œorganizer.â€ For example
29 The medical industry has been an early a dopter of the HHC. Physicians and nurses comprise a mobile workforce, so the portab ility of the HHC, especially in a wireless environment, is attractive. HHCs have been working their way into highe r education, first with heavily scheduled administrators and interested faculty, and now with some student populations. In addition to using the devices for in-class note taking, students are taking multiple choice tests and doing simulations and experiments. Even more recently, the head of Intel announced a mobile personal computer designed to provide affordable collaborative learning environments for teachers and students around the world. Eduwise will feature a built-in wireless network, run Microsoft Windows, and cost less than $400. It is thought that it will allow students in a classroom to view presentations, take tests, and in teract individually with their teachers using the built-in wireless conne ction (Slagle, 2006). HHCs among Public Health Employees While HHC use is clearly on the rise, there is virtually no publishe d literature relating specifically to public health employees and their use of HHCs. One clinic ally related article, however, did include public health professionals in their sample. De Groote (2004) sought to determine the various HHC training needs of diff erent health science students, faculty, and professionals in order to provide focused instruct ion that would meet thei r wide range of needs. Specifically, a survey was developed to measure the level of HHC usage in the college and the level of training and support that would be necessary. Of the 1,538 individuals who were sampled, 57 were public health faculty; the resu lting overall response rate was 24%, of which only 17 (30%) of the public heat h faculty responded. Of these 17 individuals, 8 used a HHC. Of all those (n=170) who res ponded to the survey (including public health faculty) and did own and use a HHC, 76% used their HHCs several times a day, 9% used their HHCs once a day, 2% used their HHCs once a week, 4% used their HHCs two to three times a week, and 7% rarely
30 or never used their HHCs. Among public he alth faculty, 100% used their HHC for time management, 11% used it for email, 11% used it for Web access, and 11% used it for â€˜other.â€™ De Groote (2004) points out that it is quite pos sible that HHC owners were more likely to answer the e-mailed survey th an non-HHC owners, and therefor e, HHC ownership and use may be much less on the campus than reflected in the survey. However, of those respondents who used HHCs, most used them regularly and th e address book, date book, an d calculator were the most commonly used applications. Finally, the aut hor suggests that they found little evidence of HHC use among public health employees; this sugge sts that the potential of HHCs in the public health field is relatively unexplored at this time. Although HHCs have been touted as having the ability to improve efficiency and safety, little is known about HHC user sâ€™ application and their at titudes about HHCs (McAlearney, Schweikhart, & Medow, 2004). Carroll & Ch ristakis (2004) randomly sampled 2,130 pediatricians with a five-minute survey to indicate HHC use, make and model, and the applications they used. They also asked about th e potential strengths of HHCs to improve health care and impediments to their use. The authors found that 35% currently use a HHC at work, and 40% currently use a HHC for personal use. The ma jority of those using HHCs used one that ran a Palm OS. Of those using HHCs, the most commonly used applicatio ns in the work setting were for drug reference, personal scheduling, medical calculations, and com puterized texts. Few pediatricians were currently using HHCs for pr escription writing or billing. In general, users were somewhat more likely to feel that HHCs have greater potentia l to improve health care than nonusers. With respect to barriers to the use of HHC s, nonusers felt that each of the potential weaknesses was more of an impediment than users. The greatest impediments were felt to be the
31 difficulty of data entry into a HHC. Both users and nonusers agreed that HHCs have the potential to decrease medical errors and improve efficiency. Users were also more likely to view the small screen size or system instability as an impediment to use. Others have investigated usability as well. Johnston, Leung, Tin, Ho, Lam, & Fielding (2004) randomly sampled 169 fourth-year medi cal students to determine HHC usefulness, satisfaction, functionality, and uti lization. In general, HHC utilization was low. Students reported calendar function use slightly more than once pe r week, whereas they used other HHC functions less than once per month. McAlearney, Schweikhart, & Medow (2004) as sessed usability by conducting eight focus group sessions with 54 physicians to determine: 1) how and why doctors use HHCs in clinical practice, 2) what barriers physic ians perceive with their use a nd how these could be overcome, and 3) what physicians expect from their use in the future. After analyzing the data, the authors found that the frequency and intensity of HHC us e varied, and on the basis of this they found that: 1) nonusers had never used HHCs or had abandoned them, 2) niche users included those whose use was restricted to a single applicati on but reported that this limited functionality was sufficiently valuable such that they would cont inue use, 3) routine us ers had integrated HHCs into their clinical workflow using multiple appl ications on a regular basis, and 4) power users were eager to showcase their latest device. Phys icians perceived benefits of HHCs to include enhanced productivity and enhanced quali ty of patient care and service. In these studies, the two main barriers to us ing HHCs were personal issues and the device itself. Issues concerning the device included size, limited memory and battery life, and speed of data exchange. The two main personal barriers were physical constraints (e.g., eyesight), and perceptual constraints, includi ng comfort with the device. Anot her major barrier for nonusers in
32 all groups was their perception that they did not receive, or expect to receive, enough value from the devices to change their existing patterns of practice. Physicians also were concerned about dependency on the devices, especially among routine users and power users (McAlearney, Schweikhart, & Medow, 2004). All of these possible barriers are certainl y relevant to public health employees. As far as expectations about future use of HHCs, most physicians thought that the trend towards incorporating new electronic technol ogies into medicine would continue. Many clinicians believed that HHCs were destined to become critical because of their potential to improve patient safety and quality of car e (McAlearney, Schweikhart, & Medow, 2004). The authors also noted that it is not yet understood how physicians acr oss practice settings view or value the devices, nor if they ha ve concerns about HHC usage. As a first step towards understanding how HHCs might benefit an institution as well as individual users, Barrett et al (2003) asked 223 resi dents to fill in a brief survey of HHC usage, and then interviewed a subsample of these reside nts in order to obtain more details on their HHC usage. These results, a systematic review of re sidentsâ€™ perceived HHC n eeds, are important not only for exploring what these residents curren tly think about HHCs, but also for providing a foundation for further analysis of perceived needs in other hea lth care groups (e.g., nurses, administrators, etc.) and actual usage by residents. When asked what the top advantages of HH Cs were, residents reported the following: speed of getting information, ability to help organize their professional calendars, contact information for either patients or colleagues, and drug information. When asked what the three most common applications were, responses incl uded: personal organize rs including calendars and address books, drug guidelines a nd medical references, and medi cal calculators. When asked
33 about the main disadvantages, they replied: data loss due to hardware or software failures, manual data entry is too sloppy, and the physical si ze of the device was too small (Barrett et al., 2003). Similar to the findings from McAlearney, Sc hweikhart, & Medow (2004) , there were also concerns about developing an absolute dependenc y on a device that can catastrophically fail or easily be lost. Barrett et al., ( 2003) suggested that future dire ctions of research include identifying information seeking behavior of re sidents and studying how HHCs are currently used for information seeking, and then considering ways HHCs might enhance information seeking and gathering in the future. Clinical setting . The integration of HHCs into the de livery of healthcare continues to grow and HHCs are already used in a number of healthcare specialties (Hirani et al., 2005). HHCs have evolved from being pr imarily personal information managers into essential tools with an enormous range of applications (Clauson et al., 2004). Some say that it will not be long before the HHC will replace individual tools such as cell phones, pagers, and voice recorders and become as common in the laboratory coat of a physician as is the st ethoscope (Miller, 2004; Suliburk, 2003). HHC-focused studies published to date in the health care li terature have been conducted among physicians and limited to the study of pr evalence of all-purpose HHC use, calculating common clinical parameters (e.g., body mass i ndex), improvement in care through use of a specific HHC reference applica tion, or data entry for resear ch or generation of reports (McCaffrey, 2003; Merrell et al., 2004; Stroud, Erkel, & Smith; 2005; Torre & Wright, 2003). In addition, studies focused on clini cal providers have investigated the application and merit of HHCs in specialty areas such as orthodontics (Hirani et al., 2005), veterinary (Bristol &
34 McWhorter, 2002), radiology (Flanders et al., 2 003; Nishino et al., 200 4; Busch et al., 2004), obstetrics & gynecology (Joy & Benrubi, 2004), em ergency medical serv ices (Vokey, 2004; Schuerenberg, June 2004), and pharmacy (Brilla & Wartenberg, 2004; Felkey & Fox, 2003; Collins, 2004; Clauson et al., 2004; Bosinski et al., 2004) . Nursing applications . While there are those employed in public health who may be considered clinical providers, most public health employees that have a cl inical billet are public health nurses. Currently, there is a growing body of literature that relates to HHC within nursing applications; for example, Eastes (2004) states that HHCs are an immensely powerful tool for nurses. Because of their size and portability, HHCs can be useful in research and data collection, especially those HHCs that come with a built-in digital camera. For example, this may be used for documenting patient wounds. Nurses in the fi eld can also have instant access to medical records, visit schedules, contact information, a nd all of the vital material needed to manage highly acute home care patients (Tweed, 2003). Bei ng able to access and modify this data can help to facilitate faster co mmunication between nurses, physicia ns, therapists, and home-care aides. As a result more timely responses can be made according to patientsâ€™ changing conditions. There are other implications for nurses as we ll. There are many beneficial ways to use HHCs in practice, including having rapid acce ss to drug information, clinical diagnoses, arranging appointments, patient records and doc umentation, journals, abstracts, and Internet capabilities (Armour, 2004; Pusk ar et al., 2004; Rosenthal, 2 004; Taylor, 2005). HHCs can help nurses perform regular daily tasks in a much quicker timeframe, such as accessing patient testing results while doing patient education. As more nurses have started adap ting HHCs for clinical use, they report that they have been helpful in organizing current info rmation to better offer quick point-of-care access (Enger & Sega l-Isaacson, 2001; Puskar et al., 2004).
35 Nurses are also starting to pr ovide reports by beaming information from one nurse to the next, and this opportunity may assi st in providing concise and c onsistent information from one shift to the next (Tooey & Mayo, 2003). Currently there are many software applicati ons for HHCs that may prove to be of real assistance to advanced-practice registered nurses including pa tient tracking, drug information, digital photography for clinical cases, diseas e review, differential diagnoses, and even a prescription-writing program that allows prescripti ons to be written in the HHC and beamed via an infrared port to a compatible pr inter (Armour, 2004; Lewis & Sommers, 2003). Puskar et al., (2004) noted that a HHC not only allows a behavi oral health nurse to gather data on the patient at the bedside, but also allows them to quickly research unfamiliar medications and medical conditions. Furthermore, another benefit can be the increase in the development of computer-based outpatient behavioral interventions focusing on patient education and counseling. The authors also note that there is a need for the literature to discuss the benefits of HHCs and examine how they can be utilized in the field of behavioral health. With the expanding use of HHCs in the nursi ng field, many nurse practitioners (NPs) have found the value of using HHCs. For example, curre nt standards of care and best practices have become readily accessible and NPs can gather, enter, and store data directly at the point-of-care. Stroud, Erkel, and Smith (2005) found in their st udy that, based on an ove rall prevalence of HHC use of 67%, both faculty and st udents find a HHC to be useful. The authors also found some emerging patterns among the NPs. For example, th e participants frequently planned their daily events via the calendar/data book feature. Also, NPs were using their HHCs to make clinical decisions such as determining appropriate drug and dosages amounts for patients, drug interactions, and contraindicati ons for prescribing a drug. NPs were finding the least costly
36 alternatives for treatm ent, identifying options for differe ntial diagnoses decisions, consulting patient records, accessing patient education ma terials, and improving patient care via using clinical practice guidelines. In addition to noting the stre ngths of HHCs, some have identified potential barriers. Kerkenbush & Lasome (2003) explored the em erging role of HHCs for capturing electronic diaries in the management of diabetes and to address the implications for todayâ€™s NPs, particularly those in the outpati ent setting. The authors found some possible barriers to HHC use. For example, those who might be particularly we ll-suited to this technol ogy include patients who already own and use a HHC for other purposes , patients comfortable with technology and computers, patients without visi on or dexterity problems that would prevent them from being able to use a HHC, and patients who maintain an active lifestyle and are looking for an easy way to monitor their diabetic diary. Also, the cost of a HHC may be prohibitive for some patients. Education setting. Although scientific publications de scribing the application of HHCs have been fairly recent, they have already b een shown to be a valuable resource for both practicing clinical medicine and teaching and l earning. As HHCs become le ss expensive, easier to use, and capable of storing a greater amount of information, their diffusion will likely continue to spread in academia and public health. As health education is an important facet within public health, the base of literature relating to schools an d education in general is especially applicable to many public health employees. Bauer & Ulrich (2002) state th at educators can use HHCs to allow students to: self-monitor behavior, self-report grades, beam lecture notes and assignments, read books, set reminders, use as a parent/teacher communication tool, use as a graphing calculator, and facilitate student collaboration. Educators who are well versed and co mfortable with current uses and applications
37 of HHCs will be well positioned and ready to ta ke advantage of new HHC resources as they become available. Over the past several years, HHCs have emer ged as a viable altern ative to desktop and laptop computers in elementary and secondary e ducation. Some even see HHCs as the next tool that will change the face of ev eryoneâ€™s lives (Oravec, 2001; Pownell & Bailey, 2001; Roschelle, 2003). However, the use of HHCs in the classr oom is not new. Teachers have used HHCs to record their observations, take notes, and manage their schedules for years (Bauer & Ulrich, 2002). Educators have seen a range of possible imp acts that can occur as a result of HHC usage by students, including: using an infrared port to beam homewo rk assignments to the teacher, taking notes on field trips, measur ing a studentâ€™s ecological footpr int, increased time on task, higher test scores, lower cost, enhanced student collaboration, and increased student motivation (Norris & Soloway, 2003; Roschelle, 2003; Stov er, 2001). Specifically, advantages of HHC usage are especially evident in terms of cost. Norris & Solowa y (2003) identified that â€œwhile desktop and laptop computers will have a place in the foreseeable future, as personal computing devices they are not particularly appropriate for [education] (p.27) .â€ PCs take up too much space, they need electricity on a regular basis, and they are overly complex. A HHC, on the other hand, is a low-power device that can go anywhere and be used almost everywhere (Ray, 2003). HHCs have even been used for preschool. Mill er et al (2002) desc ribe how HHCs were used to conduct observations in preschoolersâ€™ classrooms to document social and emotional behavior of preschoolers from low-income fa miliesâ€”without interrupting classroom activities, and still providing an ecologically valid and feas ible way to gather intensive observational data in a classroom-friendly, effici ent, and unobtrusive manner. Head Start preschoolers in three
38 schools were observed in their classrooms while emotional displays and social engagement behaviors were coded in real time using HHCs. Norris & Soloway (2003) and Roschelle ( 2003) provide additional examples of applications of HHCs in the classroom. For example, students can use HHCs to do concept mapping, text editing, infrared-enabled sharing of data, and animation programs. As a result, students may be more productive, more likely to re vise their work, and more likely to collaborate with others. However, for this â€œ HHC revolutionâ€ to occur in school s, the authors identified that the six conditions that must be met are su fficient access to technology, adequate teacher preparation, evidence-based curriculum, relevant assessm ent, supportive school/district administration, and supportive family/community. Currently, there are already examples of successf ul applications of HHCs in the classroom. Bauer & Ulrich (2002) describe what happened when teachers gave 28 sixth graders (six of which had special needs) HHCs over the course of si x weeks. The authorsâ€™ intent was to evaluate whether the use of HHCs endured. The class aver age during a five-day week ranged between 4.5 and 4.8 days of use for recording assignments, between 1.8 and 2.7 days for recording events, and between 2.2 and 3.9 days for checking thei r math using the calculator on the HHCs. However, every student reported preferring the HHC to a traditional notebook for recording assignments. Interestingly, students with identified special needs we re the strongest users of the handhelds, consistently indicati ng daily use and preference for ha ndhelds. The authors also found that girls were less likely to download progr ams from the Web, but were more likely to beam information to a friend. All but one of the 28 stud ents viewed the handheld as a useful tool and felt that it was important for the students to be able to use handheld technology.
39 Aleahmad (2002) presented an innovative appl ication of handheld technology for science education. Denver public schools helped science t eachers integrate Web-based science activities (WISE) into their courses. The goal was to deve lop HHC activities that would complement their existing library of Web-based projects. They sou ght to integrate the use of HHCs with existing WISE curriculum to enable both data collection activities like surveys, field observations, and data analysis activities. The intervention focused on two areas: convenient and portable data creation, and portable dynamic content. For exam ple, in one genetically engineered foodsoriented project, students downloa ded a survey onto their handheld, and then interviewed their family and friends on dietary habi ts and beliefs about genetically engineered foods. Afterwards, students synched with the classroom PC and provided the entire cl ass with their data. Other class projects included a focus on bi ology and oceanography content. In both of these areas, students embraced the use of HHCs more quickly and eas ily than the instructors had expected. Students had no difficulties navigating the forms on the HHC or using the handwriting recognition software. Aleahmad (2002) suggested th at future research investigate how handheld technology can improve studentsâ€™ ge neral inquiry skills. The author also suggests that the WISE learning environment and handheld computing ar e synergistic. The HHC provides the mobility necessary to collect real -world data and observations and to bring dynamic content outside of the classroom. Even private industries are becoming more incl ined to facilitate the use of HHCs in the wireless local area network (WLAN) classroom (Stover, 2001). Pfeiffer & Robb (2001) reported how a school in Baltimore welcomed school-busine ss partnerships to help keep pace with the increasing technological demands. The goal of th e partnership was to provide cutting-edge, reasonably priced, networked mobile computing pl atforms for learning. This platform consisted
40 of a wireless local area network (LAN) that conn ects HHCs to educational tools and content both inside and outside of the classroom. Instructors may find a large number of benefits, including: 1) time was no longer wasted pulling wire and inst alling computer jacks; 2) space was no longer wasted for computer labs; 3) student productivity seemed to be increased; and 4) teaching activities were changed to be more project-ori ented than information sharing (Pfeiffer & Robb, 2001; Stover, 2001). The authors su ggested that schools must turn to sources other than the government to keep pace with the demand for technology resources. With a grant from Hewlett-Packard, students were given 33 HHCs with wireless cards to use for a semester (Futhey, 2000). Students ha d the opportunity to experience multiple applications within a variety of courses. For example, a chemistry professor used software to administer concept tests (short multiple-choice qu estions posed in the lectures). Students from the design, computer science, and engineeri ng departments use the handhelds in a crossdisciplinary project course that introduced the concept of rapid prototyping, and a student team devised software that allowed the HHCsâ€™ screens to share collaborative applications so that students in the same room or across campus could exchange project designs, compile group notes, and share other information. Uses for HHCs in medical education have b een limited to documenting patient encounters and procedures done, retrieving medical inform ation, checking schedules and patient data, recording evaluations, and stori ng reference materials (Miller et al., 2005; Sutton et al., 2004; Torre & Wright, 2003). Interestingly, a concern that has surfaced within the literature is whether or not there are negative effect s of using a HHC. For example, were the students paying more attention to the HHC than to thei r instructor (Sutton et al., 2004)?
41 Bertling et al., (2003) sought to expand the role of HHCs beyond monitoring learnerâ€™s clinical experiences, to use the HHCs as a â€œteachingâ€ and clinical resource tool. For example, students have found the HHC a useful teaching tool for focused medical problems such as lower respiratory infections, hypertensi on, colorectal cancer screeni ng, and spiritual assessment. The author reports that faculty have created a vari ety of HHC teaching applic ations to facilitate knowledge and skill application, as well how to access and use electronic information that may improve patient care. Additionally, others have used HHCs to track attendance, simplify data collection, and facilitate grading a nd progress reporting (Stover, 2001). Similarly, the Stanford HHC project aims to integrate HHCs into medical education (Moffett et al., 2003). This project began with a focus on preclinical trai ning, with the goals of content creation, infrastructure development and integration, technical support, and assessment of HHCs and other mobile computing technolog ies. After two years of implementation, the authors found that the majority of the medical students used th eir HHCs more than once daily and were glad to have learned how to use th e HHC before reaching their assigned clinics. Greenberg (2004) distributed HHCs to 137 thir d year medical students when they began their clinical rotations. Each HHC was preloaded with Five Minute Clinical Consult , ePocrates Rx , ePocrates qID , iSilo , and Patient Keeper . The author also loaded AppUsage , which tallies the number of times each application is opene d and the number of minutes the application remains open. Students were tracked for three m onths and data was collected via focus groups, surveys, and AppUsage . The author found that while the usefulness of each application was rated highly, total usage time decreased for each applicati on. Greenberg (2004) speculated that this may have been caused by increased student skill or comfort levels with the HHC, resulting in increased student
42 efficiency when using an application. Student s also reported that the HHC made them more efficient by enabling them to manage patients, access information more quickly, and carry fewer books. HHC technology, combined with wireless prot ocols and streaming video technology, has the added potential to become a powerful educati onal tool for medical students and residents. Gandsas et al., (2004) conducted a study to assess the feasibility of tran sferring multimedia data in real time to a HHC via a wireless network and displaying them on the computer screens of clients at remote locations. The authors believed that if the medical st udents could be equipped with HHCs having access to a wireless comm unications system, the existing learning opportunities can be made more convenien t and fewer opportunities will be missed. Gandsas et al. (2004) transmitted a live la paroscopic splenectomy to eight medical studentsâ€™ HHCs simultaneously. Also, while the current processor power of the HHC was the main limiting factor for transmitting live streaming data resulting in a dropping of frames, the authors found that all eight view ers were able to view the proc edure and to hear the surgeonâ€™s comments throughout the entire duration of the operation. However, the authors stated that conducting clinical research to determine whether resident phys ician or medical students can benefit from the use of HHCs must do the va lidation of this new technology. They also speculated that surgeons might some day be able to log into an operating room from a remote location so as to provide advice and assist with the case via their HHCs. As with any technology, however, the value of the HHC will depend largely on whether users, including public health employees, find the device particul arly valuable for work-based applications (Stover, 2001). Base d on the large amount of research that has been done within the general field of education, it is readily apparent that especial ly those who are functioning as
43 health educators in public health can learn im portant lessons. For example, HHCs can be used for professional development traini ngs, providing technical assistan ce to constituents in the field, sharing information between colleagues when traditional methods ar e inaccessible, and collecting and an alyzing data. Public Health Employees Currently, there are approximately 500,000 public health employees in the United States (Centers for Disease Control and Prevention, 200 1). Those employed in the public health field consist of researchers, health se rvice providers, administrators, heal th educators, and others in a multidisciplinary environment that focuses on personal and environmental health. Public health employees can work in a variety of sectors (e.g., inte rnational, federal, state, territorial, or local) within a multitude of roles including physicians, di eticians, dentists, scientists, environmental engineers, therapists, veterinarian s, social workers, statisticians, computer scientists, and medical records administrators. Public he alth programs may address a vari ety of areas in cluding (USPHS, 2006): Providing healthcare and rela ted services to medically underserved populations, Preventing and controlling diseases, Improving the nationâ€™s mental health, Ensuring that drugs and medical de vices are safe and effective, Conducting biomedical, behavioral, a nd health services research, Working with other nations and internati onal agencies on solving collective health problems, Providing health education to youth, Promoting disease detection in communities, Reducing ergonomic-related injuries, and
44 Preparing for environmental and bioterrorism emergencies. Often these pursuits seek to protect the heal th of all Americans and provide essential human services, especially for those who are le ast able to help themselves (USPHS, 2006). Frequently, public health employees focus on addressing the nationâ€™s overall public health priorities, including: preventing disease, elimina ting health disparities, promoting public health preparedness, improving health literacy, promo ting organ donation, worki ng for healthy children in schools, and preventing osteoporosis (USDHHS, 2006-3). Advantages of using HHCs . HHCs have a lot to offer prospective public health employees. HHCs are lightweight, portable devices that have a long battery life (Bristol & McWhorter; Leibiger, 2002; Daniels & Sa lisbury, 2003; Thomas, 2003; Peterson, 2003). Furthermore, when a HHC is turned on, it imme diately resumes operati on without a period of prolonged booting-up period that is often required with laptop or desktop computers (Laskin & Davis, 2004; Peterson, 2003). Also, because memo ry and speed continues to evolve quickly, HHCs have processing speeds that are comparable to the desktop and notebook computers of just a few years ago. Furthermore, HHCs can be used in places that would be inefficient for notebook computers, such as environmental disasters a nd areas without electric ity (e.g., areas that are without electrical power for more than two hours). Al-Ubaydli (2004) states that HHCs have al ready brought important advantages to the health field. For many physicians, the organizer functions alone have been sufficient justification for buying a HHC. Many clinicians also like usi ng medical software to keep track of patient records. Additionally, the data connectivity of HHCs is improving the contribution that they can make to evidence-based medicine (Carroll , Tarczy-Hornoch, Oâ€™Reill y, & Christakis, 2004; Shabot, LoBue, & Chen, 2000; Volsko, 2004). It is likely that public health employees could have these same contributions.
45 HHCs offer a cost-effective, portable, and eas y-to-use platform for point-of-care-based health promotion, data collecti on, teaching, and curriculum evaluati on activities (Bertling et al., 2003). Furthermore, HHCs have been used effec tively for reducing medica tion errors, electronic medical records, billing, and to enable conveni ent access to health cont ent-related electronic journals (Armour, 2004; Bernard, 2003; Bertling et al., 2003; Bird, Zarum, & Renzi, 2001; Briggs, 2004; Carroll & Christak is, 2004; Eastes, 2001; Fischer, Lapinsky, & Weshler, 2002; Flanders et al., 2003; Luo, 2004; Marshall & Sumner, 2000; McCaffr ey, 2003; Peterson, 2003; Peterson, 2004; Stengel et al., 2004; Thomas, 2004-2; Volsko, 2004). The results of diagnostic investigations, such as laboratory results, data an alyses, study reports, and still pictures can also be downloaded onto portable devices for later re view (Gandsas & Luo, 2 004; McIntire et al., 2004). All of these areas have applic ations to the public health field. An HHC allows physicians to move from floor to floor in the hospital without needing to resynch, or share data, with a PC. Furtherm ore, a HHC can signal a physician when a new patient or new lab result has been entered, so they can access the information immediately. A non-physician public health employee could appr eciate the same portability when conducting surveillance, interviewing targeted subj ects, and communicating with colleagues. The HHC is a powerful tool enabling data acquisition, analysis, document development, and scheduling (Laskin & Davis, 2004; Merrell et al., 2004). In the classroom, a HHC may allow students to read and/or create e-books, find online information, put course information on studentsâ€™ handhelds, share information, facilitate research, and take quizzes (Laskin & Davis, 2004; Leibiger, 2002; Peterson, 2003; Ray, 2003). Additionally it is now recognized that textbooks and printed reference materials are outdate d before they can actually reach the shelves for purchase. Placing a Web-based book on the Inte rnet, selling it for downloading, and then
46 offering frequent updating through synching to a HHC would seemingly al leviate that problem (Leung et al., 2003; Peterson, 2003). It also permits the HHC user to have that resource at their fingertips for rapid and frequent use rather than sitting on a shel f at home or in the office. A public health employee and/or health educator could similarly use a HHC as a repository for surveillance and evaluation data , program planning guides, and informational databases. Disadvantages of using HHCs. At the pres ent time, several issues prevent health professionals from relying on HHCs to the same ex tent as they do their more traditional tools (Torre & Wright, 2003). First, how efficiently HHCs can be integrated in the patient encounter is not known, nor is the effect that they have on the professionalpatient relationship. Second, more evidence is needed to substant iate the benefits of HHCs comp ared with more conventional technologies or other electronic devices (Carroll & Christakis , 2004; McLeod et al., 2003; Torre & Wright, 2003). Third, although new wireless tec hnologies are on the horizon, the ability to connect to the Internet with the same speed and capabilities as a desktop computer appears to be several years away (Torre & Wright, 2003). Perhap s the most important disadvantage, however, is the concern for unsecured sensitive data. With the advent of the Health Insurance Portability and Account ability Act (HIPAA) (Thompson, 2005; USDHHS, 2006), HHCs are at high risk for breaching confidentiality if patient-specific data is stored on them. Eastes (2004) and others (Bernard, 2003; Chang et al., 2003; Chan et al., 2004; Flanders et al., 2003; Guad agno et al., 2004; Hirani et al., 2005; Laskin & Davis, 2004; Peterson, 2003; Peterson, 2004; Rose nthal, 2004) suggest that if identifiable patient data are stored on a HHC, the user must em ploy some type of secur ity software to protect the data. Administrative procedures and practices to prevent accide ntal or purposef ul disclosure, loss or misuse of information will be necessary, a nd that procedures for data storage, retrieval,
47 and backup have to be implement ed. Physical safeguards such as password protection to protect computer equipment and technical mechanisms (e.g., encryption) should be considered as additional standards to think a bout when using a HHC. Peterson ( 2003) even suggests that voice activation of the HHC may be another solution to the problem. A biometric software application ensures that only the voice of th e person that owns the HHC and is registered will be recognized so that the files may be accessed. Additionally, a policy should be developed for storing the HHC in a secure place when it is not in use. Howeve r, Al-Ubaydli (2004) suggests the easiest way to ensure that sensitive data does not get into the wrong hands is not to store any sensitive data at all. Other disadvantages for h ealth practitioners and public he alth employees may include the price of the device and its software (Eastes, 2004) and a concern for HHCs being a vector for disease transmission (Hassoun et al., 2004; Puskar et al., 2004). There may be other pathogen-based disadvantag es associated with HHCs as well. Hassoun, Vellozi and Smith (2004) evaluated HHC microb ial colonization before and after cleaning a HHC with alcohol. Before clean ing the 75 HHCs, 96% were cu lture-positive; after cleaning, 75% became culture-negative. Thus, HHCs cleaned with an alcohol swab demonstrated a significant reduction in colonization. While th ere is no direct evidence to show that microorganisms on HHCs will infect others, st rategies to reduce colonization should be considered. Still other disadvantag es to HHC usage must be cons idered. Many suggest that new information technology is as likely to decrease efficiency, as it is to increase it (Gibbs, 1997; Tierney, Overhage, & McDonald, 2004). Schuere nberg (2004) states that many medical providers routinely report a variety of hardware issues as the leading reasons for not using HHCs. Limited battery life, insufficient memo ry, vulnerability to hostile environmental
48 conditions, and small screen size being the most common concerns (Mille r et al., 2005; Peterson, 2004; Roschelle, 2003; Schuerenberg, 2004; Vernez et al., 2004). Briggs (2004) states that computer aptitude can play a part in a userâ€™s ge neral resistance to a change that incorporates computers. Some may fear losing their autonomy if they rely too heavily on technology (Briggs, 2004; McAlearney, Schweikhart, Medow, 2004). Additionally, Carrol et al (2004) and others (Fischer, Stewart, Mehta, Wax, & Lapinsky, 2003; Nikula, 2001; Berg, 2001) state that alt hough HHCs are becoming more popular in the health field, they have not been clearly show n to be beneficial. Even so, many are moving forward and transitioning to purchasing and using HHCs. Peripherals. Similar to memory expansions are othe r types of â€˜add onâ€™ features such as peripherals. Some marketers believe that ne w peripherals, including clip-on batteries and memory cards, will meet usersâ€™ needs and thus boost HHC acceptance. Some companies are looking at applications that contou r software to better fit the scr een size of a HHC; others have created mobile strategies that support HHC use though the addition of various hardware (Schuerenberg, 2004). For example, one obstacle that is recently be ing overcome is short battery life (i.e., three hours of power). Clip-on batteries may greatly increase the life of built-in batteri es. Additionally, by synching the HHC more frequently, the device will obtain a short charge. Al-Ubaydli (2004) suggests that users consider an expandable ke yboard. This device folds to the same pocket size as the handheld but unfolds to match a fullsized keyboard. HHCs may also be used as a projection device for PowerPoint pres entations. Yam (2004) describes a HHC peripheral/software package that, when used with an liquid crystal displa y (LCD) projector, can project a high-resolution presentati on that is controlled by the HHC . However, the software that
49 the author used on their HHC did not allow a ny form of PowerPoint animation. Also, after downloading the presentation onto the HHC, the file could not be m odified or edited. It is very likely that impediments such as these may introdu ce displeasure, disappointment, and/or anxiety within the workplace. Anxiety in the Workplace Stress as it Relates to Anxiety Often in the literature, stress and anxiety ar e used interchangeable; despite more than a century of research on stress, investigators still fi nd it a challenge to have a clear and satisfactory definition of the concept (Segerstrom & Miller, 2 004). In actuality, while stress is the way our bodies react to changes, anxiety is the actual feeling of dread, f ear, or distress over a real or imagined threat (NIMH, 2000). With the adve nt of new technology being introduced to the workforce, anxiety and stress also may appear . Stress in the workplace is not uncommon. A multitude of studies have shown that stressf ul work conditions are associated with poor individual well-being and increased health risks (Ganster & Sc haubroeck, 1991; Kahn & Byosiere, 1992; Sonnentag & Frese, 2003; Sparks , Cooper, Fried & Shirom, 1997; Van der Doef & Maes, 1999). While many employers may percei ve stress as an excellent motivator, the negative implications co uld far outweigh the positive ones in a relatively short period of time. While it is true that stress in the workpl ace can have both positive and negative effects on individuals and their organizati ons (Faulkner & Patiar, 1997), wo rkplace stressors should not be confused with â€œpositive stressorsâ€â€”those even ts experienced by the employee that can be motivating and challenging (Gates, 2001). Workplace stressors, such as anxiety, can ha ve a very visible effect on an employeeâ€™s health. In fact, a workersâ€™ produc tivity directly relate s to the total health of the employee, including their physical, mental, and social well-being (Humphrey, 1998). In fact, the Centers for
50 Disease Control and Preventionâ€™s National Institute for Occupational Safety and Health (CDC/NIOSH) has made a determined effort to address stress within the worksite. CDC/NIOSH is the federal agency for conduc ting research and making recomme ndations for the prevention of work-related injury and illness. Some of CD C/NIOSHâ€™s primary themes in their job stress research program are: 1) to better understand the influence of what are commonly termed â€œwork organizationâ€ or psychosocialâ€ factors on stress, i llness, and injury and 2) to identify ways to redesign jobs in an effort to create safer and healthier workplaces. Within these themes, psychological and physiological in terplays (e.g., stress, anxiety, and new mechanically-related interventions such as computers) and their imp act on employees are being investigated. This is especially relevant given tec hnological changes, like HHCs, that enable job tasks to be performed in a variety of locations and there by blurring the boundaries between job and home life (Bakker & Schaufeli, 2005). Selye (1976) states that stress is a physical reaction by individuals to demands (including anxiety) imposed upon them by their environment. This reaction may play a positive role by triggering the mobilization of adap tive responses. While stress can be either positive or negative (Levi, 1972), many individuals find stress to be so lely debilitating. Usually when people discuss stress, they refer to a physical or psychological demand---such as something associated with anxiety---that is outside thei r normal boundaries and one which signals the disparity between what is optimal conditions for them and what cond itions actually exist (Herbert, 1997). It is this disparity that seems to affect the general happiness and well-being of many employees. In a survey by the Families and Work Institute, 26 percent of workers reported that they were â€œoftenâ€ or â€œvery oftenâ€ stressed or burne d out by their work (Sauter, 1999). While the term â€œstressâ€ can seem to be a vague indicator for unhappiness, many employees find that the genesis
51 of the actual stress comes from more â€œsolid a nd visibleâ€ areas. For example, the most commonly measured stressors in the workplace are anxiet y, role overload, role ambiguity, and decision latitude (Gates, 2001). There is also mounting evidence th at suggests that workplace interpersonal conflicts and negative interpersona l relationships are a prevalent source of stress (Dewe, 1993; Israel, House, Schurman, Heane y, & Mero, 1989; Long, 1989; Ratsoy, Sarros, & Aidoo-Taylor, 1986). While stress is clearly evident within the wor kplace, not all employees seem to suffer. In fact, some contemporary commentary rejects much of the â€˜stress causes il lnessâ€™ assumption in favor of reframing stress as i ndividually defined and largely the result of a preoccupation with emotional upset (Roger, 1998). A workerâ€™s personali ty, coping style, and pe rsonal stressors have a significant impact on how the worker will apprai se and cope with a stressor in the workplace (Gates, 2001). Relationship of stress to overall health. Stress within the wor kplace can have a very visible effect on employees. Research has suggested stressâ€™s role in cardiovascular disease (Kop, 1997), peptic ulcer (Levenstein, 1998), mental il lness, infectious disease (Biondi and Zannino, 1997), asthma self-management behavior (Wrigh t et al., 1998), and in fertility (Brkovich & Fisher, 1998). In fact, research suggests that be tween 50% and 75% of all illnesses are related to stress. Studies have also linked anxiety and anger at work with depression, heart disease, and hypertension (Begley, 1994), as well as playing a role in headaches, back pain, and asthma (Pennebaker, 1997). Interestingly, although ther e is direct evidence that stress-related immunosupression can increase vulne rability to disease in anim als, there is little evidence linking stress-related immune change in healthy humans to disease vulnerability (Segerstrom & Miller, 2004). It is thought that the immune system is a remarkab ly flexible construct that is
52 capable of adapting to imposed demands. However, the flexibility of the immune system can be compromised by age, disease, illness, chronic stre ss, and genetic predispos itions. It is also likely that an individualâ€™s outlook on their health and life may impa ct their physical health. For example, studies have convincingly demons trated that peopleâ€™s cardiovascular and neuroendocrine responses to stre ssful experiences are dependen t on their appraisals of the situation and the presen ce of intrusive thoughts about it (B aum, Cohen, & Hall, 1993); Tomaka, Blascovich, Kibler, & Ernst, 1997) . Furthermore, psychological va riables such as personality and emotion can give rise to individual differences in psychological and concomitant immunological responses to stress. Optim ism and coping, for example, moderated immunological responses to stressors in severa l studies (Barger, Ma rsland, Bachen, & Manuck, 2000, Bosch, de Gues, Kelder, Veerman, Hoogstr aten, & Amerongen, 2001; Cruess, Antoni, Kilbourn, Ironson, Klimas, Fletcher , et al., 2000; Segerstrom, 2001; Stowell, Kiecolt-Glaser & Glaser, 2001). Recent research also suggests that acute st ressors lasting minutes (e.g., public speaking, vehicular accidents, and/or inacces sibility of toiletry facilities) were associated with potentially adaptive strengthening of the immune system (S egerstrom & Miller, 2004). On the other hand, chronic stressors (e.g., job dissatisfaction, martia l difficulties, and/or bereavement) suppress natural immune functions. Interest ingly, the same research also found that subjective reports of stress (whether acute or chr onic) did not associate with im mune change. This notion lends credence to the idea of job-related voluntary screenings as a compliment to existing employee assistance programs. Stress-related problems may be associated with particular professions as well. Descriptive studies of stressful workplace situations among nurs es have shown that workload, conflict, role
53 preparation and death and dying ar e key situational contexts that lead to stressful symptoms (Farrington, 1995). Among practitioners in a gene ral practice in the Un ited Kingdom, nearly a quarter of respondents from one st udy could be classified as su ffering from mental distress (while lower than practitioners in a normal hospital, this was still higher than the normal population) (Calnan, Wainwright, Forsythe, Wall, & Almond, 2001). Costs associated with stress . Many employers do not reali ze the effect stress and its resulting illnesses have on their bottom line (A ldana, 1998; Aldana, Merrill, Price, Hardy, & Hager, 2005; Lundberg & Tulczak, 1997; Tompki ns, 2000). In actuality, job stress and job dissatisfaction and their resulting anxiety disorders cost employers billions of dollars each year in health care expenses. Problems can include excessive absenteeism, reduced productivity, poor performance, and passive aggressive actions (Chen & Spector, 1992; Humphrey, 1998). Besides the physical effects and costs, other indirect co sts may hamper productiv ity and job performance as well. Faulkner & Patiar (1997) state that ex cessive levels of unresolved stress can be detrimental to the morale, performance, and health of individualâ€”this in turn can affect both the productivity of staff and the quality of service that they deliver. Elements of psychological health and the eff ect of stress upon it are understudied areas. In fact, depressed workers on average incur more than $4,373 additional health costs per year (Tompkins, 2000). Most research that has been d one has focused on blue-collar workers (Hurrell, 1985), managers (Burke, 1988) and little elsewhere. Much research has been done on traditional assembly line work, which may be characterized by high repetition, monotony, little variation, low personal control, low job satisfaction, high absenteeism, and elevated psychological stress levels (Frankenhaeuser & Gardell, 1976; Fra nkenhaeuser, 1986; Lundberg, Granqvist, Hansson, Magnusson, & Wallin, 1989). Compounding this is the notion that computer-related stress, or
54 â€˜techno-stress,â€™ has introduced to employeesâ€”employees are now expected to produce â€œinstant actionâ€ for their employers (Helge, 2001). Anxiety Anxiety is defined as a sense of apprehension and fear often marked by physical symptoms (such as sweating, tension, and increased heart ra te (Wikipedia, 2006). Anxiety, as such, is very similar to â€˜stress.â€™ As mentioned previously, st ress is the way our bodies react to changes; anxiety is the actual fee ling of dread, fear, or distress over a real or imagined threat (NIMH, 2000). While a certain amount of anxiety is nor mal, it can cause marked problems when it overwhelms and interferes with a personâ€™s normal day-to-day life. Anxiety can be a symptom of a number of illn esses known as anxiety disorders. These can include phobias, panic disorder, obs essive-compulsive disorder, or post-traumatic stress disorder. Anxiety disorders are a group of serious and tr eatable health problems caused by a combination of biological and environmental factors; this illn ess affects over 40 million adults in America, or about 18.1% of people nationwide in this age group in a given year (Kessler, Chiu, Demler & Walters, 2005). Unlike brief episodes of anxiety th at are caused by stressful events such as using a HHC, anxiety disorders are chr onic conditions that can worsen with time. For the purposes of this study, the author will focus on general anxiety rather than anxiety diso rders associated with HHC use. Anxiety has been shown to be increasing sh arply in the workplace (HSC, 2004). At the individual employee level, genera l anxiety has been found to lead to impaired work performance, accidents, and absenteeism (Allegrate & Mich ela, 1990; Blair, Collingwood, Reynolds, Smith, Hagan, & Sterling, 1986; HSC, 2004). At the organizat ional level there are lik ely to be effects on productivity, staff morale, accidents, absences, and staff turnover (Haslam, Atkinson, Brown & Haslam, 2005; Karasek & Theorell, 1990; Tu rner, Wheaton & Lloyd, 1995; Siegrist, 1996;
55 Maslach, Schaufeli & Leiter, 2001) . When studying the effects of anxiety and depression in the workplace, Haslam et al (2005) found, via five focus groups, that workers reported their anxiety was associated with impaired work performa nce. Subjects also reported that unmanageable workloads contributed to their anxiety. Computer-related anxiety . New technological changes such as HHCs are one major reason for the emergence of new forms of working (e.g., telecommuting, accessing office materials while traveling, and accessing office data when in remote geographical locations). Consequently, these new forms of working can l ead to new mental health job-related demands (Hesketh & Neal, 1999). The use of computers has raised a number of concerns relating to health and well-being (Arnetz, 1996; Berg et al., 1990; Berg et al ., 1992; Carmichael & Roberts, 1992; Ericson & Kallen, 1986; Helge, 2001; Marr iot & Stuchly, 1986; Miller & Duncan, 1988; Hunting et al., 1981; Nielsen, 1982; Pascarelli & Kella, 1993; Schno rr et al., 1991). One specific focus related to anxiety is the idea of â€œtechno-stress.â€ Tec hno-stress, sometimes referred to as techno-anxiety, is defined as the ability of computer work to induce a psychophysiologi cal arousal pattern in sensitive workers (Arnetz, 1996; Arnetz, 1997; Berg et al., 1992). At the pr esent time, there is a vacancy in the literature regard ing investigations of any possible impact of the use of HHCs on an individualâ€™s overall health, we ll-being, or anxiety. However, Sm ith et al. (1999) states that much of the stressors of human co mputer interaction at work are similar to those stressors that have historically been observed in other types of automated jobs and new stressors have emerged that can be tied primarily to human computer in teraction. As a result, it seems logical that one might be able to generalize what has been found relating to general comput er usage to the usage
56 of HHCs. For example, theoretic ally a HHC may cause increased physiologi cal arousal, somatic complaints, and/or anxiety (Smith et al., 1999). While the terms computer user â€˜stressâ€™ and â€˜a nxietyâ€™ are used interchangeably within the literature, computer/tech no- â€˜anxietyâ€™ is most commonly us ed (Hudiburg, 1992; Martinkour et al., 1996; Rosen & Maguire, 1990). Raub (1981) de fines computer anxiety as the â€œcomplex emotional reactions that are provided in indi viduals who interpret computers as personally threatening (p.9).â€ Others have defined it as â€œfear of impending in teraction with a computer that is disproportionate to the act ual threat presented by the computerâ€ (Howard, Murphy, and Thomas, 1987, p.14) and as â€œan affective response of apprehension of fear of computer technology accompanied by feelings of nervousness, intimidation, and hostilityâ€ (McInerney & McInerney, 1994, p.28). Some have thought that computer anxiet y is a learned experience stemming from an infrequent use of computers an d that increased use (a ssociated with building skills and having successful experiences) would gra dually diminish anxiety. As a result, anxiety levels associated with computers can be changed with computer training. Computer anxiety has also been shown as an important predictor for the use of technology in older adults (Czaja et al, 2006; Ellis & Allaire, 1999). Given th e important role that computer anxiety plays in computer interest and use, Czaj a et al (2006) postulated that age difference in technology adoption would be partially mediated by computer anxiety and computer selfefficacy. They also hypothesized that computer self-efficacy would have an indirect effect on technology adoption through anxiety such that peopl e with lower self-efficacy would have higher anxiety. Their findings describe that computer self-efficacy was an important predictor of general use of technology and that people w ith lower self-efficacy are less likely to use technology in general. This finding is consistent with the argument that people with lower self-
57 efficacy display less motivation to engage in a task than those w ith higher self-efficacy (Bandura, 1997; Ellis & Allaire, 1999). Computer experience has also been reported to be a consis tent correlate of computer anxiety (Cohen & Waugh, 1989; Chu & Spires, 1991; Heinssen et al., 1987; Igbaria & Chakrabarti, 1990; Kay, 1990; Liu, Reed, & Ph illips, 1992; Marcoulides, 1988; Reed & Palumbo, 1988; Rosen et al., 1987). Lloyd & Gre ssard (1984) and others (Heinssen, Glass & Knight, 1987; Howard & Smith, 1986) suggest that a major factor in computer anxiety is a lack of familiarity with computers and that increased experience should decrease anxiety. However, there have been some unexpected results described in the literat ure as well. For example, when studying the prevalence of computer anxiety of social workers, Choi, Ligon, and Ward (2002) discovered that a negative correlation was found between anxiety levels and weekly hours of computer use. Interestingly, it was found that despite increasing use of computers in the workplace, evidence has emerged that the normal daily use of computers in general can be limited due to computer anxiety, negative attitudes, and lack of training; th is is consistent with what other researchers have found as well (B ozionelos, 1996; Igbari a et al., 1989; Jacobson, Holder, & Dearner, 1989). However, one study found that for the initially high-anxious learners, some aspects of computing anxiety might actuall y facilitate learning (M cInerney, McInerney, & Marsh, 1997). Regardless, most of the literature agrees th at there is in fact a relationship between computer use and reported anxiety. Furthermor e, many studies have investigated computer anxiety (mostly among clinical healthcare employ ees) and have developed scales that are both reliable and valid (Brown & Coney, 1994; Cohe n & Waugh, 1989; Jacobson, Holder, & Dearner, 1989; Jayasuriya & Caputi, 1996; Jacobson, Hold er, & Dearner, 1989; Lester, Yang, & James,
58 2005; Oetting, 1983; Wilson, 1989). However, nowhere in the literature has a scale been developed to assess either asso ciated anxiety or self-efficacy in its relation to HHC use, especially among public health employees. Beckers & Schmidt (2001) identified six factor s associated with computer anxiety: 1) computer literacy, 2) self-efficacy, 3) physical arousal associated with comput er use, 4) affective feelings about computers, 5) beliefs about the be neficial effects of comp uters, and 6) beliefs about their dehumanizing aspects. Other authors ha ve also conclusively shown the definitive link between general anxiety and self-efficacy as well as computer anxiety and self-efficacy (Bancila, Mittelmark, & Hetland, 2006; Bandura, 1977; Brosna n, 1998; Czaja, Charness, Fisk, Hertzog, Nair, Rogers & Sharit, 2006; Giles, Turk, Fres co, 2006; Karademas, 2006; Peiser & Shamshins, 2006; Weems & Silverman, 2006). For the purposes of this study, the author will focus on selfefficacy and the affective feelings (i.e., anxiety) associated with HHC us e (i.e., techno-anxiety). Social Cognitive Theory and Self-Efficacy Background of Social Cognitive Theory Self-efficacy is an inherent construct with in Social Cognitive Theory (SCT). SCT describes an ongoing dynamic process within a r eciprocal determinism model in which the behavior, personal factors, and the environment interact (Theory at a Glance, 2005). SCT is an outgrowth from Social Learning Th eory (SLT), which asserts that people learn not only from their own experiences, but also by observing the actions of others and the benefits of those actions; SCT adds the element of self-efficacy. Ba ndura (1977) proposes that self-efficacy is the most important prerequisite for behavior change . Self-efficacy determines how much effort is invested in a given task and at what le vel an individual is able to perform. Like SLT, SCT addresses both the psychosocial dynamics influencing health behavior and methods for promoting behavioral change. As a re sult, educators and rese archers have used SCT
59 to develop interventions, procedur es, and techniques that influence personal factors and result in increasing the likelihood of a behavioral change . SCT incorporates two specific expectations: outcome expectations (individuals tend to undert ake behaviors they be lieve will help them perform their tasks better) and expectations rela ted to a concept called self-efficacy (Kulviwat et al., unknown publication date). Self-efficacy . Self-efficacy refers to the judgments an individual makes about his or her capabilities to mobilize, cognitive resources, and courses of action needed to orchestrate future performance on a specific task (Bandura, 1986; Gi st & Mitchell, 1992). Self -efficacy theory (as a product of SCT) proposes that i ndividuals who judge themselves as capable to perform certain tasks or activities will tend to attempt and succ essfully execute them (Murphy 1989). In general, individuals will attempt and successfully complete t hose activities that fall within their efficacy, and they will avoid or fail at t hose they perceive they cannot d o. Individuals make this efficacy judgment by factoring in informa tion related to past experience, cognition, and the environment. Once this decision has been made, it is thought to di rectly impact the choice to engage in a task, as well as the effort that will be expended a nd the persistence that the task will be given (Bandura, 1977; Kinzie & Delcourt, 1991). Historically, key decision ma kers in organizations have overlooked the impact of employee self-efficacy in performance as a component in achieving organizational success in the workplace (Gist & Mitchell, 1992 ). The added demands of computer technology (depending on their associated level of self-efficacy) on an em ployee may serve to erode his/her confidence in successfully using the electronic device (Gist & Mitchell, 1992; Kinzie & Delcourt, 1991). As a result, many in the workforce are creating edu cational and training prog rams that transfer computer technology skills from the classroom to the work environment; many find that building
60 employeesâ€™ computer self-efficacy is just as im portant as providing employees with computerrelated knowledge (Gist, 1987; Gist & Mitche ll, 1992; Kinzie & Delc ourt, 1991). Gist (1987) states that delivering knowledge without regard to the levels of traineesâ€™ self-efficacy may actually hamper traineesâ€™ learni ng. Consequently, there may be a need for more studies that examine the role of self-efficacy in employee tr aining. Some studies suggest that self-efficacy assessment plays a critical role in influencing wo rk effectiveness, perceived productivity, and job satisfaction (Staples, Hulland, & Higgins, 1998). Indeed, a meta-analysis of 114 studies by Stajkovic & Luthans (1998) stated that enhanced self-efficacy predicts successful performance. Others have found similar resu lts (Anna, Chandler, Jansen, an d Mero, 2000; Bandura & Adams, 1977; Bandura, Adams, & Beyer, 1977; Baum & Lo cke, 2004). It is plausible to believe that enhanced HHC self-efficacy would lead to successful use of HHC as well. Computer Self-Efficacy The concept of computer self-efficacy also is based upon SCT (Bandura, 1982; Compeau & Higgins, 1991). Consequently, it is logical to suppose that by incr easing a userâ€™s self-efficacy, there would be a corresponding increase in th e likelihood that those users would operate a computer successfully (see Figure 2-1). In fact, early studies have shown a positive experience with computers in general was found to be a predictor of self-efficacy (Compeau & Higgins, 1995; Dillon, Lending, Crews II, & Blankenshi p, 2003; Hills, Smith, & Mann, 1987; Delcourt & Kinzie, 1991; Gist & Mitc hell, 1992; Tella & Ayeni, 2006; Venkatesh, 2000). However, in some instances, while general self-efficacy was enhanced, computer-specific self-efficacy was not. For example, Tam (2000) evaluated the effects of both self-efficacy enhancement and social comparison training stra tegies on computer skills learning and selfconcept of 59 trainees with physical disabili ties. The self-efficacy enhancement group showed significantly better comput er skill learning outcomes, total se lf-concept, and social self-concept
61 than the comparison group. The author found that the self-efficacy enhancement group did not show significant changes in their self-efficacy; however, the tutorial training group showed a significant lowering of their computer self-efficacy scores . In essence, the authorâ€™s training strategy that incorporated self-efficacy enhancement was able to maintain the computer selfefficacy of trainees with physical disabilities , while those who did not have the self-efficacy enhancement showed a lowering of their baseline computer self-efficacy. Similar findings were found in other studies as well (Tam, 1996; Fray ne & Latham, 1997; Gist, Schwoerer, & Rosen, 1989; Caplan, Vinokur, Price, & Va n Ryn, 1989). Tam (2000) suggested that the trainees in the self-efficacy enhancement group showed generally higher computer self-efficacy, and since selfefficacy correlates with motivation (Bandura 1992), the author hypothesized that those group members exerted more effort during the training. Many variables have been shown to influe nce an individualâ€™s self-efficacy with information technology in general, including gender , age, education level, computer ownership, computer experience, professional orientati on, training, organizational support, management support, encouragement, and computer attitude s (Ellis & Allaire, 1999; Henderson et al., 1995; Marakas, Yi, & Johnson, 1998; Ogletree & Williams, 1990). It is thought that many of these variables are also associated with computer s (Cassidy & Eachus, 2002). Self-efficacy beliefs have repeatedly been reported as a major factor in understanding the frequency and success with which individuals use computers. Compeau & Hi ggins (1995) found that individuals with high self-efficacy used computers more, enjoyed them more, and experienced less computer anxiety. Others found that computer self-efficacy belief s affected whether individuals chose to use computers irrespective of their beliefs about th e value of doing so (Hill, Smith, and Mann, 1987).
62 Computer knowledge and experience have also b een associated with determining levels of self-efficacy. While many have found that comput er self-efficacy increased significantly with computer training courses (Cassidy & Eachus, 2 002; Ellis & Allaire, 1999; Hill, Smith, and Mann, 1987; Torkzadeh & Koufteros, 1994), some have found that the actual amount of experience was not correlated w ith self-efficacy beliefs. Regardless, the preponderance of the research relating to computer self-efficacy suppor ts the posit that self-efficacy plays a crucial role in determining technology acceptance and therefore use of the technology (Agarwal, Sambamurthy, & Stair, 2000; Compeau, Higgi ns, & Huff, 1999; Dabholkar & Bagozzi, 2002; Ellen et al., 1991; Lee, Kim, & Chung, 2003; Ve nkatesh, 2000; Venkatesh & Davis, 1996). However, within the literature there are spec ific concerns relating to the value of those measurement tools that are being used to assess computer self-efficacy. For example, there are concerns about validity (Miura, 1987), those meas ures that only incorporate self-efficacy as one component (Lloyd & Gressard, 1984), problems w ith reliability (Hill, Smith, & Mann, 1987), validity (Vasil, Hesketh, & Podd, 1987), and bias (Murphy, Coover, & Owen, 1989). As a result, while there are some studies that show pr omise (e.g., Cassidy & Eachus, 2002) there is a definitive need in the literature for a reliable a nd valid instrument that adequately assesses not just computer self-efficacy, but HHC self-efficacy among public health employees. Even more importantly, instruments developed for other pr ofessions such as nursi ng and other clinical providers may not address the uni que training, roles, activities, and respons ibilities of public health employees (Cork, Detmer, & Friedman, 1998), thus a need for an instrument designed specifically for the public health profession is warranted. Summary The prospect of improved work performance and overall health among public health employees is certainly exciting. This is especial ly so given the large national focus on the many
63 benefits (e.g., morale, attendance, and other re turns on investment) associated with promoting the wellness of workforces. In the clinical and educational sectors and presumably public health, HHCs are becoming a versatile resource. Very littl e research has been done to determine not only the usage, but also the impact of HHCs on overall health (especia lly anxiety and selfefficacy). This study will provide important cont ributions that will translate into valuable applications in the field, especially in the areas of worksite wellness, performance, and professional portability.
64 Figure 2-1. Existence of an indi vidualâ€™s physiological and emotiona l state (i.e., feeling anxiety) and how it relates to those judgments that are made in determining self-efficacy and resultant behavior. Physiological and Emotional States ( i.e. , anxiet y) Self-Efficacy Judgments Behavior/ Performance
65 CHAPTER 3 METHODOLOGY This study assessed public health employees â€™ use of HHCs and the corresponding selfefficacy and anxiety related to their usage. This chapter describes the methods used to conduct the research project in three phases. Specifical ly, these phases are scale development, pilot testing, and final testing. Research Design This survey research involved the constructi on and validation of an online instrument that assesses the extent of public health employeesâ€™ use of HHC s and self-efficacy and anxiety related to HHC use. The sample was selected from three national non-government organizations (NGOs) that are predominantly comprised of subject s from the desired population: public health employees. In order to obtain instrument reliabil ity and validity, a pilot test and final test was performed. In addition, statistical tests were used to examine the relationship between HHC use and HHC self-efficacy and HHC anxiety. Instrument Development The instrument was designed based on the Computer User Self-Efficacy Scale (alpha=.97) developed and validated by Cassi dy and Eachus (2002) and the Short Computer Anxiety Scale (alpha=.78) developed by Le ster, Yang, and James (2005). In this study, the instrument has three parts. In Part One the respondents were aske d to provide basic bac kground information about themselves and their experiences with both handheld and desktop/ laptop computers. In Part Two, respondents were asked to provide more detailed information about the extent to which they agree or disagree with statements related to HHC self-efficacy. In Part Three, respondents were asked to provide more detailed information about th e extent to which they agree or disagree with statements related to HHC anxiety.
66 In order to best assess HHC-associated us age, HHC anxiety, and HHC self-efficacy, an instrument was developed that ta rgets not only those constructs, but specifically public health employees as well. Although it may be possibl e to use instruments developed for other professions (e.g., clinicians), this approach may not prove valuable to those in public health. For example, it is not known if public health employees have shared knowledge, beliefs, or attitudes with other health-oriente d (e.g., clinical) professions. Also, th e instruments that were developed for one group of professionals may not be generali zable to others. Curren tly, there is nothing in the professional literature that assesses the extent of public health employeesâ€™ HHC usage. Additionally, the litera ture shows no evidence of resear ch being done to determine the employeesâ€™ level of self-efficacy or anxiety related to HHC technology. Therefore, this study was designed to assess public health employ eesâ€™ use of HHCs and its corresponding self-efficacy and anxiety related to HHC usage. This study was performed with member s from three national non-governmental organizations whose membership is comprised of public health employees throughout the nation. The study was conducted during the 2006 and 2007 calendar year. Before developing the instrument , the researcher reviewed th e original Cassidy and Eachus (2002) and Lester, Yang, and James (2005) instrume nts. A panel of experts was asked to review the instruments. Based on review feedback, a revised instrument was developed to assess the level of HHC self-efficacy and HHC anxiety among public health employees. The revised instrument consisted of items in three sections: Section 1: Demographics and HHC Use . This section included 18 items relating to name, age, gender, level of education, experi ence with HHCs, and use of HHCs. Section 2: HHC Self-Efficacy . This part of the questionnaire included 30 items assessing the level of HHC self-efficacy among public health employees. Each item asked the
67 respondent to respond to a statement relating to HHC use. Using a six-point Likert scale, the respondent indicated the extent to which he/s he agrees or disagrees with the statement. Section 3: HHC Anxiety . This section contained a 6-item brief measure of HHC anxiety. Using a six-point Likert scale, the respondent indicated the ex tent to which he/she agrees or disagrees with the given statement. Pilot Test The purpose of the pilot test was to assess the format of the questionn aire, clarity of the instructions, item appropriateness, ease of administration, comple tion speed, and reliability and validity of the scales. Procedures The instrument along with its protocol was submitted to the Univ ersity of Florida Institutional Review Board (IRB) for approval before the pilot test. A total of 54 items including 18 demographic, 6 HHC anxiety questions, and 30 HHC self-efficacy questions were in the pilot survey. The pilot test consis ted of a convenience sample de rived from 13 public health employees in a federal public health agency. These colleagues were used for the pilot test because of both the convenience aspect and the re ality that all were currently working in public health. Participants in the pilot study had eith er knowledge or experien ce with HHCs, computers in general, and public health. After the pilot test, item analysis was perfor med in order to determine if the questionnaire needed to be revised. Three areas were assess ed: item difficulty, item discrimination, and item consistency. All three scales (demographics and HHC use, anxiety, and self-efficacy) were examined. The values of Cronbachâ€™s alpha for the HHC self-efficacy and HHC anxiety sections were 0.965 and 0.723, respectively. Before the administration of the final questi onnaire, existing questions in the preliminary questionnaire were slightly modi fied based on feedback from the pilot test. Furthermore, six
68 questions were modified and one additional question relating to demographic and HHC use was added to the survey. Survey changes included: Revising â€œHow many years of education af ter high school have you completed (openended)?â€ to â€œWhat is the hi ghest level of education that you have completed? (closeended)? Changing group affiliation to includ e â€œAre you a member of SOPHE?â€ Changing the term â€œnon-profitâ€ to â€œn ational non-governmental organization.â€ Changing â€œCan your HHC be used as a phone?â€ to â€œCan the HHC that you use most often for your job also be used as a phone?â€ Changing â€œDo you ever use a HHC?â€ to â€œDo you ever use a HHC for your job?â€ Changing â€œWhat brand of HHC( s) do you use?â€ to â€œWhat brand of HHC do you use most often for your job?â€ Changing â€œDo you own your HHC?â€ to â€œDo you own the HHC that you use most often for your job?â€ Changing â€œHow many years have you owned your HHC?â€ to â€œHow many years have you owned the HHC that you use most often for your job?â€ Adding â€œOn average, how many hours per do we ek do you use (for non-work activities) a desktop computer? A HHC? A laptop computer ?â€ and adding (to the same question) â€œOn average, how many hours per do week do you us e (for work-related activities) a desktop computer? A HHC? A laptop computer?â€ The Final Instrument The modified instrument included 55 ques tions, 19 demographic and HHC use items, 30 items to assess the level of HHC self-efficacy among public health employees, and six items to assess HHC anxiety. The layout was the same as that of the pilot test questionnaire. To assess â€˜ Experience with Handheld Computers, â€™ each question was scored using a standard Likert format where â€œnoneâ€ is scor ed as 1 and â€œextensiveâ€ is scored as 5. â€˜ Number of Handheld Computer Packages Usedâ€™ was scored a 1 for each package used and these were summed to give a total score.
69 To score the self-efficacy scale, items 1 to 30 were all scored on a 5point Likert scale. Items 1, 2, 3, 6, 8, 9, 12, 16, 18, 20, 24, 27, and 29 were positively worded and the respondentâ€™s answer was recorded as the actual scale score for these items, e.g., a respon se of 4 to item 1 will be scored as 4. Strongly Disagree 1 2 3 4 5 Strongly Agree Items 4, 5, 7, 10, 11, 13, 14, 15, 17, 19, 21, 22, 23, 25, 26, 28, and 30 were negatively worded and were scored in reverse coding. Summing the scores of all 30 items gave the total self-efficacy score. Using this scoring method, a high total scale score indicated more positive self-efficacy beliefs towards HHC use. For the anxiety scale, 6 items were sc ored on a 6-point Likert scale. Items 32, 33, 34, and 35 were positively worded and the respondentâ€™s answer was recorded as the actual scale score for these items, e.g., a response of 4 to item 1 will be scored as 4. Strongly Disagree 1 2 3 4 5 6 Strongly Agree Items 31 and 36 were negatively worded and were scored in reverse coding. Summing the scores of all 6 items gave the total anxiety score. Using this scoring method, a higher total scale score indicated less anxiety towards HHC use. Survey Administration The modified questionnaire was formatte d into web-based survey. A total of 382 participants are required for a good representation of the popul ation. This sample size was calculated as a result of Krejcie & Morganâ€™s (197 0) sample size determination formula. Namely, s = 2NP(1-P) / d2(N-1) + 2P(1-P), where: s = required sample size 2 = the table value of chi-square for 1 degree of freedom at the desired confidence level (3.841)
70 N = the population size P = the population proportion (assumed to be .50 since this would provide the maximum sample size) d = the degree of accuracy expressed as a proportion (.05) In order to attempt to achiev e a response rate of at least 40%, the researcher chose to survey at least 960 public health employees. Obvi ously, a higher response rate would further improve the generalizability of the study findings to other members in the NGOs on the HHC use and its associated self-efficacy and anxiety. Participants According to a CDC publica tion (2001), there are approxi mately 500,000 public health employees in the United States. A sample from this population was drawn from the membership of three national non-governmental organizatio ns (NGOs): the Society for Public Health Education (SOPHE), the Director s of Health Promotion and Edu cation (DHPE), and the National Association of Chronic Di sease Directors (NACDD). SOPHEâ€™s membership comprises more than 4,000 professionals with formal training and/or an interest in public he alth education and health promo tion throughout the United States and 25 foreign countries. Members work in school s, universities, medical/m anaged care settings, corporations, voluntary health agencies, internat ional organizations, volu ntary health agencies, and federal, state, and local public health government agencies . There are currently 24 SOPHE chapters covering 33 states. DHPEâ€™s membership represents 55 directors of health educati on/health promotion units of state health departments and the health department s of the District of Columbia, Puerto Rico, the Virgin Islands, Guam and American Samoa as we ll as the 11 directors of the health education
71 units of the Indian Health Service Area O ffices. DHPE also has more than 300 associate members and members emeritus. Programmatically, DHPE directors administer a wide range of health education/health promotion-related public health programs including chronic disease prevention, injury prevention, HIV/AIDS, risk factor related progr ams such as tobacco use prevention, nutrition and physical activity, school, worksite and community health promotion. NACDDâ€™s membership consists of 58 voting members and more than 500 regular and associates members. NACDD works to reduce the impact of chronic diseases on the American population by advocating for preventative pol icies and programs, encouraging knowledge sharing and developing partners hips for health promotion. NACDDâ€™s six councils -Arthriti s, Breast and Cervical Can cer, Cardiovascular Health, Diabetes, Osteoporosis and Womenâ€™s Health -a ddress the unique needs of specific chronic diseases to advance prevention and control efforts in those areas. Additionally, other NACDD projects and interest groups such as compre hensive cancer control, healthy agi ng, physical activity, and school health, fac ilitate communication and profe ssional development for chronic disease staff with common program interests. The population was selected and sampled to a ssess the characteristics of public health employees, their use of HHCs and its associated self-efficacy and anxiety. In this study participants were invited by an email with the URL of the online questionna ire and the letter of informed consent from November 27th 2006. A sample of at least 960 members total was selected for the survey. Data Collection Procedure While membership lists from several NGOs was originally at tempted to be obtained, the staff of the NGOs thought that it would be more appropriate for the organization to send the
72 original invitation and reminder email messages to their respective members. The NGOs sent the e-mails via listserv to their entire membership bodies. This study used as a web-based form (WBF ) study. WBFs are an ideal data collection method; they are relatively inexpens ive, easy to use, and applicable to a wide variety of studies (Bakker et al, 2002; Buchanan & Smith, 1999; Smith & Leigh, 1997). They allow users who have received minimal training and who do not have a significant prio r level of technical proficiency or education to use th e method to enter data efficiently and in a consistent way that minimizes input errors and loss of data. Finall y, they allow the use of relatively inexpensive equipment or equipment that is already in use in a department (Shapiro et al., 2004). WBFs may be easier and faster to use than traditional paper forms. On the other hand, they may be unsuitable for people who are uncomfortable usi ng a computer and, of course, WBFs exclude respondents who do not have access to a computer. Furthermore, WBFs have been shown to be as reliable as paper forms and to have fewer data entry erro rs (Pettit, 2002). This data collection method lends itself ex tremely well to remotely collect surveys targeting individuals who have acce ss to a computer, because of the ease with which the survey can be distributed and with which responses a nd response rates can be tracked. Furthermore, a number of studies have compared data between traditional and we b-based versions of the same study. Research strongly suggests th at web-based studies reach th e same conclusions as those that are done traditionally, once the demographics of the participants are taken into consideration (Birnbaum 2000; Birnbaum, 1999; Buchanan, 2000; Buchanan & Smith, 1999; Krantz, Ballard, & Scher, 1997; Krantz & Dalal, 2000; Pasveer & Ellard, 1998; Pettit, 1999; Stanton, 1998). Data were collected from participants dur ing fall 2006 using Dillmanâ€™s Tailored Survey Design Method, which has been found to have an av erage return rate of 73% (2000). A link to an
73 online questionnaire was emailed to each of the members within the NGOsâ€™ membership lists. The online questionnaire (Appendi x A) included a letter of in formed consent (Appendix B) explaining the purpose of the study, inst ructions, and the questionnaire. Participants were instructed to complete th e letter of informed consent. If consent was given, participants would be direct ed to the actual questionnaire. In the event that the participant does not give consent, he/she should not navigate to the actual questionnaire. Four e-mails were sent to maximize the res ponse rate: 1) an e-mail letter that included a cover letter and the URL for the questionnaire; 2) an electronic thank yo u/reminder e-mail letter that included the URL for the que stionnaire (one week later); 3) a follow-up e-mail with the URL for the questionnaire (another one week later); and 4) final contact with an e-mailed letter that contains the URL for the questi onnaire (another one week later). Each of the DHPE and NACDD participants received four e-mails with a link to the web-based questionnaire. Due to a software error, SOPHE members received only two email messages. Data Analysis Data analysis was completed using the statistical package SPSS (version 13.0.1). All statistical tests were performe d at the 0.05 significance level. Descriptions of data . Descriptive statistics results provided information relating to the participants such as the mean and standard de viation of age, distri bution of gender, position titles, geographic stations, experience in public health, and level of education. Item analysis . Reliability is the extent to which an instrument measures what it is measuring consistently. For the purposes of this study, Cronbachâ€™s alpha was conducted. The item analysis focused on three areas: HHC use, HHC self-efficacy, and HHC anxiety. Each survey question was assi gned a numeric code for data entry. This data was exported from an online SurveyMonkey.com (www.surveymonkey.com ) database into an SPSS package
74 through Excel format. Demographic characteristic s of the respondents we re described via the mean, standard deviations and percentages. In addition, correlation analyses were used to examine associations between HHC use and HHC self-efficacy and HHC anxiety. Specifical ly, the Pearson Product-Moment Correlation Coefficient ( r ) was used to assess relationships betw een 1) HHC use and HHC self-efficacy, 2) HHC use and HHC anxiety, and 3) HHC self-efficacy and HHC anxiety. Summary A cross-sectional survey rese arch design was implemented among public health employees to address the research questions and hypothese s of the study. The survey instrument was modified from two existing instruments that i nvestigated computer self-efficacy and anxiety respectively (Cassidy and Eachus, 2002; Lest er, Yang, and James, 2005). This revised instrument assessed the level of HHC self-e fficacy and HHC anxiety among public health employees. The revised instrument consisted of items in three sections: Demographics and HHC use, HHC Self-Efficacy, and HHC Anxiety. Based on the results of the pilo t study, reliability and validity were established. The final survey wa s designed to sample from at least 962 public health employees. Data from the study was anal yzed using SPSS. Descri ptive and analytical statistics were used to answer research questions.
75 CHAPTER 4 RESULTS This study was designed to assess public health employeesâ€™ use of HHCs and the corresponding self-efficacy and anxiety related to their usage. A total of 466 participants including 309 members from SO PHE, 76 members from DHPE, and 91 members from NACDD completed the online surv ey between November 27th 2006 and January 10th 2007. Four responders who stated that they had no experience in public hea lth were eliminated from the overall analysis. Of the 466 final participants, 10 were members of two or more of the sampled organizations. However, since those members an swered the survey only once, all 462 surveys were usable. Finally, while the total response rate was 9.4% and less th an the targeted 40% response rate, the study resulted in 466 usable surveys and exceeded the needed 382 participants to portray a good represen tation of the population. It is also important to note that of the 4,913 members of the three NGOs, an indeterminate amount of people would have received the message s more than once (due to cross-membership within the NGOs). In other words, since the actu al membership lists were not released to the researcher, it may appear as if it would be di fficult to determine how ma ny unique participants were in the entire sample. However, after crossreferencing the IP addresses and position titles of each of the respondents, it was determined that no subject answered the survey more than once. The average age of the participants was 44 years old. Gender-wise, 85.5% were females and 14.3% were males. Demographic Profile of the Respondents The defined population for this study was pe ople employed in the public health field. Based on the membership lists counts provide d by DHPE, NACDD, and SOPHE, there were 4,913 total members. However, as stated prev iously, it was difficult to determine how many
76 members did not provide an e-mail addre ss and how many non-re sponding members are members of more than one of the organizati ons. Via multiple email messages, public health employees were contacted for the final survey. In order to determine whether or not a respondent answered more than one survey, IP addresses were cross-referenced with job titles. While there were a few users who had the same IP addresse s as other respondents, there were no duplicate job titles. In other words, no respondent answered the survey more than once from the same computer network. Among the usable responses, 85.7% were fema le (n=395) and 14.3% were male (n=66). The majority of respondents held a Master de gree (59.5%) and were primarily employed at the state level of public health (48.5%). Respondents we re aged from 22 to 62 years with a mean of 44 (SD=10.9). The number of years employed in public health ranged from less than one year to slightly over 40 years with a mean of 13 (SD= 9.4). All were affiliated at least one of the professional organizations with the majority (6 6%) of responders bei ng members of SOPHE. Table 4-1 contains a summary profile of the participants. Figure 4-1 shows the usage of handheld comput er, laptops, and deskt op computers in hours per week. Respondents reported that, on average, they used desktop computers 25.73 hours per week (N=222). Respondents reported that, on av erage, they used laptop computers 8.39 hours per week (N=215). Respondents reported that, on average, they used HHCs 5.94 hours per week (N=221). Participants were asked to re port their experience with spec ific software when using a HHC, using a laptop computer, a nd using a desktop computer. T ypes of software that were examined included: word processing, spreadsheet s, databases, presentation packages, desktop publishing, multimedia, Internet, and email (Table 4-2).
77 Participants were asked to evaluate their perceived competence using an HHC, using a laptop computer, and using a desktop computer. Th e respondents were aske d to interpret their competence with each of the three devices as follows: Very Incompetent Very Competent 1 2 3 4 5 The mean of the perceived competence using a HHC was less than perceived competence of using both laptop computers and desktop comput ers (Table 4-3). However, with a mean of 3.47 (SD=1.12) competency rating, the participants ag reed they were in th e level of somewhat competent. Research Questions One and Two Is every scale that comprised the inst rument reliable (Question One) and what results regarding each scale and each item within those s cales in the instrument does item analysis show (Question Two)? The final questionnaire included 55 items (19 usage and demographic, 30 selfefficacy, and 6 anxiety). The reliability and validity concerns were addresse d at the item level. Handheld Computer (HHC) Self-Efficacy Scale The HHC self-efficacy scale incl uded a total of 30 opinion items in the final questionnaire. The response format for the opinion questions is a 5-point Likert scaling (from strongly agree to strongly disagree). These items were coded from 1 to 5 with 1=strongly disagree and 5=strongly agree. Cronbachâ€™s alpha was performed on each of the items in the HHC Self-Efficacy scale. Table 4-4 shows the question, the corrected item-total correlati on, and Cronbachâ€™s alpha if the item is deleted. The Cronbachâ€™s reliability coefficient of the HHC self-efficacy scale was 0.951 (N=193). All items seemed to have small effects on scale reliability coefficient Cronbachâ€™s alpha.
78 Handheld Computer (HHC) Anxiety Scale The HHC Anxiety scale included a total of si x opinion items in the final questionnaire. The response format for the opinion questions is a 6-point Likert scaling (from strongly agree to strongly disagree). These items were coded from 1 to 6 with 1=strongly disagree and 6=strongly agree. Table 4-6 depicts the summary of ite m analysis for the 6 HHC anxiety items. The Cronbach's Alpha reliability coefficient of the opinion scale was 0.828 (N=212). All items seemed to have small effects on sc ale reliability coefficient alpha. Research Question Three To answer the question of whether or not an association between HHC use and HHC selfefficacy among public health employees existed, hours of HHC use in a week (N=218) were correlated with those items in the HHC use se lf-efficacy scale (N=222). Study results showed that on average, public health employees used HHCs an average of 5.94 hours a week (SD=8.832). The mean of perceived HHC competence was on average 3.47 (SD=1.122); the actual HHC self-efficacy was 3.75 (SD=.675). Data analysis showed a statistically significant positive relationship between hours of using a HHC and HHC self-efficacy (r=.209, p<.01). This indicated public health employees with highe r self-efficacy in using HHC tended to use HHC more at work. Furthermore, the participants â€™ perception of thei r competence using a HHC (N=225) was correlated with those items in the HHC self -efficacy scale as well (N=222). There was a statistically significant positive relationship between perceived HHC competence and HHC use self-efficacy (r=.529, P<.01). This indicated that public health employeesâ€™ perceptions of their HHC competence were fairly accurate at determin ing actual HHC self-effi cacy. The data further supports that as HHC use increases, there was an increase in reported HHC self-efficacy.
79 Research Question Four To determine if an association between HHC use and HHC anxiety among public health employees existed, hours of HHC use in a week (N =221) were correlated with those items in the HHC use anxiety scale (N=219). St udy results show that public hea lth employees did not appear to exhibit much anxiety related to HHC use (X=2.04, SD=.811). The data analysis showed a statistically significant negativ e relationship between hours of using a HHC and HHC anxiety (r=-.185, p<.01). This indicated that as public he alth employees used a HHC more often, their anxiety associated with th e device slightly decreased. Furthermore, the subjects perception of their competence using a HHC (X=3.47; SD=1.122) were correlated with those items in the HHC anxiety scale as well. There was a statistically significant negative relationship between perceived HHC competence and HHC use anxiety (r=-.408, P<.01). This indicat ed that public health employ eesâ€™ perceptions of their HHC competence was reflective of actual HHC anxiety. The data further supports that as HHC use increased, there was a decrease in reported HHC anxiety. Research Question Five To determine if an association between HHC self-efficacy and HHC anxiety among public health employees existed, the HHC self-efficacy scores (N=222) were correlated with the HHC anxiety scores (N=219). There wa s a statistically significant ne gative relationship between HHC self-efficacy and HHC anxiety (r=-.830, p<.01). Th e data supported that as HHC self-efficacy increases, there was a decrease in HHC anxiety.
80 Summary A total of 4,913 members in DHPE, NACDD, an d SOPHE were invited to participate in the web-based survey. With four hundred sixt y-two usable surveys be ing returned, the study exceeded the minimum number of cases needed to achieve power for statistical analyses about the sampled population. Among the usable response s, the majority of respondents were female and Caucasian. Nearly half worked at the state level in public health, and the majority held a Master degree. All participants were affiliated with at least one of the three sampled NGOs. Both the HHC self-efficacy and HHC anxiet y scales were found to be reliable. Furthermore, the data from this study suggest that as HHC use increases, there is an increase in reported HHC self-efficacy. Also, the data suppor ts that as HHC use increased, there was a decrease in reported HHC anxiety. Finally, th e data supported that as HHC self-efficacy increased, there was a decrease in HHC anxiety.
81 Table 4-1. Demographics by gender, age, years in public health, education, work setting, and professional affiliation of 462 re sponding public health employees. Demographics N Valid % Gender 461 Female 39585.7 Male 6614.3 Age 456 25 and under 122.6 26-30 5712.5 31-35 5912.9 36-40 449.6 41-45 6213.5 46-50 7215.7 51-55 7917.3 56-60 4710.3 61 and over 245.2 Years in Public Health 460 5 and under 11925.8 6-10 10823.4 11-15 7616.5 16-20 6313.6 21-25 388.2 26-30 347.3 31-35 173.6 36 and over 71.5 Education 461 High School 20.4 Bachelors 8418.2 Masters 27559.7 Doctorate 7616.5 Post-Doctorate 245.2 Work Setting 450 Federal 224.9 State 22449.8 Local 12026.7 Corporate 337.3 NGO 5111.3 Professional Affiliation DHPE 7616.5 NACDD 9119.7 SOPHE 30566.0 Belong to More than One NGO 102.0
82 Table 4-1. Continued Demographics N Valid % HHC is used on the Job 462 Yes 23250.2 No 23049.8 HHC is also a Phone 230 Yes 8336.1 No 14462.6 Donâ€™t Know 31.3 Attended a HHC Training 229 Yes 208.7 No 20991.3 Employer Requires Use of HHC 230 Yes 2812.2 No 20287.8 Employer Provides HHC 227 Yes 11751.5 No 11048.5 Own HHC that is Used for Job 231 Yes 11750.6 No 11449.4 Years Own HHC Used for Job 210 Less than One 83.8 One to Four 15473.0 Five to Eight 4521.3 Nine to More 31.9
83 Table 4-2. Frequency of usersâ€™ experience with software appli cations when using a HHC, laptop computer, and desktop computer (N=232). Software Desktop Laptop HHC Word Processing (N=224) 96% (216) 88% (196) 33% (73) Spreadsheets (N=218) 94% (206) 74% (162) 13% (29) Databases (N=201) 96% ( 193) 68% (136) 15% (30) Presentation Packages (N=220) 96% (212) 84% (185) 9% (20) Desktop Publishing (N=165) 90% (161) 72% (128) 4% (7) Multimedia (e.g., music/video) (N=179) 90% (161) 72% (128) 18% (32) Internet (N=223) 97% ( 216) 83% (186) 33% (73) Email (N=224) 96% (216) 83% (187) 50% (112) Table 4-3. Perceived competence using a HHC, using a laptop computer, and using a desktop computer. Device n Mean Standard Deviation HHC 2253.471.12 Laptop Computer 2244.151.09 Desktop Computer 2254.341.07 * Range = 1-5
84 Table 4-4. Summary of item analysis for th e 30 HHC self-efficacy items (alpha=0.951). Question X* SD Corrected Item Total Correlation Cronbachâ€™s Alpha if Item Deleted Most difficulties I encounter when using HHCs, I can usually deal with. 3.59 1.104 .678 .949 I find working with HHCs very easy. 3.52 1.083 .774 .948 I am very sure of my abilities to use HHCs. 3.47 1.081 .728 .949 I seem to have difficulties with most of the HHC programs I have tried to use. 3.808 1.022 .620 .950 HHCs frighten me. 4.482 .915 .347 .952 I enjoy working with HHCs. 3.65 1.046 .660 .949 I find that HHCs get in the way of my job. 4.211 1.021 .395 .952 HHC software doesnâ€™t cause many problems for me. 3.42 1.053 .567 .950 HHCs make me much more productive. 3.49 1.029 .642 .949 I often have difficulties when trying to learn how to use a new HHC program. 3.619 1.118 .623 .950 Most of the HHC programs I have used are difficult to use. 3.763 1.018 .676 .949 I am very confident in my abilities to use HHCs. 3.65 1.031 .798 .948 I find it difficult to get HHCs to do what I want them to do. 3.646 1.077 .780 .948
85 Table 4-4. Continued Question X* SD Corrected Item Total Correlation Cronbachâ€™s Alpha if Item Deleted At times I find working with HHCs very confusing. 3.523 1.128 .757 .948 I would rather that I did not have to learn how to use HHCs. 4.129 1.039 .545 .950 I usually find it easy to learn how to use a new HHC program. 3.55 .973 .681 .949 I seem to waste a lot of time struggling with HHCs. 3.857 1.052 .747 .948 HHCs make my job more interesting. 3.21 1.103 .472 .951 I always seem to have problems when trying to use computers. 4.290 .889 .407 .951 Some HHCs software definitely makes my job easier. 3.78 .974 .536 .950 HHC jargon baffles me. 3.635 1.033 .609 .950 HHCs are far too complicated for me. 4.236 .875 .551 .950 Using HHCs are something I rarely enjoy. 3.870 1.117 .574 .950 HHCs are good aids for my job. 4.06 .910 .578 .950 Sometimes when using a HHC, things seem to happen and I donâ€™t know why. 3.533 1.132 .564 .950
86 Table 4-4. Continued Question X* SD Corrected Item Total Correlation Cronbachâ€™s Alpha if Item Deleted As far as HHCs go, I donâ€™t consider myself very competent. 3.586 1.160 .529 .950 HHCs help me save a lot of time. 3.57 1.046 .626 .950 I find working with HHCs very frustrating. 3.967 1.017 .767 .948 I consider myself a skilled HHC user. 3.25 1.136 .715 .949 When using HHCs I worry that I might press the wrong button and damage it. 4.389 .930 .381 .952* Range = 1-5 Table 4-5. Summary of item analysis for the six HHC anxiety items (alpha=0.828). Question X* SD Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted I feel confident and relaxed while working on a HHC. 2.660 1.324 .512 .824 The harder I work at learning HHCs the more confused I get. 1.81 .942 .655 .790 I have sometimes thought that I am too old to learn about HHCs. 1.52 .988 .739 .778 I have sometimes thought â€œHHCs donâ€™t like me.â€ 1.59 .990 .474 .824 I always have problems working on HHCs. 1.75 .981 .575 .806 I can usually manage to solve HHC problems by myself. 2.931 1.291 .716 .779 * Range = 1-6
87 0 5 10 15 20 25 30 DesktopLaptopHandheld Hours of Weekly Use Figure 4-1. Average weekly hours of use of desktop, handheld, and laptop computers.
88 CHAPTER 5 CONCLUSIONS, DISCUSSION, RECOMMENDATIONS This non-experimental descrip tive and exploratory study used a web-based form to gather information about public health employeesâ€™ us e of HHCs, the corresponding HHC self-efficacy, HHC anxiety, and their relationships. The 58-item instrument consisted of 22 demographic and usage items, 30 HHC self-efficacy items, and 6 HHC anxiety items. Results demonstrated that people who use HHCs more often have greater HHC self-efficacy, and less associated HHC anxiety. Summary This exploratory study imple mented a cross-sectional survey among public health employees who were members of at least one of three NGOs (DHPE, NACDD, and SOPHE). The HHC-related survey instrument was develo ped based on selected concepts of Social Cognitive Theory, specifically in the construct of self-efficacy (Bandura, 1977). The items in the instrument were based on two valid and reliable pre-existing instruments that focused solely on non-handheld computers. To ensure the validity as we ll as test the reliability of the newly created HHC instrument, a pilot test was conducted with 13 public health employees in a federal public health agency. These colleagues were used for th e pilot test because of both the convenience aspect and the reality that all we re currently working in public health. All but one of the subjects had experience with HHCs; all pilot test subjects had experience with computers in general and public health. Item analysis was performed to determine if the questionnaire needed to be revised. The reliability values for both measurem ents were acceptable. Therefore, only minor wordsmith modifications to seven demographic/ use questions and the addition of one new HHC usage-based question was made to the survey. The revised instrument included 55 items in three sections: 1) demographics and HHC use, 2) HHC self-efficacy, a nd 3) HHC anxiety. Coefficients
89 of internal consistency of items in the pilot study were calculated. The values of Cronbachâ€™s alpha for the HHC self-efficacy and HHC anxi ety sections were 0.951 and 0.828, respectively. The defined population for this survey include d all voting and associate members of both DHPE and NACDD, as well as the general member ship of SOPHE. Based on the membership lists provided by the NGOs there were an es timated total of 4,913 members among the three organizations. However, it was impossible to determine exactly how many members were without an e-mail address and how many non-res ponding members were also members of more than one of the organizations. Via multiple email messages, all 4,913 public health employees were contacted for the survey. Each of the DHPE and NACDD participants received four e-mails with a link to the web-based questionnaire. Du e to the SOPHEâ€™s e-mail distribution software error, their members received only two e-ma il messages. Consequently, SOPHE members only had two weeks to respond to the survey. Had SO PHE members been given additional time, it is possible that even more respondents may have be en received. However, it is important to note that on the last day the survey was publis hed to be open for SOPHE members, over 100 responses arrived; for the week that the WBF was surreptitiously open after the published end date, no additional responses were obtained. Of the 466 total questionnaires re ceived, four responders stated that they had no experience in public health (nor even currently used an HHC ) and were eliminated from the analysis, thus leaving a total of 462 usable que stionnaires and meeting the thre shold for achieving statistical power. The study answered five research questions: 1. Is every scale that comprised the instrument reliable? Both the HHC self-efficacy and HHC anxiety scales were found to be reliable. The reliability coefficient of the HHC sel f-efficacy opinion scale was 0.951 (N=195). The reliability coefficient of the HHC an xiety opinion scale was 0.828 (N=212).
90 2. What results regarding each scale and each it em within the scale of the instrument do item analysis show? The results of the item analyses show that al l questions within the scales were adequate for the research purpose, as indicated by th e respectable or very good Cronbachâ€™s alphas. Each item correlated with the total score of its instrument showing good internal consistency. 3. Is there an association between HHC us e and HHC self-efficacy among public health employees? There appears to be a statistically signifi cant positive relationship between hours of using an HHC and HHC self-efficacy (r=.209, p<.01). Th ere was also a statistically significant positive relationship between perceived HHC competence and HHC use self-efficacy (r=.529, P<.01). The data supports the hypothesis that as HHC use increases, there is an increase in reported HHC self-efficacy. 4. Is there an association between HHC use and HHC anxiety among public health employees? Hours of HHC use in a week (N=222) were correlated with those items in the HHC use anxiety scale and the analysis showed a sta tistically significant negative relationship between hours of using an HHC and HHC anxiety (r=-.185, p<.01). Furthermore, the participantsâ€™ perception of their competen ce using an HHC showed a statistically significant negative relations hip between perceived HHC competence and HHC use anxiety (r=-.408, P<.01). The data supports that as HHC use increases, there is a decrease in reported HHC anxiety. 5. Is there an association between HHC use self-efficacy and HHC use anxiety among public health employees? The HHC self-efficacy scale was correlated w ith those items in the HHC anxiety scale. Results showed that there was a statistically significant negative relationship between HHC self-efficacy and HHC anxiety (r=-.830, p<.01). The data supports that as HHC self-efficacy increased, there was a decrease in HHC anxiety. Discussion As this study broke ground in an area where theory and supp orting research was incomplete, an exploratory research approach was warranted (Collins, 2006). The methodology used in this study was suitable because it allowed the public health field to obtain a deeper understanding of the phenomenon related to an under-explored concept, namely the use of a particular technological device a nd its associated impact on a us er. As evidenced by the growing
91 literature body relating to HHC us e in general, this study was an initial attempt to show an example of how a technological tool was being used to allow those in public health to move in person or virtually across many t ypes of environmental and tem poral barriers to transfer information, improve their skills, and provide better care to their constituents (Goldberg et al., 2005). Furthermore, this study explored the re lationship between usage of HHCs and two key constructs (i.e., anxiety and self-efficacy) that are well supported in the literature as being associated with usage of other t echnological tools. Such an appro ach yields critical insight into the nature of HHC use and can assist employers in creating tools and appl ications to support the growth of public health HHC use in the future. HHC Use Of those who answered the survey, partic ipants reported using desktop computers on average 25.73 hours a week and laptop computers an average of 8.39 hours a week for their jobs. On average, respondents who used HHCs repor ted using the device 5.94 hours a week. Most HHC users reported using Blackberry and Palm devices. Based on the data from this study, it also appears that many public health employees are frequently using HHCs with much of the usage relating to Internet and e-mail. Given th at many of the current HHC devices are designed to â€˜pushâ€™ e-mail from a hosting server immediately to HHCs, th is finding was not surprising. Considering what De Groote (2004) found among public health faculty members, usage of HHCs may be increasing. Of the 17 public heath f aculty members who responded in De Grooteâ€™s (2004) study, eight (47%) used an HHC. Among them, 11% used their HHCs for e-mail and 11% for Web access. In this study, results revealed th at among 462 public health employees who used HHCs, 232 (50.2%) used an HHC. Among them, 50% used their HHCs for e-mail and 33% for Web access. It is important to note that in the De Groote (2004) study, all eight of the HHC users used the device for time management; this was not a variable that was investigated in this study.
92 It is likely that had â€˜time managementâ€™ been an option for software use in this study, the percentage of overall usage would have been much higher. Future studies should investigate this particular aspect of HHC use and include it as a variable if using this instrument. Besides e-mail and Web access, many respondents in this study used HHCs in a variety of ways that have not previously been closel y examined among those who are public health employees. For instance, of thos e respondents who used HHCs, many noted that they used their devices for word processing (33% of respondents) , viewing spreadsheets (13% of respondents), utilizing information databases (15% of res pondents), working with electronic presentation packages (9% of respondent s), performing desktop publishing (4% of respondents), and viewing/listening to multimedia (18% of respon dents). These data add to the growing body of evidence that HHCs are becoming a versatile tool in the field that can enable data acquisition, analysis, and document developmen t (Futhey, 2000; Laskin & Davis, 2004; Merrell et al., 2004). The variety of HHC applications reported in this study was esp ecially encouraging. These data lend credence that rapid access to information ma y be a useful application of HHCs in public health (Cimono & Bakken, 2005). It is likely that by using HHCs, many of the respondents in this study were able to obtain and/or share in formation that could be used to prevent both infections and chronic diseases as well as serv e as an agent for health promotion efforts. Future research should examine not only how th ese software applications are being used among public health employees, but also why. For ex ample, are electronic databases being used because textbooks and other printed references are quickly outdated (Leung et al., 2003; Peterson, 2003)? Additional resear ch should explore not only the myriad of uses of HHCs as revealed by this study, but also the reasons they are used rather than other methods for things such as professional development trainings, providi ng technical assistance to constituents in the
93 field, sharing information between colleagues when other more traditional methods are inaccessible, and/or collecting and analyzing data (Stover, 2001). The software that respondents reported using in this study on their HHCs often has compatibility (and visual similarities) with those programs (e.g., Microsoft Office) that may typically be used on a desktop/la ptop in a public health office environment. As a result, it was not surprising that many respondents from this st udy had expressed intera ctivity with their HHC that transcends just e-mail or Internet usage. Th ese findings were consistent with other research as well (Daniels & Salisbury, 2003; Luo, 2004). In some part, HHC users within this study may also have expressed increased HHC self-effi cacy, decreased HHC anxiety, and increased HHC perceived competence due to the display on thei r HHC being similar to the desktop computers that they may use in their office, as suggest ed by previous research (Eastes, 2004). These similarities are not by chance. Over the pa st decade, HHC manufact urers have shown an increased effort to make the interface between HH Cs and desktop computers appear very similar. As a result, the findings of this study may par tially be explained by HHC users having a degree of comfort with the device that was related to the similarity of the desktop computer that they use more frequently (see Table 4-2). The data from this study also show that th e average HHC user (N= 225) stated that they: felt they were fairly competent using an HHC (X=3.47, SD=1.12); did not appear to exhibit much anxiety related to HHC use (X=2.04, SD= .811); and demonstrated fair self-efficacy (X=3.75, SD=.675). However, HHC users still reported higher perceived competence using laptop computers (X=4.15, SD=1.09) and desktop computers (X=4.34, SD=1.07) than HHCs. It is possible that the discrepancy between the de vices may be associated with various negative effects than have been previously associated with HHC use. For example, public health
94 employee users in this study who have vision and/ or dexterity problems, or are afraid of the fragility of the device might be less competent using an HHC (Barrett et al., 2003; Kerkenbush & Lasome, 2003; Miller et al., 2005; Peterson, 2004; Roschelle, 2003; Schuerenberg, 2004; Vernez et al., 2004) and report less perceived competence a ssociated with using the device. Additionally, it is also possible that the perceived competen ce discrepancy between th e computer devices may be associated with some respondents who are requ ired to use HHCs and intr insically believe that HHCs are not necessarily benefici al to their work (Carrol et al., 2004; Fischer et al., 2003; Nikula, 2001; Berg, 2001) and cons equently shy away from using th e device. As a result, they do not develop perceived competency. Finally, it may be possible that respondent s in this study reported less perceived competence due to an inadequate knowledge and/or concern of security measures that may or may not be associated with HHCs. For example, many researchers have suggested that some HHC users are concerned about the device being a high risk for breaching confidentially if sensitive data are stored on them (Bernard, 2003; Chang et al., 2003; Chan et al., 2004; Flanders et al., 2003; Guadagno et al., 2004; Hirani et al ., 2005; Laskin & Davis, 2004; Peterson, 2003; Peterson, 2004; Rosenthal, 2004). As a result, us ers may not only feel less competent using a HHC, but also feel more anxious about the applic ation of tasks that are associated with the device. HHC Anxiety Many studies have linked anxiet y at work with a plethora of major health problems (Begley, 1994; Chen & Spector, 1992; Ganste r & Schaubroeck, 1991; Humphrey, 1998; Kahn & Byosiere, 1992; Pennebaker, 1997; Sonnentag & Fr ese, 2003; Sparks et al., 1997; Van der Doef & Maes, 1999) and productivity and job performance (Faulkner & Patiar, 1997; Haslam et al., 2005). Techno-anxiety, or in the case of this study, HHC anxiety can be viewed as the ability of
95 computer work to induce a psychophysiological arousal pattern in sensitive workers (Arnetz, 1996; Arnetz, 1997; Berg et al., 1992). Conse quently, as the HHC usage hours among public health employees in the field continue to gr ow, associated HHC anxiety can seriously and negatively impact both the individual employee and the collective public health workplace. This study showed that 50.2% of the responde nts (N=462) used HHCs for their jobs. Of those who used HHCs, 51.5% (N=227) were pr ovided HHCs by their em ployer. Interestingly, 12.2% of HHC users (N=230) were required to use HHCs by their employer. Because of this trend and the threat of HHC-asso ciated anxiety, deliberate effort s should be made to provide employees (especially those who are required to us e HHCs) with training relating to use of this device. This is particularly necessary as HHC use appears to be growi ng within the field (De Groote, 2004) and may be linked to anxiety in some users. C onsequently, employers might, as Segerstrom & Miller (2004) sugge st, consider the idea of volunta ry, job-related screenings for those frequently using HHCs as a complimen t to existing employee assistance programs. Results of this study indicated that there was a statistically significant relationship (r=.185, p<.01) between hours of using an HHC and HHC anxiety. This finding is consistent with previous research that identifies (non-HHC) com puter use as being a c onsistent correlate of computer anxiety (Cohen & Waugh, 1989; Chu & Sp ires, 1991; Heinssen et al., 1987; Igbaria & Chakrabarti, 1990; Kay, 1990; Liu, et al., 1992 ; Marcoulides, 1988; R eed & Palumbo, 1988; Rosen et al., 1987). Furthermore, this finding is also consistent with pr evious research that suggests that a major factor in general computer anxiety is a lack of familiarity with computers and that increased experience s hould decrease anxiety (Heinssen et al., 1987; Howard & Smith, 1986; Lloyd & Gressard, 1984). Specifically, this study revealed that those who used HHCs more often had decreased HHC anxiety.
96 Furthermore, there was a statistically signi ficant negative relations hip between perceived HHC competence and HHC use anxiety (r= -.408, P< .01). In essence, it appears that perceived competence of HHC use may decrease actual HHC a nxiety. Further research would need to be done to determine why there was a relationship a nd if other variables may also be related to HHC use anxiety. This is a very important finding because the results of this study suggest it may be possible that HHC perceived competence, a variable also associated with self-efficacy (Bandura, 1977), may be useful in future st udies as a predictor of actual HHC anxiety. The findings from this study also support the established close relationship between anxiety and self-efficacy found in other literature (Bancila et al., 2006; Bandura, 1977; Beckers & Schmidt, 2001; Brosnan, 1998; Czaja et al., 2006; Giles et al., 2006; Karademas, 2006; Peiser & Shamshins, 2006; Weems & Silverman, 2006). Resu lts of this study showed that there was a statistically significant negative relationship between HHC self-efficacy and HHC anxiety (r=.830, p<.01). The data supports the hypothesis that as HHC self-efficacy increases, there was a decrease in HHC related anxiet y. These findings are consistent with what Compeau & Higgins (1995) found considering individuals with high self -efficacy experiencing less computer anxiety. Additionally, the findings of this study are consistent with earlie r research desc ribing computer self-efficacy as an important predictor of computer anxiety (Czaja, et al., 2006). HHC Self-Efficacy Employersâ€™ increased demands of their empl oyees using computer technology in general (including HHCs) may erode employeesâ€™ confid ence in using that same technology (Gist & Mitchell, 1992; Kinzie & Delcourt, 1991). As a result, a growing body of evidence suggests that building employeesâ€™ computer self-efficacy is just as important as building those same employeesâ€™ computer knowledge (Gist, 1987; Gist & Mitchell, 1992; Kinzie & Delcourt, 1991). Consequently, self-efficacy assessmen t is a critical factor in dete rmining HHC use, effectiveness,
97 and job performance (Staples et al., 1998). Result s of this study indicated that there was a statistically significant relati onship between hours of using an HHC and HHC self-efficacy (r=.209, p<.01). This finding is consistent with previous research th at identifies (non-HHC) computer self-efficacy as an important predicto r of general use of technology and that people with lower general self-efficacy are less likely to use technology in general (Czaja et al., 2006). This finding also supports the argument that people with lower self-efficacy display less motivation to engage in a task than those w ith higher self-efficacy (Bandura, 1997; Ellis & Allaire, 1999). Furthermore, there was a statistically signi ficant positive relationship between perceived HHC competence and HHC use self-efficacy (r= -.529, P<.01). In essence, it appears that perceived competence of HHC use may determ ine actual HHC self-efficacy as well as HHC anxiety. Further research would need to be done to determine why there was a relationship and if other variables may also be re lated to HHC use self-efficacy. Th is is a very important finding because the results of this study suggest that it may be possible that perceived competence (and in this case, perceived HHC competence), a vari able associated with self-efficacy in general (Bandura, 1977) may be useful in future stud ies as a predictor of actual HHC self-efficacy. Similar to earlier stated findings relating to HHC use training reduc ing anxiety, research also has shown that computer self-efficacy in creased significantly with computer training courses (Cassidy & Eachus, 2002; Ellis & Al laire, 1999, Hill et al., 1987; Torkzadeh & Koufteros, 1994). As stated earlie r, this study has shown that on ly 8.7% of HHC users (N=229) attended an HHC-specific training (T able 4-1). As a result, it is likel y that had more public health employees attended HHC training, reported HHC-rela ted self-efficacy in this study would have been even greater.
98 The findings of this study can help public health employers unde rstand, and shape, the work environment and behaviors of their employ ees. Results of this sentinel exploratory study will be the basis for future studies and will prov ide the public health field with a tool that determines the psychological impact of HHCs a nd a resultant probable ef fect on productivity and personal health and well-being. Furthermore, this exploratory st udy provides the necessary initial steps to establish HHCs as an agent that promotes professional portability in the field of public health. Implications for Training with HHCs By conducting this exploratory st udy, the field now has an instrument that has been piloted and validated among public health professionals, shown to have a high degree of reliability, and accurately identified factors that need to be addr essed in the public health worksite. For example, this study has shown that only 8.7% of HHC us ers (N=229) have attended an HHC-specific training (Table 4-1). This fi nding has great implications as many studies (Bozionelos, 1996; Choi et al., 2002; Igbaria et al., 1989; Jacobson et al., 1989) support that use of computers can be limited due to computer anxiety a nd lack of training. Also since pr evious research (Mahar et al., 1997; McInerney & McInerney, 1994) has shown th at increased usage combined with building skills from training can gradually diminish co mputer anxiety, HHC training is definitely warranted for the public health workplace. Maha r et al., (1997) specifically recommends that, while little research has been done to determine how to speci fically treat general computer anxiety, other methods of addressing general anxiety may be warranted. For example, HHC trainers may consider biofeedback training, relaxa tion therapy, or skill-sp ecific based training. It may be assumed that a combination of each or all of these trainings may be even more effective (Farhill, 1985).
99 Regardless of whether HHC training is focu sed on anxiety, use, or even self-efficacy (Dillon et al., 2003), some form of training for public health employees who are using HHCs in the workplace is critical (Joy & Benrubi, 2004). A training plan can be made to address the specific training needs of the individuals and shou ld be informed by literature relating to not only the results from this study, but the field of professional development and training (Wood & Thompson, 1993). Employers can provide or support HHC professional development and training in a number of ways, including: Establishing a cadre of HHC trainers who can provide and model effective HHC use and can provide ongoing support, training, and feedback. Using multiple training delivery systems, su ch as HHC workshops, interactive online training, and peer mentoring programs. Providing support staff to manage long and short-term HHC training. Coordinating marketing strategies to create awareness of and encourage participation in HHC training sessions. Training should identify the targ et audience for each event an d should include learning and performance objectives; training should also be evaluated for immediate and extended effectiveness. Training may need to be segmented according to the HHC competence and or HHC self-efficacy of the staff. The instrument from this study could be used to assess HHC competency and training needs an allow employe rs to tailor training toward HHC awareness sessions, basic HHC skills building, HHC program-s pecific training, and or customized learning plans for staff who may require specialized assistance. In addition, other research (Marcinkiewicz, 1993) suggests that employers conducting trai ning (either via in-house initiatives or externally-oriented) should be aware not only of variable s like self-efficacy and anxiety when considering training (Martocchi o, 1994), but also other constructs such as individual innovativenes s, age, gender, and who is actu ally performing the HHC training.
100 Additionally, as suggested by others (McAl earney et al., 2004), tr aining should address individual employeesâ€™ constr aints concerning HHC use (e.g., discomfort with technology, preference for using paper, concer ns about data security, and fear of over-reliance on the device). Finally, training oriented toward s HHCs must show that HHCs f it into current public health practices and offers a clear benefit over simp ler and less expensive a lternatives (Murphy, 2003). Employers could explore additional oppor tunities for HHC training through the organizationâ€™s IT staff, national or state level IT-focused conferences, technology-related magazines, or independent training consultants. Strategies should al so be explored that determine how a worksite will adopt specific HHC devices as well as how to facilitate their use. McAlearney et al., (2005) state that an organizational appr oach to HHC adoption and support involves individualized attention to existing and potential users rather than a general organization-wide effort. In ot her words, HHC trainings and e xpectations might best be well planned, well executed, and individual-focused. As a result of this study, researchers now have a reliable survey that can precede supplementary research which could reveal a dditional possibilities fo r better knowledge and training implications concerning HHC use and associations with social phenomena, such as selfefficacy and/or anxiety among public health employees. Limitations Sample Size It is important to note that, while the tota l response rate was 9.4% and less than the targeted 40% response rate, the study resulted in 466 usable surveys and exceeded the needed 382 participants to portray a good representation of the popula tion. However, the low response rate may be explained in a variety of ways. First, while the survey was or iginally planned to be sent to DHPE and NACDD listserv members on D ecember 4, there was a problem with the
101 NGOsâ€™ distribution lists and the ad min staff did not release the initial survey on December 11. Additionally, while survey reminders were intend ed to be sent out on Monday of each week for four weeks, reminders were occasionally sent by NGO staff one, two, or even four days later. Also, because of previous technology-related de lays, one of the protocol weeks ended up falling during the week of Christmas. Consequently it may be unlikely that staff within the sample were accessing their work-related email account. Finall y, due to similar technological problems, the initial SOPHE message was sent out two w eeks after the DHPE and NACDD messages. Consequently, SOPHE members only had two w eeks to respond to the survey. Had SOPHE members been given additional time, it is possible that a higher response rate may have been achieved. However, it is important to note that on the published last day the survey was open for SOPHE members, over 100 responses arrived; for the week that the WBF was surreptitiously open after that, no additiona l responses were obtained. It is also likely that an increased rate ma y have been more likely had some type of incentive been used. Fortunately, the questionnaire was brief enough that it may have resulted in preventing premature cessation of the survey. Additio nally, it is possible, that HHC owners were more likely to answer the emailed survey than non-HHC owners (De Groote, 2004). However, of the 462 usable responses, roughly half (n=230) did not use a HHC for their job and yet still answered the survey. Consequently, as a result of th e smaller (albeit statistically powerful) response rate, results from this survey may not be generalizable to th e field of public health outside of those sampled within the NGO membership. Future research should consider increasing th e response rate by: 1) incorporating incentives into th e research design, 2) expanding on the number of public health employees who are sampled (i.e., sampling from a larger public health NGO such as the
102 American Public Health Association (APHA), 3) conducting the survey at a time in the calendar year that is far away from most major holidays, and/or 4) attempt to manually send messages to the NGOs rather than rely on one of the organizationâ€™s staff. WBFs Approximately 29 participants requested results from this current survey. Opinions and comments from participants were mostly posit ive in relation to the study. However, three comments (two written and one oral) were received that demonstrated that some participants might have been unable to complete and submit th eir results due to diffi culties with the WBFs. For example: â€œI . . . was trying to fill it out . . . the SurveyMonkey was malfunctioning when I tried â€“ just wanted to let you know. [Hereâ€™s what I think th e] specific error was: I filled out data for every question on Page 1, but the error message sa ys that I left certain questions blank and won't move on to Page 2 unless those ite ms with an asterisk are answered.â€ â€œI tried responding to the Surv ey Monkey survey for your di ssertation. I answered every item on the first page, but got an error messa ge that I had omitted answering a required question and the survey would not let me proceed.â€ It appears that a bui lt-in requirement for participants to answer certain questions (specifically all three sub-questi ons of question number six) may inadvertently result in surveys not being completed. It is unc lear how many of the non-respondents may have had a similar problem and as a result did not complete the survey. Conclusions Based on the data analyze d, it is concluded that: The instrument, items, and scales develope d for this study are robust enough to be an appropriate measure of HHC use, self-e fficacy, and anxiety for future studies. Of those public health employees who used HHCs, when HHC use increases there appears to be an increase in reported HHC self-efficacy. Of those public health employees who used HHCs, when HHC use increases there appears to be a decrease in HHC anxiety.
103 Of those public health employees who used HHCs, there appears to be a positive relationship between HHC compet ence and HHC use self-efficacy. Of those public health employees who used HHCs, there appears to be a negative relationship between HHC co mpetence and HHC anxiety. As HHC self-efficacy increases, there is a decrease in HHC reported anxiety. Recommendations Based on feedback from the participants and the findings of this study, the following recommendations are made: This study, which examined solely public hea lth employees, was the largest of its kind. Because there are a great number of public heal th employees in the United States, and the use of HHCs appears to be growing (and is cu rrently even required by some public health employers) it is suggested that further re search be done to explore how technology may impact the well-being and productivity of this workforce in relation to other types of health-impacting constructs (e.g., general a nxiety, partner/spouse/family-related anxiety, eye strain, etc.). Additional research should be conducted using this study design among public health employees that are not members of DHPE, NAC DD, or SOPHE to see if results of this study can be replicated and result in a more representative profile of the public health employee population. For example, it may be advantageous to disseminate this questionnaire to the APHA, a professional organization that boasts more than 30,000 individual members and 20,000 additional state and local affiliate members representing more than 50 professional disciplines. The experiences of other professions that ha ve already made some progress with HHC use should be examined. Their useful strategies s hould be studied and adopted for future use. For example, as demonstrated by the literat ure review of this study, a large number of HHC-related studies have been conducted in th e clinical and educat ional sectors. Since public health can encompass those areas and ot her sectors, future research should examine the design and context of these studies to determ ine if results may be generalized to public health-specific activities. Feedback from participants in the study demons trates that some users may have difficulty working with WBF surveys. It may be a dvantageous to remove requirements for responders to answer all questions completely before they are able to continue future surveys that may use this instrument. Findings from this study confirm the emer ging importance of public health employers examining the impact of HHC use on their em ployees. For the purposes of this study, the author focused on general HHC anxiety rather than anxiety disorders associated with HHC use. More research is needed to examine how HHCs affect gene ral stress and anxiety
104 levels of public health employees and/or their family members or co-workers. For example, some respondents sent e-mail to th e researcher that supported a desire for a broader approach to how HHCs affect the lives of users and their families in terms of general stress and anxiety. This study showed that many organizations are moving forward and transitioning to purchasing and using HHCs. And, as also ev idenced by this study, employers are even requiring HHCs be used. Further exploratory re search should be done to determine why HHCs are being required and whether or not HH Cs are actually beneficial to employees and/or the public health employer. Additiona lly, research should be done that examines effective training methods that can be done which minimizes HHC anxiety, maximizes HHC self-efficacy, and results in a co rresponding increase in productivity. Considering this study examined one concept of Social Cognitive Theory (i.e., selfefficacy), future research should examine how Social Cognitive Theoryâ€™s other concepts can relate to HHC use and/or training. Fo r example, research examining reciprocal determinism might explore multiple ways to promote HHC use adoption and focus on ways to make adjustments to the public health worksite or personal attitudes relating to HHC use. Furthermore, training that is focused on the con cept of observational learning (i.e., modeling) might focus on encouraging HHC users who are credible role models to demonstrate effective/efficient use of HHCs. In attempting to make future generalizations about public health employees in the field, it may be useful for membership organizati ons to specifically track what additional professional organizations their members belong to and thereby minimize external validity threats. For example, when studying pub lic health employees stratified by NGO membership, it may be helpful for DHPE to definitively know which of their members have joint membership with NACDD, APHA, and/or SOPHE. This study revealed statistica lly significant relationships be tween HHC anxiety, HHC selfefficacy, and HHC use. It is imperative that fu ture research examines other chronologically defining variables associated with HHC use. This study assessed HHC usage by asking about â€œhours of HHC use.â€ Since HHC operators may not typically be using the device for hours at a time, future research might examin e â€œfrequency of usageâ€ rather than â€œduration of usage.â€ However, by taking this approac h, it would be difficult to determine those comparisons to laptop and desktop computers (w hich typically are used for hours at a time) that were done in this study. Research should be extended to different asp ects of public health employees (e.g., dental hygienists, nurses, health educators, environmen tal health engineers, etc.) to explore crosssector similarities and differences. Additio nally, further research should examine the evident impact of HHC training on employ ee health and productivity. Fostering an organizational culture that s upports HHC trainings has implications for improving the lives and work of all public health employees. Further research needs to examine applications of professional portabi lity relating to HHCs that might strengthen the sustainability of public health-care support in the field.
105 Specifically, further research might examine th e effectiveness of HHCs in areas such as providing technical assistance via e-mail/text messaging, sharing of information through HHC-driven PowerPoint presentations, and/or benefits associated with using HHC-based databases in the field. Demographic variables including age, gender, and/or years of public health experience may also influence the use of HHC and its relationship to HHC self-efficacy or HHC anxiety. Future studies might consider expand ing on the design of this study to explore the relationship of this variable to HHC use, self-efficacy, and anxiety as well.
106 APPENDIX A INSTRUMENT Handheld Computer User Self-Effi cacy and Anxiety Scale (HCUSEA) A handheld computer, also known as a personal digi tal assistant or PDA, is a handheld computer that allows a user to access email, the Intern et, calendar appointments, contact information, and even music and/or video. Some examples of such devices include Palm Pilots, Pocket PCs, and Blackberrys, and Smart Phones (dev ices that are predominantly considered phones but can also serve as a handheld computer). The purpose of this online questionnaire is to examine attitudes toward the use of handheld computers. The questionnaire is di vided into three parts. In part 1 you are asked to provide some basic background information abou t yourself and your experience with handheld computers, if any. Part 2 aims to elicit more detailed inform ation by asking you to indicate the extent to which you, personally, agree or disagree with the statements provided. Part 3 investigates handheld computer anxiety. Part 1: What is your job title: _____________________________ How many years have you been employed in public health? ____ What is your age: ____ Your gender: ____Female ____Male What is the highest level of e ducation that you have completed? ____high school ____bachelors ____masters ____doctorate ____post-doctorate At what level of public health are you primarily employed? ____federal ____state ____local ____corporate ____national non-government organization Are you a member of: ____Directors of Health Promo tion and Education (DHPE) ____National Association of Chr onic Disease Directors (NACDD) ____Society for Public Hea lth Education (SOPHE) Do you use a handheld computer (e.g., PDA, Blackberry, Pocket PC, etc.) for your job? ____yes
107 ____no What brand of handheld computer do you use most often for your job? _______________________________ Can the handheld computer that you use most often for your job also be used as a phone? ____yes ____no Have you ever attended a handheld computer training course? ____yes ____no Does your employer require that you use a handheld computer? ____yes ____no Does your employer provide you with a handheld computer? ____yes ____no Do you own the handheld computer that you use most often for your job? ____yes ____no How many years have you owned the handheld computer that you use most often for your job? On average, how many hours per week do you use: A desktop computer for nonjob related activities? ____ A handheld computer for nonjob related activities? ____ A laptop computer for non-j ob related activities? ____ A desktop computer for job related activities? ____ A handheld computer for j ob related activities? ____ A laptop computer for job related activities? ____ How competent do you feel using a handheld computer? very dissatisfied 1__ 2__ 3__ 4__ 5__ very satisfied How competent do you feel using a laptop computer? very dissatisfied 1__ 2__ 3__ 4__ 5__ very satisfied How competent do you feel using a desktop computer?
108 very dissatisfied 1__ 2__ 3__ 4__ 5__ very satisfied Relating to your job, what type s of programs have you used on handheld computers (please check all boxes that apply): ____word-processing programs ____spreadsheets ____databases ____presentation packages ____statistic packages ____desktop publishing ____multimedia ____internet ____email ____other (please specify)________________________________________________ Relating to your job, what types of programs have you used on de sktop computers (please check all boxes that apply): ____word-processing programs ____spreadsheets ____databases ____presentation packages ____statistic packages ____desktop publishing ____multimedia ____internet ____email ____other (please specify)________________________________________________ Relating to your job, what types of programs have you used on de sktop computers (please check all boxes that apply): ____word-processing programs ____spreadsheets ____databases ____presentation packages ____statistic packages ____desktop publishing ____multimedia ____internet ____email ____other (please specify)________________________________________________
109 Part 2: Below you will find a number of statements concerning how you might feel about handheld computers. Please indicate the strength of your agreement/disagreement wit the statements using the 5-point scale shown below. Mark the box that most closely represents how much you agree or disagree with the statement. There are no correct responses, it is your own views that are important. 1. Most difficulties I encounter when using ha ndheld computers, I can usually deal with. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 2. I find working with handheld computers very easy. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 3. I am very sure of my abilit ies to use handheld computers. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 4. I seem to have difficulties with most of the handheld computer programs I have tried to use. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 5. Handheld computers frighten me. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 6. I enjoy working with handheld computers. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 7. I find that handheld computers get in the way of my job. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 8. Handheld computer software doesnâ€™t cause many problems for me. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 9. Handheld computers make me much more productive. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 10. I often have difficulties when trying to learn how to use a new handheld computer program. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 11. Most of the handheld computer programs that I have had ex perience with, have been easy to use. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 12. I am very confident in my abilities to use handheld computers. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree
110 13. I find it difficult to get handheld computers to do what I want them to do. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 14. At times I find working with handheld computers very confusing. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 15. I would rather that I did not have to learn how to use handheld computers. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 16. I usually find it easy to learn how to use a new handheld computer program. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 17. I seem to waste a lot of time st ruggling with handheld computers. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 18. handheld computers make my job more interesting. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 19. I always seem to have problems when trying to use computers. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 20. Some handheld computer software definitely makes my job easier. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 21. Handheld computer jargon baffles me. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 22. Handheld computers are far too complicated for me strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 23. Using handheld computers is something I rarely enjoy. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 24. Handheld computes are good aids for my job. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 25. Sometimes when using a handheld computer, things seem to happened and I donâ€™t know why. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 26. As far as handheld computers go, I donâ€™ t consider myself very competent. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 27. Handheld computers help me save a lot of time. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree
111 28. I find working with handheld computers very frustrating. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 29. I consider myself a skilled handheld computer user. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree 30. When using handheld computers I worry that I might press the wrong button and damage it. strongly disagree 1__ 2__ 3__ 4__ 5__ strongly agree Part 3: Using the 6-point scale, mark the circle that most closely represents how much you agree or disagree with the statement. 31. I feel confident and relaxed wh ile working on a handheld computer. strongly disagree 1__ 2__ 3__ 4__ 5__ 6__ strongly agree 32. The harder I work at learning handheld computers the more confused I get. strongly disagree 1__ 2__ 3__ 4__ 5__ 6__ strongly agree 33. I have sometimes thought that I am too old to learn about handheld computers. strongly disagree 1__ 2__ 3__ 4__ 5__ 6__ strongly agree 34. I have sometimes thought â€œHandheld computers donâ€™t like me.â€ strongly disagree 1__ 2__ 3__ 4__ 5__ 6__ strongly agree 35. I always have problems working on handheld computers. strongly disagree 1__ 2__ 3__ 4__ 5__ 6__ strongly agree 36. I can usually manage to solve ha ndheld computer problems by myself. strongly disagree 1__ 2__ 3__ 4__ 5__ 6__ strongly agree Thank you for your time.
112 APPENDIX B LETTER OF INFORMED CONSENT Protocol Title: The Relationships of Handheld Computer Use, Techno-Anxiety, and Self-Efficacy among Public Health Employees. Please read this consent document carefully befo re you decide to participate in this study. Purpose of this study: The purpose of this study is to assess public h ealth employeesâ€™ use of handheld computers and the corresponding self-efficacy and tec hno-anxiety related to their usage. What you will be asked to do in this study: By electing to initiate the online survey, you are consenting to answer que stions relating to your demographics, the extent of your usage of handhe ld, your level of efficacy relating to handheld computers, and your level of techno-anxi ety relating to handheld computers. Time required: 10 minutes Risks and benefits: Your participation will contribute to the literature , but we do not anticipate that there will be risk involved by participating in this study. Compensation: There is no compensation given for participating in this study. Confidentiality: Your identity will be kept confidential to the ex tent provide by the law. Your name will not be used in any report. For questions about your rights as a research participant, please contact the IRB at firstname.lastname@example.org . Voluntary Participation: Your participation in this study is completely voluntary. There is no penalty for not participating. Any questions or concerns that you have about y our participant rights can be directed to the UFIRB office, Box 112250, University of Florida, Gainesville FL 32611-2250 (email@example.com ). Right to withdraw from the study: You have the right to withdraw from the study at anytime without consequence. You do not have to answer any questions that you do not wish to answer. Whom to contact if you have questions about the study:
113 Michael Schmoyer Doctoral Candidate Department of Health Education & Behavior University of Florida HappyFmly@Bellsouth. Net W. William Chen, PhD Faculty Advisory Department of Health Education &Behavior University of Florida firstname.lastname@example.org Agreement: By clicking on the link below, I am indicating that I have read th e procedure described above. I agree to participate in the procedure and I have received a copy of this description.
114 APPENDIX C LETTER ONE Dear XXX Members, Below is an e-mail from Michael Schmoyer, a public health colleague, who has worked with [NGO] for the past several years. Michael is surveying health profe ssionals on the use of handheld computers and their relationship to an xiety and self-efficacy. If you could please take 510 minutes to complete his survey he would greatly appreciate it. Also linked below is a protocol description rega rding your participation. Thank you for your help. ****************************************************************************** ** As a fellow public health employee, I would like to give you the opportunity to answer a brief (<9 minutes) survey relating to handheld computer use, anxiety, and self-efficacy. This, the first study of its kind that focuses on our field, provides us a great opport unity to examine Palm Pilot, Blackberry, Smart Phones, and other handheld computers use among those employed in public health. Please, even if you do not currently use a handheld computer, consider taking a few moments to provide this important data before 12/4/06. The aggregated results of this study will be shared with the membership offices of the Directors of Health Prom otion and Education, the National Association of Chronic Di sease Directors, and the Society for Public Health Education. The data from this study (as well as the work site wellness implications for state health departments) will also be presented at an upcoming major public health conference. Thank you so much, Michael https://www.surveymonkey.com/s.asp?u=194302891802 By clicking on the link above, you are indicating th at you have read the procedure described in the Letter of Informed Consent linked below. You have also agreed to participate in the procedure and have received a c opy of the protocol description. Letter of Informed Consent
115 APPENDIX D LETTER TWO As a fellow public health employee, I would like to remind you of this opportunity to answer a brief (<9 minutes) survey relating to handheld computer use, anxi ety, and self-efficacy. This, the first study if its kind that focuses on our field, provides us a great initial opportunity to examine Palm Pilot, Blackberry, Smart Phones, and other handheld computers use am ong those employed in the public health. I thank those of you who took the time to provide me f eedback; if you haven't yet co mpleted the survey, please consider providing me your insight. Thank you so much, Michael https://www.surveymonke y.com/s.asp?u=194302891802 By clicking on the link above, you are indicating that you have read the pr ocedure described in the attachment of this email. You have also agreed to participate in the procedure and have received a copy of the protocol description.
116 APPENDIX E LETTER THREE As a fellow public health employee, I would like to t hank you for answering the brief (<9 minutes) survey relating to handheld computer use, anxiety, and self-effica cy. This, the first study if its kind that focuses on our field, provides us a great initial opportunity to examine Palm Pilot, Blackberry, Smart Phones, and other handheld computers use among those employed in the public health. Again, I thank those of you who took the time to provide me feedback; if y ou haven't yet completed the survey, please consider providing me your insight. Thank you so much, Michael https://www.surveymonke y.com/s.asp?u=194302891802 By clicking on the link above, you are indicating that you have read the pr ocedure described in the attachment of this email. You have also agreed to participate in the procedure and have received a copy of the protocol description.
117 APPENDIX F LETTER FOUR Dear xxx Members, Please note the final reminder below from Michael Schmoyer, a public health colleague, who has worked with [NGO] for the past several years. Michael is survey ing health professionals on the use of handheld computers and their rela tionship to anxiety and self-efficacy. Thank you for your help. ****************************************************************************** ** As a fellow public health employee, I would like to thank you a final time for answering the brief (<9 minutes) survey relating to handheld computer use, anxiety, and self-efficacy. This, the first study of its kind that focuses on our field, will provi de us a great initial opportunity to examine Palm Pilot, Blackberry, Smart Phones, and ot her handheld computers use among those employed in public health. Again, I thank all of you who took the time to provide me feedback; if you have not yet completed the survey, please consider providing me your insight. Thank you so much, Michael https://www.surveymonkey.com/s.asp?u=194302891802 By clicking on the link above, you are indicating th at you have read the procedure described in the Letter of Informed Consent linked below. You have also agreed to participate in the procedure and have received a c opy of the protocol description. Letter of Informed Consent
118 APPENDIX G INSTITUTIONAL REVIEW BOARD APPROVAL
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136 BIOGRAPHICAL SKETCH LT Michael Schmoyer is a commissioned officer in the United States Public Health Service. LT Schmoyer is currently stationed as a Program Analyst in the Office of the Director in the Division of Adolescent & School Health ( DASH) at the Centers for Disease Control and Prevention (CDC). Overall, LT Schmoyer has worked in DASH for four years (starting off in the Research Application Branch, eventually moving to the Program Development and Services Branch and the Research Application Branch, a nd currently in the Offi ce of the Director). LT Schmoyer earned his BS (physical educa tion & health science) and MSEd (health education) from SUNY Brockport. After comple ting his University of Florida PhD program (health and human performance), LT Schmoyer will (after a brief respite) initiate work on an MA in national security. Over the course of his career, LT Schmoyer has been awarded the Distinguished Service Award (2007); Society of State Directors of Health, Physical Education, and Recreation CDC International Experience and Tec hnical Assistance (IETA) fellowship (2006); Centers for Disease Control and Prevention Outstanding Graduate Student Teaching Award (2001-2002); University of Florida Thomas F. Hayes, IV, Memorial Graduate Scholarship (2001); Un iversity of Florida Grinter Fellowship (1999-2000) ; University of Florida Whoâ€™s Who in American Colle ges and Universities (1996) Residential Life Outstanding Se rvice Award (1995); SUNY Brockport LT Schmoyer has been in the health educati on/public health field for over twelve years working at the federal level (CDC/DASH), with universities (SUNY Broc kport, University of Rochester, and University of Florida), schools (t eaching, extracurricular education, and assisting special needs children), and national non-government al organizations (Catholic Family Charities
137 shelter programs, and the American Red Cross). Wh en he is not in the office, Michael enjoys Latin dancing with his wife, spending time in his garden, and practicing martial arts.