Work behavior types, job satisfaction, and attrition in medical technology

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Work behavior types, job satisfaction, and attrition in medical technology
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Thesis (Ph. D.)--University of Florida, 1984.
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Includes bibliographical references (leaves 130-142).
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by Sybil Auriel Wellstood.
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Vita.

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Full Text















WORK BEHAVIOR TYPES, JOB SATISFACTION, AND
ATTRITION IN MEDICAL TECHNOLOGY











BY

SYBIL AURIEL WELLSTOOD


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN
PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR THE DEGREE OF DOCTOR OF PHILOSOPHY


UNIVERSITY OF FLORIDA


1984


















ACKNOWLEDGEMENTS


The author thanks Dr. Margaret Morgan for her time, expertise,

and guidance as chairperson of the doctoral committee. She also

thanks Drs. James Hensel, Herman Baer, Sylvia Coleman, and Gordon

Lawrence for serving as committee members.

A special acknowledgement goes to Dr. John Nickens who provided

valuable assistance with the Marcus Paul Placement Profile and data

analyses.

The author is grateful for the cooperation and support of the

chief medical technologists and administrators in participating

facilities. She is also indebted to the technologists and former

technologists who provided the data for this study.

Finally, the author thanks John, a special friend, who provided

support, encouragement, a sympathetic ear, and numerous chocolate bars

during this ordeal.


























TABLE OF CONTENTS


Page


ACKNOWLEDGEMENTS . . . .


ABSTRACT . . . .


CHAPTER


I INTRODUCTION . . .


Background . .
Statement of the Problem .
Delimitations and Limitations
Justification for the Study
Assumptions . .
Definition of Terms .
Organization of the Study .


II REVIEW OF RELATED LITERATURE . .


Organization of the Chapter .
Job Satisfaction .
Definition . .
Measures . .
History . .
Theories ...


Intrinsic Factors and Job Satisfaction
Extrinsic Factors and Job Satisfaction
Individual Differences .
Turnover................
Definition . .
fC


Personal and Demographic Predictor Variables
Organizational and Work Environment Variables
SJob Content Variables . .
Attitudinal Variables . .
Availability of Alternatives . .
Turnover Models . .
Work Behavior Type . ... .
Definition . . .
Industrial Psychology . .
Educational Psychology .. ... .
Theories of Vocational Development .
History of Work Behavior Types .
Marcus Paul Placement Profile .
Job Satisfaction, Attrition, Work Behavior Typl
Medical Technologists . .


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CHAPTER Page

III DESIGN AND METHODOLOGY . ... 72

Design . . . 72
Population . . .. 73
Data Collection .... . . 73
Instrumentation . . .. 76
Job Descriptive Index. . .. 76
Marcus Paul Placement Profile. . .. 77
Questionnaires for Practicing and Former Medical
Technologists . .. .. 79
Data Treatment and Analysis . .. 79

IV RESULTS . . .. 81

Description of Population. . ... 81
Practicing Medical Technologists . 81
Former Medical Technologists . .. 83
Research Questions . . .. 87
Chapter Summary. . . .107

V SUMMARY, CONCLUSIONS, AND IMPLICATIONS .. .109

Problem and Procedures . .. 109
Conclusions. . . .112
Implications .... . ... 113
Recommendations . . 115

APPENDICES

A LETTER TO CHIEF MEDICAL TECHNOLOGISTS. ... 118

B INSTRUMENTS . . 120

C LETTER TO PRACTICING MEDICAL TECHNOLOGISTS .. 127

D LETTER TO FORMER MEDICAL TECHNOLOGISTS . 129

LIST OF REFERENCES .... . . .130

BIOGRAPHICAL SKETCH . . .. 143
At


















Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy


WORK BEHAVIOR TYPES, JOB SATISFACTION, AND
ATTRITION IN MEDICAL TECHNOLOGY

By

Sybil Auriel Wellstood

April 1984

Chairman: Margaret Morgan
Major Department: Curriculum and Instruction


Job dissatisfaction and attrition are major concerns in medical

technology. The purpose of this study was to identify work behavior

types of medical technologists and to determine their relationship to

job satisfaction and attrition. Information generated by this work

could be useful in counseling and matching the right person to the

right job.

Ninety-two bench-level technologists employed in hospital and

nonhospital laboratories and 19 former technologists employed in a

variety of occupations comprised the sample. The Job Descriptive

Index measured job satisfaction. The Marcus Paul Placement Profile

indicated work behavior type. A questionnaire provided demographic data.

The majority of technologists were females (78.3%) with more than

5 years experience. One third expected to leave medical technology and

22.8% expected to leave within the coming year. Most received












inadequate career counseling prior to choosing medical technology;

three fourths indicated information about work behavior types would have

helped in career decision making.

Technologists were predominantly Producers and Concentrators.

These types occurred more frequently than in the general population.

Work behavior types among former technologists approximated those of the

general population. Findings are consistent with earlier research on

personality types among medical technologists.

Results indicate that work behavior type relates to overall and

specific aspects of job satisfaction. Inducers indicate higher levels

of overall job satisfaction and satisfaction with promotions than other

types. The relationship between work behavior type and attrition is

equivocable. However, Energizers and Inducers leave at higher rates

than Producers and Concentrators.

Former technologists are more satisfied with their jobs, work,

pay, promotions, and co-workers than practicing technologists in

hospital or nonhospital laboratories. No differences exist in overall

job satisfaction or specific aspects of it among practicing technologists.

Although the sex of the participant does not affect job satisfaction,

sex relates to attrition and may stem from poor salaries received by

technologists compared to others with comparable education.

Attrition from medical technology can be predicted from age, sex,

years experience, satisfaction with promotions, Producer and Energizer

scores. These variables explain 30.4% of the variance in attrition.


vi


















CHAPTER I
INTRODUCTION


Work is a central life activity for the majority of adults in

modern society--more than just a means for earning a living. According

to Terkel (1972), work is

a search, too, for daily meaning as well as daily bread,
for recognition as well as cash, for astonishment rather
than torpor; in short, for a sort of life rather than a
Monday through Friday sort of dying. Perhaps immortality,
too, is part of the quest. (p. xi)

Since the Industrial Revolution, job dissatisfaction, turnover,

and poor productivity have been growing problems among American

workers. Toeffler (1980) stated that industrialization "drove a

giant invisible wedge into our economy, our psyches, and even our

sexual selves" (p. 53). Industrialization separated production from

consumption and producer from consumer. Mass production brought

synchronization, centralization, specialization, standardization,

concentration, and maximization. Workers lost control over the

processes and outcomes of work. The importance of skill and

creativity diminished and workers no longer felt challenged or

stimulated.

Industrialization also satisfied workers' lower order needs

enabling them to focus on satisfaction inherent in the work itself.

Workers demand that work be satisfying, meaningful, and less

depersonalized. They expect equity and justice in the work place












and sufficient wages to live comfortably, according to the current

standard of living (Yankelovich, 1974). When these demands and

expectations clash with the realities of the world of work,

disappointment, dissatisfaction, and turnover may follow.

Inadequate career planning and improper placement of people in

jobs are central to the problems of job dissatisfaction and turnover.

Poor use of human resources often leads to a mismatch between the

individual and the job. Effective person/job matching is a major

challenge for business, industry, and education today.

This study was designed to provide new insights into the

problems of people/job matching in medical technology. The purpose

was to investigate the relationship among work behavior types, job

satisfaction, and attrition among a selected group of Florida medical

technologists.


Background


Since the 1970s, medical technology has been expanding to meet

the growing demands of the nation's health care system. Technological

advances have created needs for additional technologists to perform

the increasing numbers of laboratory tests available to physicians for

diagnosis, prevention, and treatment of disease. Population growth,

especially for the elderly, greater health awareness by the public,

and widespread availability of health insurance have also, indirectly,

influenced personnel requirements for medical technology. Employment

opportunities will continue to spiral. Projections for the 1980s

indicate that the number of medical technology positions will increase











faster than the average of all occupations (U.S. Bureau of Labor

Statistics, 1982).

In 1982, approximately 205,000 medical laboratory workers were

employed in hospitals, independent laboratories, physicians' offices,

clinics, public health agencies, pharmaceutical companies, and

research institutions (U.S. Bureau of Labor Statistics, 1982). Many

others will be needed to fill new positions and to serve as replacements

for those who retire, die, or leave medical technology for other kinds

of work.

The literature contains increasing evidence that the numbers of

technologists will not be sufficient to fill future vacancies. Jeanne

Burson (1981), former president of the American Society for Medical

Technology, indicated that medical technology, like nursing, is facing

a personnel shortage. She attributed this situation, in part, to

insufficient pay for the educational requirements and job responsibilities

demanded by the profession. She also stated that medical technologists

have experienced an "identity crisis." Many feel they do not receive

adequate recognition as health care professionals from the public or

from other health care practitioners.

Studies by Hajek and Blumberg (1982), Myers, Bronstein, and Vojir

(1982), Koneman (1982), and Irwin (1983) on job dissatisfaction and

attrition among medical technologists also agreed with these

observations. More than half of the technologists working today

indicated they would not be active in medical technology within 5 years.

Schools of medical technology are facing declining enrollments.

Some schools have been forced to close or operate with less than full

enrollments. Others have accepted less qualified applicants in order











to remain open (French & Elkins, 1982). These are indications that

schools of medical technology may not graduate sufficient numbers of

technologists to meet the increased demands for these allied health

professionals.

The current trends in attrition among medical technologists and

the shortage of new graduates could have serious impact on the health

care industry. Koneman (1982) noted that future laboratories might be

staffed by inexperienced, less qualified individuals. The National

Commission for Health Certifying Agencies (cited in Irwin, 1983) also

expressed concerns about the effects of technologists' dissatisfaction

and attrition on the quality and accuracy of laboratory results.

High turnover not only compromises the quality of patient care;

it also raises the cost of that care because the care must be provided

by fewer people at higher rates (Price & Mueller, 1981). Karni,

Studer, and Carter (1981) found that laboratory personnel were among

the most expensive hospital employees to replace. Simpson and LaValle

(1983) estimated that turnover costs for a vacated staff technologist

position could run as high as $7,458. These costs are eventually

passed along to the patient consumer, making health care an expensive

commodity.

Attrition also represents a waste of human resources, with

psychosocial implications for individuals, organizations, and society.

Greenberg (1979) indicated that 80% of the people working today are not

matched to the right job. Not surprisingly, a majority of American

workers are dissatisfied with their jobs and would not voluntarily

choose the same work again if given the opportunity (Special Task Force

to the Secretary of H.E.W., 1973).











In a recent study by Irwin (1983), medical technologists expressed the

same views.

During the past 20 years, the rising educational level of American

workers has increased their expectations and demands for useful,

satisfying work. However, the realities of the job may not fulfill

these expectations. Furthermore, the capabilities of the employee

often do not match the requirements of the job (Jelinik, 1979). Under

these conditions, the worker fails to achieve self-actualization,

becomes dissatisfied with the job, and sometimes leaves the organization.

Medical technology students are prepared to assume a collaborative

role with physicians and become members of the health care team. In

addition to being trained to perform tests and report results, they are

trained to interpret the significance of those results. However, poor

communications and rivalries between technologists and the medical staff

preclude technologist involvement in patient care at this higher level.

Recent advances in automation have also reduced the technical expertise

required to perform tests. Yet employers tend to "overhire" and

technologists find themselves in relatively low paying, routine jobs

that provide little opportunity for self-actualization, esteem, or

upward mobility. The brightest and best recruits may also become the

most dissatisfied workers and move on to more challenging fields.

Therefore, placement and training decisions must be based on additional

factors.

Although organizations claim that human resources are their most

important asset, they do little to match an individual's skills,

knowledge, interests, aptitudes, or work behavior preferences to

available jobs. Jelinik (1979) stated that even the most progressive











organizations lacked expertise in the area of person/job matching.

Many use outdated selection and placement methods that include

evaluation of past work history, educational background, interviews,

and reference checks. Occasionally these subjective techniques may

be supplemented by objective, job-related tests (Silver & Berke, 1981).

During the past 10 years, industrial psychologists and other

researchers have contributed useful knowledge and methods for a more

rational approach to matching people to jobs or students to careers.

Recent studies in the personnel selection literature provide a greater

understanding of the basic structures and taxonomies of human

characteristics. Others have suggested significantly improved methods

for measuring the behavioral components of jobs and job performance

dimensions (Dunnette & Borman, 1979). McCormick's (1976) task

inventory technology has provided a basis for job analysis techniques

used to infer the personal attributes important for doing a job. The

development of job samples has permitted evaluation of a candidate's

proficiency in performing the tasks involved in the job. Job samples

have been useful for jobs requiring motor skills and are more valid

than other types of tests in reflecting an individual's performance

level (Asher & Sciarrino, 1974).

Dunnette and Borman (1979) conceptualized the ideal counseling and

placement system of the future: a data bank containing the parameters

of available jobs and the attributes of available persons. Standardized

task checklists, scorable in terms of behavioral and attribute

categories, would be used to derive job parameters. Job candidates or

students would use similar checklists to record previous experience,

preferences, and estimated capabilities. Scores generated according











to job and attribute categories would be referred to the data bank for

job matching. Aptitude tests, job knowledge tests, job samples, and

simulations would provide additional data for individual and organizational

decision making.

Recent studies by Bauch (1981) and Glenn (1982) indicated that an

individual's work patterns or work behavior traits also played an

important role in job matching and recommended additional research in

this area. The assumption is that effective job matching will maximize

use of human resources and decrease job dissatisfaction, poor

productivity, and turnover.

As previously discussed, job dissatisfaction and attrition are

major concerns in medical technology. In the interest of providing

new insights into these problems, this investigator examined the

relationships among work behavior type, job satisfaction, and attrition

among Florida medical technologists.


Statement of the Problem


The problem of this study was to determine the relationships

among work behavior type, job satisfaction, attrition, and demographic

variables of medical technologists in Florida. The study was developed

to answer the following research questions:

1. What are the work behavior types of medical technologists
in Florida as measured by the Marcus Paul Placement Profile?

2. Does a relationship exist between the work behavior type
of technologists and overall job satisfaction as measured
by the Job Descriptive Index?

3. Does a relationship exist between work behavior types and
specific aspects of job satisfaction as determined by the
subscales of the Job Descriptive Index?











4. Do participants' work behavior types relate to attrition
or the intention to leave medical technology?

5. Do medical technologists working in hospitals differ in
overall job satisfaction from those working in nonhospital
laboratories or other fields?

6. Do medical technologists working in hospitals differ in
specific aspects of job satisfaction from those working
in nonhospital laboratories or other fields?

7. Does a relationship exist between the sex of the
participant and job satisfaction?

8. Does a relationship exist between the sex of the
participant and attrition or the intention to leave
medical technology?

9. Can some combination of demographic variables, work
behavior type, and job satisfaction predict attrition
of Florida medical technologists?


Delimitations and Limitations


This study was delimited by the following factors:

1. The subjects of this study were practicing and former staff
medical technologists in Florida holding, at least, a
Bachelor of Science degree.

2. Information on work behavior type was confined to that
measured by the Marcus Paul Placement Profile.

3. Information about job satisfaction was restricted to the
facets measured by the Job Descriptive Index.

The following limitations were also observed in this study:

1. Medical technologists volunteered to participate in this
study. There is no assurance they are representative of
the population of medical technologists in Florida or
medical technologists in general. Therefore, results may
not be generalizable to other populations of technologists.

2. The design of the study made it impossible to manipulate the
independent variables.











Justification for the Study


Medical technologists are dissatisfied with their jobs and are

leaving the profession to work in other areas. Karni et al. (1982)

estimated that the overall turnover rate among laboratory personnel

in Minneapolis hospitals ranged between 15% and 20%. An estimated

43% of those resignations were avoidable. Investigators have

identified many sources of dissatisfaction and attrition and have

made many recommendations to remedy the situation. Although these

proposals have merit, they have not alleviated the problem. Attrition

among medical technologists not only impairs the delivery of health

services; it represents a significant threat to the quality and cost

of health care. Immediate solutions are required to reduce the

attrition rate and reduce personnel shortages in medical technology.

Research indicates that people exhibit a particular pattern of

behaviors and qualities in the working situation (Geier, 1979). When

individuals have information about their work behavior styles and they

are matched to jobs requiring and encouraging those styles, they have

a greater opportunity for success and job satisfaction. The right "fit"

between employee and job also decreases the likelihood that the employee

will become frustrated and quit.

If information were available on the work behavior types of

medical technologists who enjoyed their work and intended to remain in

the profession, major efforts could be directed toward matching people

with these profiles to jobs and educational programs. This study was

designed to add to the limited research on work behavior types.

Findings may also provide new insights into the problems of job











satisfaction and attrition among medical technologists as these

problems relate to people/job matching.

Results of the study may also have implications for career

planning, academic advising, and planning effective educational and

training programs for medical technologists. Advisors, counselors,

students, and employers may use the information as a basis for a

more systematic approach to hiring and career selection. Program

developers may apply the results in developing instructional strategies

that would foster and enhance work behaviors essential for success in

medical technology.


Assumptions


This study is based on the following assumptions:

1. Participants answered the surveys honestly and responses
accurately reflect their attitudes and preferences.

2. The Marcus Paul Placement Profile is a valid and reliable
instrument for measuring work behavior type of medical
technologists.

3. The Job Descriptive Index is a valid, reliable measure of
job satisfaction.

4. Responses to behavioral intention questions predict
turnover.


Definition of Terms


Medical technologist. An individual who has completed four years

of college with a Bachelor of Science degree in medical technology or

a Bachelor of Science degree that includes 16 hours of chemistry, 16

hours of biology, and one semester of math and is qualified to perform

laboratory tests that require the exercise of independent judgment and











responsibility under the supervision of the laboratory director or

supervisor.

Job satisfaction. A participant's score in the Job Descriptive

Index.

Attrition. As used in this study, the loss of medical

technologists to other fields or professions.

Marcus Paul Placement Profile (MPPP). An instrument designed to

measure work behavior type (described more fully in Chapter II).

Work behavior type. A description of an individual's general

qualities and behaviors as they relate to the work situation and

derived from responses on the Marcus Paul Placement Profile.

Job Descriptive Index (JDI). An instrument designed to measure

job satisfaction (described more fully in Chapter III).


Organization of the Study


The remainder of this study is organized into four chapters.

Chapter II presents a review of the literature and research on job

satisfaction, attrition, and development of work behavior types. It

concludes with a review of the literature on these topics as they

relate to medical technologists.

Chapter III describes the design and methodology of the study.

It contains the research design, population, data collection,

instrumentation, and procedures.

Chapter IV contains the results of the study, including data

analysis, and discussion.

Chapter V includes a summary of the study, conclusions about the

findings, implications, and recommendations for additional research.


















CHAPTER II
REVIEW OF RELATED LITERATURE


Organization of the Chapter

This review covers four areas. The first section presents an

overview of research on job satisfaction. This is followed by a review

of the literature on turnover, including the relationship between job

satisfaction and turnover. The next section consists of research and

theories leading to the development of work behavior types and the

Marcus Paul Placement Profile. The final section provides a synthesis

of the research on job satisfaction, attrition, and career development

in medical technology.


Job Satisfaction

Definition

According to Locke (1976), more than 3,000 articles, books, and

dissertations have been written about job satisfaction. Gruneberg

(1979) stated it was one of the most researched topics in psychology.

Because job satisfaction impacts on the well-being of individuals,

organizations, and society, it is not surprising to find a large

volume of research on this subject.

Numerous definitions of job satisfaction have emerged from these

studies and researchers do not agree on a single, universal definition

of the term (Locke, 1969). Davis (1977) related job satisfaction to

the fit between employee and job. For him, it was











the favorableness or unfavorableness with which employees
view their work. It results when there is a fit between job
characteristics and the wants of employees. It expresses
the amount of congruence between one's expectations of the
job and the rewards that the job provides. (p. 74)

Smith, Kendall, and Hulin (1969) defined job satisfaction as "feelings

or affective responses to facets of the situation" (p. 6). Wanous

and Lawler (1972) listed nine different operational definitions,

theoretically based on need fulfillment, equity, or work values.

Porter and Steers (1973) defined job satisfaction as the "sum total of

an individual's met expectations on the job" (p. 167).

The term job satisfaction is, however, distinguished from the

term morale. The former refers to an individual's response to the

job and the latter term refers to group well-being (Gruneberg, 1979).

Measures

Job satisfaction has also been measured by a variety of

objective, descriptive, or projective instruments. Many investigators

have devised new instruments or altered others to meet the demands of

their particular study. Objective surveys contain questions with

pre-determined responses. Descriptive surveys allow respondents an

opportunity for unstructured replies and questions are open-ended.

Psychologists devise and administer projective surveys to assess

mental health, usually in nonwork settings (Davis, 1977).

Herzberg (1966) used a form of descriptive survey called the

critical incident technique to collect data on job satisfaction.

He asked workers to think of a time when they felt especially good

or bad about their jobs. While this technique has been popular, it

has also been criticized (Gardner, 1977).










Wanous and Lawler (1972) determined that different measures of

job satisfaction may not assess the same variables and concluded there

was no one best way to measure this construct. In a later review of

the literature, Gruneberg (1979) drew the same conclusion and added

that the best measure of job satisfaction depended on the variables

under investigation.

However, the Job Descriptive Index (JDI) developed by Smith,

Kendall, and Hulin (1969) has been regarded as the most reliable,

carefully developed, and researched instrument for measuring job

satisfaction. After examining inventories and terms used by previous

investigators to describe the same or similar facts, Smith and

co-workers found five common factors in these inventories. They

included a general factor, a pay and material rewards factor, the work

itself, a supervision factor, and a factor related to other workers on

the job. These factors formed the five subscales of the JDI and

measured satisfaction with work, pay, opportunities for promotion,

supervision, and co-workers.

History

Historically, industrial psychologists have been interested in

job satisfaction since the early 1900s. In 1911, Frederick Taylor

brought principles of scientific management to the work setting.

Using time and motion studies at the Bethlehem steelworks, he redesigned

equipment, simplified, fragmented, and compartmentalized work tasks,

and placed workers under continuous supervision. Although primarily

concerned with increasing productivity and efficiency, Taylor also

called attention to the importance of the human element in getting the

job done.











In the 1920s, the "human relations" school of thought on job

satisfaction emerged from the Hawthorne studies conducted by Elton

Mayo (1933). Like Taylor, Mayo sought to find ways to improve

productivity by altering physical work conditions. However, he also

observed that human relationships within the organization were more

important to the workers. He contended that "friendly" relationships

between employees and supervisors or between co-workers led to job

satisfaction. Job satisfaction, in turn, led to higher productivity.

Hoppock (1935) published results of several studies on job

satisfaction. He used survey methods and attitude scales to collect

his data. He concluded job satisfaction consisted of many factors.

The presence of these factors in the work situation led to satisfaction

while their absence led to job dissatisfaction. He also examined the

relationship among job satisfaction, life satisfaction, and mental

health. In a survey involving 500 teachers, 21% of the least

satisfied teachers were from unhappy homes, compared to only 6% of

the teachers expressing high satisfaction.

Theories

Campbell, Dunnette, Lawler, and Weik (1970) classified current

theories of satisfaction as either content or process theories.

Content theories relate to factors that motivate people to work and

process theories are intended to explain job satisfaction in terms of

the interaction between the individual's needs and what the job actually

offers.

Maslow's (1943) needs hierarchy theory is a major content theory.

He explained the dynamics of job satisfaction in terms of fulfilling

individual needs. Maslow arranged human needs in an ascending hierarchy.











Lower-order needs were (a) basic physiological needs, (b) safety and

security needs, and (c) social (affection) needs. Higher-order needs

were (d) esteem and (e) self-actualization. Lower-order needs had to

be satisfied before higher-order needs could assume importance.

However, once a need was met, it no longer served as a motivator.

Building on Maslow's work, Herzberg, Mausner, and Snyderman (1959)

formulated the two-factor theory of job satisfaction. They claimed

that two classes of work variables, the motivators and hygiene factors,

influenced job satisfaction. Motivators were intrinsic factors such

as achievement, recognition, advancement, responsibility, and the

inherent interest of the work itself. When present in a job,

motivators were satisfiers because they had a positive effect on

employee output. Achievement was the strongest motivator followed by

recognition. Motivators correspond to Maslow's higher-order needs.

Hygiene factors were extrinsic to the job and included pay,

security, supervision, and physical working conditions. They were

analogous to Maslow's lower-order needs. When absent from the job,

they were linked to dissatisfaction. However, Herzberg and associates

clearly pointed out that the presence of a hygiene factor doesn't

automatically produce job satisfaction and the absence of a motivator

doesn't necessarily lead to dissatisfaction.

Vroom's (1964) expectancy theory is representative of process

theories. He proposed that job satisfaction depended on the degree to

which a job met the individual's needs. Motivation depended on the

workers' perceptions of the likelihood that their needs would be

satisfied. Individuals ascribe valences to job outcomes such as

higher pay, promotion, peer approval, and recognition, according to











their perceived importance in satisfying various needs. Workers also

assign a valence to the expectancy or their perception of the likelihood

the outcome will actually materialize. Motivation is a product of the

valence of expectancy times the valence of the outcome.

Porter and Lawler (1968) expanded and refined Vroom's model. They

developed a multivariable model to explain the complex relationship

among motivation, satisfaction, and performance. They claimed that

the amount of effort or motivation expended by an employee depended on

the interaction between the value of the reward for them and the

perceived effort-reward probability. Effort leads to performance and

the level of performance depends on the employee's abilities, traits,

and role expectations as well as the amount of effort expended. The

rewards that follow performance and how they are perceived affect job

satisfaction.

According to the Porter and Lawler model, job satisfaction

depends on the extent to which rewards measure up to the individual's

perceived equitable level of those rewards. In contrast to previous

models, in this model the theorists recognize that job satisfaction

is only partially determined by actual rewards received. The

employee's perceptions of what the rewards should be for a given

level of performance also play a significant role in satisfaction.

Furthermore, this model states that satisfaction depends on performance

and not the reverse.

Equity theorists are also process theorists who examine job

satisfaction in terms of the equity in treatment workers perceive they

receive compared to the treatment others receive in a similar job.

Adams (1965) argued that the degree of equity or inequity perceived by











an employee is compared to other workers and forms the basis for job

satisfaction and motivation. Employees contribute Inputs (skills,

personal traits, and experiences) to a job. They receive Outputs

(salary, promotions, praise) from the work. They form a ratio of

Inputs to Outputs and compare it to other workers. The ratio must be

perceived as equal for the worker to be satisfied.

Recently, attribution theory and locus of control have become

important for understanding job satisfaction. Attribution theorists

claim that an individual's perceived behavior is determined by

internal forces (personal attributes such as ability, effort,

fatigue) and external forces (environmental attributes such as rules

or the weather). People behave differently when they perceive internal

as compared to external attributes (Luthans, 1981).

Locus of control explains work behavior in terms of employees'

perceptions of internally or externally controlled outcomes.

Perceived locus of control has an impact on job performance and

satisfaction. Mitchell, Smyser, and Weed (1975) tested the

attribution/locus of control model and found that internally

controlled employees are generally more satisfied with their jobs

than employees who perceive external control.

Intrinsic Factors and Job Satisfaction

Herzberg et al. (1959) were the earliest investigators to point

out the importance of changes in the actual job performed as a

necessary factor for increasing job satisfaction. Success, recognition,

appreciation of skills, the feeling of doing something worthwhile, and

job involvement are content or intrinsic factors of the actual job

performed that affect job satisfaction.











Locke (1965) demonstrated that success at a task increased job

satisfaction because success enhanced self-esteem. However, the

individual had to perceive the task as being important (Nord, 1977).

Many individuals also require external validation of their successes

and achievements in the form of tangible recognition (promotion,

merit pay increase) or intangible recognition (praise). In one study,

workers rated recognition by supervisors and colleagues as a major

source of job satisfaction (Locke, 1976).

Workers must also be able to use their skills or abilities to

feel successful at a job. Walker and Guest (1952) studied the

relationship of skill level to job satisfaction among automobile

production workers. They found job satisfaction was related to the

amount of skill required and to the number of operations performed in

a job.

Hackman and Lawler (1971) examined the relationship of job

satisfaction to job variety, job autonomy, job identity, and feedback.

Findings on job variety agreed with those of Walker and Guest (1952).

However, Hackman and Lawler (1971) added that not all employees

preferred task variety in their jobs. Individuals with little interest

in meeting higher-order needs were satisfied with repetitive work.

The degree of job autonomy (the extent to which individuals make

decisions about their jobs) was also positively correlated to job

satisfaction. Workers free to choose their own methods and pace of

work were satisfied. Task identity or wholeness of the work was

important for job satisfaction among workers with higher-order needs.

They had to perform an entire piece of work for it to have meaning

and be satisfying.











Lodahl and Kejner (1965), Weissenberg and Gruenfield (1968), and

Hall, Schneider, and Nygren (1970) reported a positive correlation

between job satisfaction and job involvement. Job involvement is the

extent to which an individual identifies with a particular job

(Gruneberg, 1979). Individual attitudes toward work (Lodahl, 1964),

strength of higher-order needs (Hackman & Lawler, 1971), and the

organizational structure or situation (Argyris, 1964; Rabinowitz &

Hall, 1977) influence job involvement. However, little is known

about how individuals develop an interest in a particular job

(Gruneberg, 1979).

Extrinsic Factors and Job Satisfaction

Although intrinsic factors are generally regarded as most

important for job satisfaction, extrinsic or context factors also play

a significant role. These factors include pay, job security, work

groups, and supervision.

Pay is an important aspect of job satisfaction. It provides more

to individuals than the means to purchase goods and services. Pay is

often associated with achievement, recognition, and worth; Wernimont

and Fitzpatrick (1972), however, found significant individual

differences in the meaning of money according to the stage of career

development, experiences, sex, economic status, and personality of the

worker.

The actual level of pay is not as important to job satisfaction

as the relative level. According to the equity theorists (discussed

earlier), workers compare themselves to other workers in terms of

Inputs and Outputs. Individuals weigh the equity of their pay in

terms of their skills, amount of effort, responsibility, and











experience compared to pay received by similar workers. Dissatisfaction

occurs when the pay received is not perceived as equitable (Warr &

Wall, 1975).

Many individuals rate job security as a leading factor for job

satisfaction. It is one of Herzberg's Hygiene factors and, when

absent, causes job dissatisfaction. When it is present, however, it

is unimportant. Our society places a high value on work. Individuals

associate having a job with competence and worth. Siassi, Crocetti,

and Spiro (1975) identified a higher incidence of mental illness in

the unemployed compared to others. Herzberg, Mausner, Peterson, and

Capwell (1957) pointed out the importance of the work group and social

aspects of the job for job satisfaction. Maslow (1943) also included

needs for social interaction as a basic lower-order need. Walker and

Guest (1952) demonstrated that workers with isolated jobs were more

dissatisfied than others. In addition, Van Zelst (1952) found that job

satisfaction, turnover, and productivity improved when workers were

permitted to select their work mates. Workers of similar backgrounds,

skills, and values formed cohesive work groups. These groups also

provided support, generated feelings of self-esteem from being valued

by others, and were a source of satisfaction derived from cooperating

with others to achieve common goals.

Supervision is another extrinsic factor involved in job satisfaction.

The "human relations" school of management regarded "friendly" supervision

as vital for the improvement of job satisfaction. The Hawthorne studies

related increased productivity to increases in friendly supervision.

However, these results have been questioned and increased productivity

may have resulted in friendlier supervision (Gruneberg, 1979).











Weed, Mitchell, and Moffitt (1976) examined the relationship

between leadership style and job satisfaction. They distinguished

between employee-oriented leaders who established personal relationships

with employees and were pleasant and leaders who were task-oriented and

saw the group as a vehicle for achieving production targets.

Task-oriented leaders also initiated and organized the work. However,

Warr and Wall (1975) pointed out that task-oriented leaders were not

necessarily the opposites of employee-oriented leaders. Task-oriented

leaders also demonstrated concern for employees while organizing the

work.

House (1971) stated that different groups of workers wanted and

expected different styles of leadership. Unskilled and semi-skilled

workers resented the task-oriented supervisor. High-level workers

found this type of supervision satisfying because it helped them achieve

goals.

One of the major sources of discontent among workers is the

feeling that they have no say in what happens to them. A number of

studies have indicated that a democratic style of leadership increases

job satisfaction and cooperation (Coch & French, 1949; Startup &

Gruneberg, 1973). Workers usually indicate a desire to participate in

decision making, especially when the decision directly affects them

(Hespe & Wall, 1976). Employee participation in decision making not

only results in higher job involvement and greater commitment to the

decisions made, it also produces better decisions, develops group

cohesion, and establishes group norms (Argyle, 1972). The Japanese

have capitalized on participatory management theories. Their success











as world leaders in technology has been largely attributed to this

management style (Ouchi, 1981).

Kahn, Wolfe, Quinn, Snoek, and Rosenthal (1964) and Keller (1975)

studied job satisfaction in terms of role ambiguity and role conflict.

Individuals experience role conflict when the behaviors expected of

them are inconsistent with the behaviors they expect of themselves.

They experience role ambiguity when expectations are unknown or unclear.

Role ambiguity and role conflict in the job situation often create

stress and job dissatisfaction. However, there are differences related

to the occupational level of the worker (Kahn et al., 1964; Schuler,

1977). Role ambiguity was more stressful for higher level personnel

in organizations, whereas lower level personnel experienced more job

dissatisfaction when role conflict existed.

Organizational climate or the quality of the total workplace

environment also affects job satisfaction. However, Friedlander and

Margulies (1969), Pritchard and Karasick (1973), and Schneider and

Snyder (1975) pointed out that individual differences played a

significant role in the relationship between these factors. For

example, organizations with high levels of control appealed to workers

with strong needs for security, whereas creative individuals or those

who preferred to participate in decision making favored more democratic

organizations. Supportiveness, concern for social relationships,

progressiveness, harmony, and consideration were important aspects of

organizational climate correlated to high job satisfaction.

Individual Differences

In addition to the content and context factors of the job,

individual differences between people affect job satisfaction.











Researchers have considered the influence of age, sex, educational

level, race, cultural background, and personality. However, results

from this area of job satisfaction research have not been as consistent

or reliable as results from other areas.

Herzberg, Mausner, Peterson, and Campbell (1957) found a U-shaped

relationship between age and job satisfaction. Job satisfaction

starts out high in the young worker, declines rapidly, and then rises

again with increasing age. Supposedly, as individuals age they adjust

more easily to work and life situations. Hunt and Saul (1975)

related age and job satisfaction to the sex of the worker and found

significant relationship only in males. Glenn, Taylor, and Weaver

(1977) found a significant relationship in both sexes. Hulin and

Smith (1965) disagreed with the U-shaped relationship between age and

satisfaction. They found that satisfaction declined five years

before retirement. At this stage of a worker's career, opportunities

for growth and promotion usually declined.

Studies relating sex to job satisfaction have also been

contradictory. According to traditional thinking, men and women had

different attitudes and values about work and jobs. Schuler (1975)

stated that women were more interested in the social aspects of the

job, whereas men were interested in self-expression and promotion

opportunities. Herzberg et al. (1957) also reported that males

regarded the intrinsic factors of the job as more important than

females did. Brief and Oliver (1976) found no significant sex-related

differences in work attitudes, particularly when other variables

(occupational level, salary, career orientation) were statistically

controlled.










Klein and Maher (1966) and Vollmer and Kinny (1955) reported a

negative correlation between education level and job satisfaction.

These findings suggested that employees with higher levels of

education expected more from their jobs and became more dissatisfied

when the job failed to meet those expectations. They also pointed

out the problems in hiring over-qualified individuals for positions,

or unnecessarily raising the academic qualifications for a job.

Herzberg et al. (1957) showed a positive relationship between

education and job satisfaction.

In a 1973 survey conducted by a Special Task Force, job

satisfaction among minority groups was consistently lower than

satisfaction among white workers. However, Jones, James, Bruni, and

Sells (1977) found no differences in overall job satisfaction among

black and white sailors matched by type of job.

The relationship between job satisfaction and personality

factors has not been thoroughly researched (Gruneberg, 1979).

Clearly, however, aspects of personality determine the extent to

which different job characteristics affect an individual's job

satisfaction.

For example, McClelland (1961) demonstrated that individuals with

high needs for achievement required challenging jobs to enhance their

self-esteem and provide them with job satisfaction. Steers (1975) found

that individuals with high achievement needs derived job satisfaction

from high levels of job performance. These high achievers became

involved in their jobs when they perceived opportunities for success

and rewards as a result of performance.











Self-esteem is another personality dimension related to job

satisfaction. Warr and Wall (1975) argued that job satisfaction

declines when an individual's self-esteem is threatened. This may

occur when workers are unable to apply skills or are placed in

situations where they compare poorly with other workers.

Korman's (1977) findings on self-esteem and job satisfaction were

comparable to Steer's results for high achievers and job satisfaction.

He demonstrated that those with high self-esteem were satisfied when

they performed well on the job. However, these individuals also

expected rewards for high performance and experienced job dissatisfaction

when they did not receive those rewards.

Many studies have focused on the relationship between personality

type, measured by the Myers-Briggs Type Indicator (MBTI), and job

satisfaction. The MBTI is an instrument designed by Myers (1962) to

identify personality type according to dimensions of extraversion (E)

or introversion (I), sensing (S) or intuition (N), thinking (T) or

feeling (F), and judging (J) or perception (P).

Brown's (1973) study of occupational therapists in Florida,

William's (1975) study of medical technologists, and Kuhn's (1981)

study of teachers revealed that extraverts were more satisfied with

their overall careers than introverts. Fellers (1974), French and

Rezler (1976), and Glenn (1982) found no relationship between

personality type and job satisfaction among dietitians, medical

technologists, and vocational education administrators. In 1975,

Clitsome studied job satisfaction and turnover of intensive care (ICU)

and general staff nurses. Among ICU nurses, judging types were more











satisfied than perceptive types. Among general staff nurses, the STJ

types were more satisfied with work than the NFP types.

In summary, job satisfaction is a complex, multifaceted attitude.

A variety of content (success, recognition, appreciation, job variety,

job autonomy, job involvement), context (pay, job security, supervision,

work groups, role ambiguity, role conflict, organizational climate),

and personal factors (age, sex, education level, race, personality type,

tenure) affect an individual's job satisfaction. Job satisfaction, in

turn, impacts on many other aspects of life. The relationship between

job satisfaction and turnover will be discussed in the next section.


Turnover

This section is a review of literature describing the turnover

process. It will include definitions of turnover, consequences for

the individual and organization, predictor variables (personal,

organizational/work-related, job content, attitudinal), and turnover

models.

Definition

Turnover has also been a well researched topic. According to

Steers and Mowday (1981), more than 1000 studies have appeared in the

literature since 1910.

Brayfield and Crockett (1955) described turnover as an extreme

behavior along a continuum of behaviors showing psychological withdrawal

of commitment to a job. Absences, lateness, grievances, strikes, and

sabotage are less extreme forms of withdrawal behavior that may precede

or substitute for turnover when quitting is not a viable option.

Because most turnover is voluntary (Price, 1977), Price and Mueller











(1981) called turnover "a voluntary separation from an organization"

(p. 2).

Gillies (1982) classified turnover as unavoidable or avoidable.

Marriage, childbearing, or transfer of a spouse were associated with

unavoidable turnover, where avoidable turnover resulted when a job

failed to meet the employee's needs or expectations.

Consequences

Turnover has increased significantly in many organizations over

the past 20 years. Turnover rates of 50% to 60% are not unusual

(Silver & Berke, 1981).

Turnover has both negative and positive consequences for the

organization, the individual leaver, and the individual stayer. For

the organization, the cost of replacing one employee is high. Direct

and indirect costs are involved. Direct costs include expenses for

recruiting, selecting, processing, orienting, and training new

employees. Indirect costs are incurred for overtime pay for remaining

employees to complete the work. New employees are also less efficient

and productive during training periods (Gillies, 1982).

Turnover also has-potentially desirable consequences for organizations.

These include replacement of poor performers, opportunities for cost

reduction, consolidation, introduction of new knowledge/technology,

and internal mobility (Mobley, 1982).

The cost of turnover for the individual who decides to leave an

organization may include increased stress, disruption of family and

social life, loss of seniority and nonvested benefits, and moving

expenses. Advantages of quitting could include higher earnings,











career advancement, better person-organization "fit," stimulation from

a new environment, and self-development (Mobley, 1982).

Most researchers have neglected the "stayers" in the turnover

process. Those who remain with the organization may become overburdened

by the increased workload created by the loss of an employee.

Performance may decline as a result of the increased demands and

stress. Morale, commitment, and satisfaction may decrease, especially

if the departing employee voices strong negative opinions about the

job or organization. Leavers may also make others aware that better

jobs are available elsewhere. When the departing employee was a

valued member of the work group, social and communication patterns

may be disrupted by the loss of this employee. On the other hand,

turnover may increase promotion opportunities for those who remain and

the new replacement may fit in better with coworkers (Mobley, 1982).

Personal and Demographic Predictor Variables

Researchers have identified critical factors involved in the

turnover process. Some investigators have examined personal and

demographic variables as predictors of the decision to terminate

employment. These factors include age, tenure, and family

responsibilities.

With few exceptions, there is a strong positive relationship

between age and turnover (Muchinsky & Tuttle, 1979). However, Mobley,

Griffeth, Hand, and Meglino (1979) pointed out that age was related to

many other variables and, alone, explained only 7% of the variance in

turnover.

Tenure in an organization (length of service) is consistently,

inversely related to turnover (Muchinsky & Tuttle, 1979). Mangione











(1973) and Steers (1977) suggested tenure was one of the single best

predictors of turnover behavior.

Family responsibilities, including marital status and number of

dependents, are also associated with turnover. For males, increases

in family responsibilities are inversely related to withdrawal.

However, for females, the relationship depends on the wage earner

status of the employee. When women work as primary wage earners, there

is a negative relationship between family responsibilities and turnover,

whereas for women who are secondary wage earners, increases in family

responsibilities are positively correlated to withdrawal (Federico,

Federico, & Lundquist, 1976).

Schuh (1967) attempted to predict turnover from personality and

vocational inventories and biographical information. Although he

found no relationship between turnover and scores on intelligence,

aptitude, or personality tests, he did find evidence for predicting

turnover from vocational interest inventories and biographical

information.

Organizational and Work Environment Variables

Pay, promotion, supervision, and peer group relations are

organizational and work environment factors related to turnover.

Early studies indicated that low pay and few promotion opportunities

were major reasons for withdrawal (Mobley et al., 1979). Knowles

(1964), Hulin (1968), and Federico, Federico, and Lundquist (1976)

pointed out that the perceived equity of pay and promotion was more

important than the actual pay received in the decision to stay or quit.

Recent studies suggest there is no relationship between pay, promotion,











and turnover (Koch & Steers, 1978; Kraut, 1975; Mobley, Horner, &

Hollingsworth, 1978).

These inconsistencies may be attributed to other variables that

mediate the effects of pay satisfaction on turnover. Mobley (1977)

and Mobley et al. (1978) reported that intention to quit and intention

to search for another job were the direct antecedents of turnover.

Pay satisfaction may be more correlated to these variables than to

actual turnover.

Motowidlo (1983) examined the relationship between pay

satisfaction, amount of pay, expectations of receiving more satisfying

pay in another job, withdrawal intentions, and actual quitting.

Satisfaction with pay explained 43% of the variance in withdrawal

intentions beyond that explained by age, tenure, general satisfaction,

amount of pay received, and pay expectation. Although the amount of

pay received was weakly correlated to turnover, results suggest it is

strongly associated with pay satisfaction which, in turn, is related to

withdrawal intentions.

Saleh, Lee and Prien (1965) demonstrated the importance of

supervisory behavior as a variable in turnover among hospital nurses.

Nurses cited lack of consideration from supervisors as a major reason

for leaving. Ley (1966), Hulin (1968), and Graen and Ginsburgh (1977)

obtained similar results for production and clerical workers.

Bassett (1967) related turnover to the amount of supervisory

experience. Employees supervised by individuals with less than 5 years

of management experience withdrew at a higher rate than employees with

more experienced supervisors.











Although studies, generally, offer support for a negative

relationship between satisfaction with supervision and turnover,

Mobley et al. (1979) identified several recent studies that show no

significant relationship between these variables. The nature of the

leadership measures and the need for multivariate analyses may

explain these results.

Research conducted during the past 10 years on the relationship

between peer group interactions and turnover indicates no significant

correlation between these variables (Mobley et al., 1979). Although

Koch and Steers (1978) found a significant relationship between

satisfaction with co-workers and turnover, only 4% of the variance in

turnover was explained by this factor.

Studies prior to 1973, however, indicated a strong, negative

impact of peer group relations on turnover (Evan, 1973; Farris, 1971;

Hulin, 1968; Schuh, 1967). Porter and Steers (1973) suggested that

individual needs for affiliation played an important role in explaining

discrepant findings in this area of turnover research.

Job Content Variables

Satisfaction with the work itself, task repetitiveness, job

autonomy and responsibility, and role clarity are job content variables

impacting on an employee's decision to terminate employment.

Satisfaction with the work itself is negatively correlated to

turnover. However, it explains less than 16% of the variance in

turnover (Mobley et al., 1979).

Routinization of jobs and task repetitiveness contribute to

turnover. Job stress is an intervening variable. Increases in











routinization result in greater job stress; job stress, in turn, leads

to higher turnover (Porter & Steers, 1973).

Numerous studies (Farris, 1971; Lawler, 1973; Porter & Steers,

1973) indicate that high job autonomy results in low turnover.

However, job satisfaction may be an intervening variable (Price &

Mueller, 1981).

Weitz (1956) demonstrated that role clarity played a significant

part in turnover. In a well controlled study, he demonstrated that

applicants who had detailed information about their jobs prior to

employment remained with the organization longer than those who had

little or no information about their jobs. Macedonia (1969) and

Youngberg (1963) drew the same conclusions from their studies.

Lyons (1971) added that the relationship between role clarity and

turnover may depend on individual tolerances for job ambiguity.

Tolerant individuals are not affected by unclear roles, whereas those

low in tolerance for job ambiguity withdraw at a higher rate when roles

are not well defined.

Attitudinal Variables

Turnover has also been assessed in terms of attitudinal variables

designed to measure workers' perceptions and feelings about their jobs

and organizations. These variables include job satisfaction,

organizational commitment, satisfaction of expectations, and existence

of perceived conflicting standards.

Research has generally supported the premise that a satisfied

worker will remain with the organization and attend work regularly.

In 1973, Porter and Steers reviewed 60 studies on employee turnover.

They found consistent evidence that job satisfaction represented an











important influence on turnover. The average correlation between these

variables was .25. Although the magnitude of the relationship was

small, it was consistent.

Vroom (1964) described the relationship between turnover and job

satisfaction in terms of his expectancy/valence theory. He theorized

that the decision to leave was a function of the difference in

strength between forces to remain and forces to leave. The force to

remain was reflected in job satisfaction levels. The force to leave

was influenced by the valence of outcomes individuals could not attain

unless they left their present position as well as by the expectancy

that these outcomes could be attained elsewhere.

Hulin's (1966) study is a notable example of research relating

job satisfaction and turnover. Using the JDI, he obtained baseline

job satisfaction measures on all female clerical workers who participated

in the study. Each subject who subsequently left the company during

the next 12 months was matched to two "stayers" along several

demographic variables. The leavers had significantly lower mean job

satisfaction scores than the stayers. Hulin concluded he could predict

leavers, at least on a group basis, using job satisfaction measures.

In 1968, Hulin repeated the study in the same company and obtained

similar results. However, scores on four of the five scales of the JDI

had risen and the turnover rate dropped more than 50%. He linked these

changes to new salary and promotion policies instituted by the company

after the first study.

Recent literature suggests that job satisfaction is indirectly

related to turnover. It may act as a precursor for other behaviors,











constructs, and processes that are more important predictors of

withdrawal (Parasuraman, 1982).

Organizational commitment, involvement, and job attachment have

been the subjects of other investigations on turnover. Porter,

Steers, Mowday, and Boulian (1974) defined organizational commitment

as "the strength of an individual's identification with and involvement

in a particular organization" (p. 604). They found it was significantly

and negatively related to turnover. Intention to remain is a component

of commitment. Porter et al. (1974), Steers (1977), and Marsh and

Mannari (1977) found that commitment had a higher negative correlation

to turnover than job satisfaction.

Koch and Steers (1978) stated that job attachment was significantly

and negatively related to turnover. They defined job attachment as

"an attitudinal response to one's job." While related to organizational

commitment, job attachment focuses more specifically on the job or

occupation rather than on the organization.

Porter and Steers (1973) explained the diverse views on turnover

by a theoretical framework based on met expectations. They proposed

that each individual brings a unique set of expectations for a job to

the employment situation. Individuals are less likely to quit if they

perceive their expectations are being met on the job. The decision to

remain is based on a process of balancing rewards (received or

potential) with expectations. The studies of Farr et al. (1973),

Wanous (1973), and Federico et al. (1976) supported this position.

Availability of Alternatives

Limited research has been conducted on the role of available

alternatives in the turnover process. Woodard (1975-1976) found a











negative relationship between unemployment and turnover and a position

relationship between available jobs and withdrawal rates. Locke

(1976) and Price (1977) also documented the relationship between

economic factors and turnover. Mobley et al. (1978) stated that the

expectancy of finding an acceptable alternative job was significantly

and positively correlated to intention to quit but not to actual

resigning. However, intention to quit was significantly and positively

related to turnover.

Turnover Models

Until recently, most of the studies on turnover have been limited

and have failed to provide a comprehensive view of the withdrawal

process. Mobley (1982), Mowday, Porter, and Steers (1982), and Steers

and Mowday (1981) have advocated the development of process-oriented

models of turnover based on multivariate analyses and longitudinal

research.

In 1958, March and Simon proposed a participation model. This

model serves as a basis for many current theoretical models of

turnover that specify the various processes underlying the decision

to withdraw. According to the model, the decision to leave an

organization depends on the individual's perception of the desirability

of movement and ease of movement. The level of job satisfaction

influences desirability to leave. Available alternatives, the current

economy, and the personal characteristics of the individual influence

ease of movement.

Price (1977) extended the March-Simon model by adding a variety

of variables to explain turnover. He suggested that five organizational

factors determined job satisfaction. These were pay, integration











(the degree to which an individual has close friends in the

organization), instrumental communication (degree to which information

about a job is transmitted by an organization to its members), formal

communications, and centralization (degree of autonomy). Job

satisfaction, in turn, combined with opportunity to leave to determine

actual turnover.

Mobley (1977) also presented a conceptual model of turnover,

focusing on the intermediate steps between job satisfaction and the

decision to leave. He stated that job dissatisfaction led to thinking

about quitting, intention to search, intention to stay or leave, and,

finally, to actual quitting. He also argued that intention to leave

was a more accurate predictor of actual turnover than job satisfaction.

In 1978, Mobley, Horner, and Hollingsworth evaluated Mobley's

model on 203 hospital employees. Their results supported the accuracy

of the model and the contention that the behavioral intention to leave

was a more important determinant of turnover than job satisfaction.

Behavioral intent correlated .49 to turnover, whereas dissatisfaction

correlated .21 with the decision to withdraw.

Earlier studies by Atchinson and Lefferts (1972), Kraut (1975),

and Waters, Roach, and Waters (1976) also indicated that behavioral

intentions to leave or remain with an organization account for more

variance in turnover than does job satisfaction. Job satisfaction,

however, was a salient precursor of behavioral intentions.

Miller, Katerberg, and Hulin (1979) evaluated the Mobley-Horner-

Hollingsworth (1978) model and proposed a more general model of the

turnover process. They collapsed the seven variables that Mobley and

his coworkers studied into four general constructs: career mobility











(age, tenure, probability of finding another job), job satisfaction,

withdrawal cognitions (intention to quit, intention to search), and

withdrawal behavior (turnover).

Mobley, Griffeth, Hand, and Meglino (1979) presented an expanded

turnover model focusing on behavioral intentions (intention to search,

intention to quit) as the immediate precursor of turnover. The model

also recognized the role of perceptions, expectations, values, and

available job alternatives as factors in the decision to leave an

organization.

In 1981, Steers and Mowday proposed a comprehensive, process-oriented

model of turnover. This model incorporated determinants of turnover

from earlier models and featured several new dimensions of the turnover

process. The new variables added to the model included job

expectations, employee performance level, ability to change the work

situation, and nonwork related factors that influenced the decision

to leave. Figure 1 represents this 13-stage model.

Price and Mueller (1981) described a causal model of turnover,

containing 13 variables or "determinants" of turnover. They posited

that routinization (repetitiveness of job), participation, instrumental

communication, integration, pay, distributive justice (rewards or

punishments are related to job inputs) and promotional opportunity

would influence turnover through the intervening variable, job

satisfaction. Job satisfaction, in turn, affected intent to stay.

Professionalism (degree of dedication to occupational standards of

performance), amount of general training, and kinship responsibility

(degree of an individual's obligations to relatives in the community)











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also influenced intent to stay. Intent to stay and opportunity

determine actual turnover.

Arnold and Feldman (1982) tested a multivariate model of turnover

on 654 accountants. The variables in their model were individual

demographic factors, tenure, cognitive/affective orientations to the

position (including multiple measures of job satisfaction and

organizational commitment), job security, perceived availability of

alternatives, intention to search for alternatives, intention to quit,

and actual turnover.

Results indicated that the most powerful model of turnover

behavior contained four significant predicator variables: tenure,

overall job satisfaction, perceived job security, and intention to

search for an alternative position. The results also suggested that

all variables did not influence turnover behavior through their impact

on intentions to change positions. Several variables explained

additional, unique variance in turnover behavior beyond that explained

by intentions. Turnover was more strongly related to intentions to

search for alternatives than to intentions to quit. Intentions to

search for alternatives were, in turn, highly predictable by a

combination of age, job satisfaction, and organizational commitment.

Using the Mobley et al. (1979) model, Youngblood, Mobley, and

Meglino (1983) analyzed turnover among Marine Corps enlistees. The

authors assessed the enlistees over a four-year period on the variables

posited in the model. These were behavioral intentions, expected

utility of the present role, expected utility of alternative roles, and

satisfaction. For subjects who left the Marines both early and later

in the enlistment period, behavioral intentions to continue were











lowest in the period immediately prior to leaving. For those who left

early, the perceived likelihood of finding an alternative job appeared

to influence the turnover decision. Results supported earlier research

that suggested behavioral intentions were a diagnostic precursor of

turnover.

Rusbult and Farrell (1983) also conducted a longitudinal study of

turnover using an investment model to predict turnover. They stated

that, in general, high rewards (high pay, autonomy, variety) and low

job costs (unexpected variations of workload, numerous deadlines,

inadequate resources, unfair promotion practices) generated higher

employee satisfaction. Job commitment increased with higher rewards,

lower costs, greater investment of resources (years of service,

nonvested benefits, work-related friendships), and less attractive

alternatives. The impact of rewards on job satisfaction and commitment

remained constant over time. However, the effects of job costs and

investments increased with time. Just prior to leaving, the job

commitment of leavers was best predicted by a combination of rewards,

costs, and alternatives.

In summary, numerous variables are involved in the decision to

withdraw. Some variables are organization-related (pay, promotion

policies), whereas others are related to the immediate work

environment (supervision, peer group relations). The content of the

job (nature of the job itself, autonomy, routinization, role clarity),

characteristics of workers (age, tenure, family responsibilities),

their attitudes about the job (overall job satisfaction, satisfaction

of expectations, organizational commitment), and economic factors

(availability of alternatives) influence the withdrawal decision.











Several researchers have developed models incorporating these variables

to explain and predict the turnover process.

Organizations and individuals have also recognized that matching

the right person to the right job influences job satisfaction,

productivity, and turnover. Research on person/job matching and work

behavior type will be reviewed in the next section.


Work Behavior Type

Research on work behavior type itself has been limited. Therefore,

this portion of the review will focus on research related to person/job

matching and work behavior type. It will include a definition of work

behavior, contributions of industrial and educational psychology to

person/job matching, theories of vocational choices, history of work

behavior types, and development of the Marcus Paul Placement Profile.

Definition

According to Neff (1969), adult work behavior is "the complex

product of a long series of learned and habitual styles of perceiving

and coping with demands of the environment" (p. 72). Coping behaviors

consolidate to form a particular "work style."

Industrial Psychology

Many researchers have claimed that work behavior is a distinctive

area of human behavior and, therefore, requires separate theories to

explain the behavior of people at work (Neff, 1969; Bass & Barrett,

1974). The field of industrial psychology evolved, specifically, to

address the issues, problems, and behaviors of people in the work

environment.

During World War I, industrial psychologists made major

contributions to testing. The Army needed a fast way to place large











numbers of men in optimal assignments. Industrial psychologists

responded by developing a series of psychological tests to match men

to jobs (Siegel & Lane, 1982).

Recently, spiraling labor costs, increased demands for productivity,

international competition, rising costs of turnover, and the

heterogeneity and educational level of the work force have forced

many organizations to examine their personnel selection and placement

procedures (Cascio & Awad, 1981).

Industrial psychologists have responded to these needs by

developing new methods to improve selection and placement programs.

The methods focus on improving the predictive powers of managers in

selecting the individual who can satisfactorily perform a job or work

activity.

Traditionally, organizations relied heavily on results from

intelligence, personality, interest, aptitude, or achievement tests

in the selection process. However, the advent of civil rights

legislation and equal employment opportunity guidelines frightened

many organizations into abandoning testing completely (Luthans, 1981).

Interviewing has also been a traditional selection procedure.

Many consider it an art rather than a science (Luthans, 1981).

Evidence suggests that interviews are less valid than tests in

selection for the following reasons (Porter, Lawler, & Hackman, 1975):

1. The same material is not covered in each interview.

2. Different interviewers weigh the same information differently.

3. Except for intelligence or mental ability, interviewers
cannot assess traits accurately.

4. Interviewers make selection decisions early in the interview,
before the candidate has presented all information.











5. Interviewers give more weight to negative than to favorable
information.

Selection problems inherent in testing and interviewing have led

organizations to assessment centers for assistance in hiring and

promoting people. The assessment center is a holistic approach to

selection and uses multiple assessment techniques and multiple

assessors. It also demonstrates high validity and selection fairness

for men, women, minorities, and nonminorities. The center method has

been successful and cost effective for organizations (Cascio & Awad,

1981).

Assessment techniques include in-basket exercises, leaderless

group discussions, paper and pencil ability tests, simulations,

personality questionnaires, projective tests, and background interviews.

Assessors are trained to standardize interpretations of candidates'

behaviors and go through the training as participants before rating

others. Selection decisions are derived from the pooled judgments of

all assessors.

The dimensions, attributes, characteristics, or qualities that

are evaluated are derived from an analysis of relevant job behaviors.

McCormick and his associates (1964) analyzed characteristics common to

a variety of jobs in terms of worker activities (job content) and

prerequisites (attributes). They developed the Position Analysis

Questionnaire (PAQ) to rate job elements for different jobs. The PAQ

consists of 194 job elements that were reduced to 30 job dimensions

which, in turn, were subsumed under six major activity categories:

1. Information input (where and how the worker gets the

information used for the job).











2. Mental processes (decision making and information processing).

3. Output (the physical activities performed by the worker and

tools or devices used).

4. Interpersonal activities (communicating instructions,

supervising others).

5. Job context in which the work is performed (stresses, hazards).

6. Miscellaneous aspect of the work activities (work schedule,

clothing worn).

Job analysis methods and new assessment techniques are an attempt

to bring the individual, job, and organization together for a

potentially rewarding relationship. When the matching process is

successful, it is mutually beneficial to the individual, organization,

and society.

Educational Psychology

Although industrial psychologists focus on people who are already

working and educational psychologists concentrate on people in school,

their interests often overlap. Educational psychologists, however,

place more emphasis on career development and planning, occupational

choice, and career counseling than their industrial counterparts.

The need and demand for career development and planning have never

been greater than they are today. Employees realize that their careers

impact not only on the quality of their work life but on the quality of

life in general. Organizations recognize the effect of the quality of

life on employee job satisfaction, performance, and turnover (Luthans,

1981).

Career decision making has also become complex. Social and legal

changes have opened up a range of career alternatives and opportunities











for both men and women. Technology has created a rapid pace of change

in the labor market. New jobs emerge as others become obsolete.

Medical advances have expanded life expectancy. Instead of one career

decision, people must make multiple career decisions in a lifetime.

Theories of Vocational Development

Several authors have proposed theories of vocational development

and occupational choice. Ginzberg, Ginsburg, Axelrod, and Herma (1951)

argued that occupational choice was an irreversible process. It took

place over 8 to 10 years and passed through a number of well-marked

developmental stages. Early decisions reduced the number of successive

choices and available options.

Occupational decision making occurs in three stages. The fantasy

stage occurs between ages 10 and 12. Children at this stage have no

conception of their capabilities, occupational limitations, or

opportunities. During the tentative stage, adolescents think about

occupations in terms of their abilities and interests. The realistic

stage is characteristic of late adolescence and early adulthood when

individuals become more concerned with realistic opportunities and the

limitations of the available work environment. The final occupational

choice is a compromise between personal preferences (interests,

abilities) and the constraints of the work world.

In 1971, Ginsberg revised his earlier position and claimed that

occupational choice was "open-ended" throughout a person's life. Choice

was influenced by work experiences, changes in values, physiological

changes, marital relationships, financial status shifts, and loss or

change in job.











Super's (1953) theory of vocational development was based on the

premise that people selected occupations consistent with their

self-concept. The self-concept developed in the individual over time

and passed through many stages of formation, differentiation, and

articulation. Using a longitudinal research design, Super attempted

to assess the components of the self-concept at different points in

time and to correlate these components to the career patterns that

emerged.

Using psychoanalytic theory, Roe (1956) hypothesized that career

development and occupational identity formed during early childhood.

The quality of the parent-child relationship had a strong influence on

the development process. She devised a typological classification of

occupations according to the amount of involvement with people or

objects demanded by the occupation. She also classified types of early

parent-child relationships. Positive parent-child relationships

predisposed the child to enter person-oriented occupations, whereas a

negative family atmosphere led to a nonperson-oriented occupation.

In 1964, Roe revised her original hypothesis and said vocational

development .was more complex and vocational behaviors developed

independently of early childhood experiences.

Holland (1959) developed a typology theory of career choice.

His theory is based on the assumption that most people in our culture

can be classified into one of six types: realistic, investigative,

artistic, social, enterprising, or conventional. He also identified

six types of environments: realistic, investigative, artistic, social,

enterprising, and conventional. Individuals search for the environment

that will allow them to exercise their abilities and values and











assume acceptable roles. People's behaviors are determined by the

interaction between their personalities and the characteristics of

the immediate environment.

Holland also assumed that at the time people selected a career,

they were the product of heredity and a variety of environmental

factors, including peers, parents, other significant adults, social

class, culture, and the physical environment. From this background,

the individual developed a typology or hierarchy of orientations for

coping with environmental tasks. When people make career choices,

they are searching for those environments that are congruent with their

personal orientations. Holland (1959) devised the Vocational Preference

Inventory to estimate personality patterns.

Tiedman (1961), like Super (1951), was interested in the

development of the vocational self-concept. He based his work on

Erickson's (1959) theory of personality development and psycho-social

crisis. Tiedman related vocational development to the process of

decision making and adjustment from a period of exploration to final

integration.

Recently, it has become popular to view career and occupational

development as a major component of adult life stages (Levinson, 1978;

Sheehy, 1977). Hall (1976) synthesized these adult life-stage theories

into an overall model of career development. This was a psychological

success-based model that integrated concepts of the self with individual

task behavior and job attitudes. Hall stated that people developed in

their careers through a cyclical process of goal setting, performance,

feelings of success, favorable job attitudes, and goal resetting.











During the exploration stage, the young employee searched for an

identity and tried out several jobs and roles. In the second stage,

the employee settled down and grew in a career role. The third stage

of maintenance was where the employee's productivity reached a

plateau. At this time, the individual might assume a mentor role out

of a need for generativity (the concern to leave something for the

next generation). The individual could also stagnate, decline, or have

a growth spurt. The final stage was decline. The employee searched

for integrity (feelings of satisfaction with life choices and overall

career).

Although there are many theories of career choice, they all

reflect people's efforts to obtain a proper fit between themselves and

their jobs. The closer the match, the greater the rewards for both

employees and organizations.

Organizations are slowly becoming aware of their role in career

planning and development to improve the effectiveness of their

operations. Organizations are beginning to provide employees with

workshops, counseling services, and innovative programs for special

career needs (i.e. flex-time) as part of human resource management

programs (Luthans, 1981).

When individuals obtain more information about themselves, they

can make more accurate career decisions and find the right job. With

this premise in mind, Bauch (1981) developed the Marcus Paul Placement

Profile (MPPP). This instrument for measuring work behavior types had

its foundations in trait and type theory.











History of Work Behavior Types

William Marston's (1927) work formed the basis for current

theories of work behavior traits and types. He proposed a model of

behavior based on four primary emotions: Dominance, Compliance,

Inducement, and Submission. A primary emotion was "an emotion which

contained the maximal amount of alliance, antagonism, superiority of

strength of the motor self in respect to the motor stimulus"

(Marston, 1928, p. 106).

This means that Marston designated a primary emotion according

to people's reactions in a favorable environment (alliance) or

unfavorable environment (antagonism). An interaction with the

environment could be active (superior strength) or passive (inferior

strength). Individuals need a balance between active and passive

interactions with the environment. The intensity of an emotion or

subsequent reaction to a stimulus, depended on the individual's past

experience.

Marston described each emotion in physiological and behavioral

terms. He defined Dominance as a "central release of additional motor

energy directed toward dominating obstacles to a reaction already in

progress (Marston, 1927, p. 349). It consists of "an increase of the

self to overcome an opponent,. .a feeling of an outrush of energy to

remove opposition" (Marston, 1928, p. 140).

Dominance is a fundamental behavior, important for survival of

early humans. It is the primary life-propelling emotion of human beings

during the first 3 years of life (Marston, 1927). It may be a desirable

emotion when competition and aggressiveness are appropriate behaviors.

However, dominance may also act as a negative emotion when it is out of











control or is expressed in the wrong environment. Dominant people in

authority positions may create dissatisfaction and hostility among

subordinates.

Compliance is also a basic emotional response and refers to

"control (but not inhibition) of tonic motor discharge reinforcement

by a phasic reflex? (Marston, 1927, p. 350). It may also mean taking

an interest in the stimuli and "is not to be confused with inaction

or inhibition" (p. 351). Marston (1928) subsequently defined Compliance

as a

decrease of the motor self to let an opponent move the
organism as if by will; either passively, by making the
self give up some dominant activity, or some anti-dominant
way. It is a feeling of acceptance of an object of force
as inevitably just what it is, followed by self-yielding
sufficient to bring about harmonious readjustment of self
to object. (p. 128)

Compliant behavior results from recognizing or believing that

outside forces are imminently stronger. It may occur when individuals

are afraid, startled, experience sudden change, or voluntarily

surrender. Compliance may also result from an intense enduring or

repeated environment stimulus. Compliance may be a pleasant experience

when it allows individuals to be one with God or nature, to feel empathy,

or to be an effective team member.

Dominance and Compliance form one axis of Marston's two-axis

model. Figure 2 illustrates this model. Although individuals display

these emotions in varying degrees at various times, there is always an

effort to maintain a balance between the extremes of each axis.

Differences in behavior among individuals relate to the differences in

the point of balance on the axis.





























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Submission, according to Marston (1927) is a "voluntary yielding

to whatever stimuli may be imposed. .It does not seem to overwhelm,

or dominate the subject by force, but rather brings about a spontaneous

lessening of the subject's resistance to it until the subject has

become less strong than the stimulus" (pp. 356-357). In other words,

Submission is a willingness or mutual feeling of warmth between the

person submitting and the person submitted to (Marston, 1928).

Submission is usually a pleasant emotion and may take the form of

consideration, service to others, selflessness, accommodation, and

generosity.

The fourth primary emotion described by Marston (1927) was

Inducement. It was the "active solicitation of attention and

stimulation. .calculated to reinforce submission reaction in order

to induce further submission from another individual" (p. 539).

Inducement is also a "central release of additional motor energy

directed toward drawing forth or inducing submission responses from

another individual" (p. 361).

In 1928, Marston's definition of Inducement stated that

Inducement consists of an increase of self, and making of
the self more completely allied with the stimulus person,
for the purpose of establishing control over that person's
behavior. (p. 273)

Individuals who gain voluntary submission from others exhibit

Inducement behavior. This behavior may take the form of persuasion,

personal charm, friendliness, seduction, or subtle manipulation.

Commercial advertising is a prime example of inducement behavior in


our culture.











Submission and Inducement form the second axis of Marston's model.

They are also opposite ends of a continuum, separated by intensity of

response (either active or passive) and by the orientation of the

individual (either outward or inward). Inducement requests Submission,

whereas Dominance demands Compliance. Dominance is antagonistic toward

its subject and inducement is allied with its subject.

Marston divides the two axes of the model horizontally.

Dominance and Inducement form the upper, active component of the model

and Submission and Compliance form the lower, passive component. The

dimensions represent tendencies, not all inclusive labels. Individuals

exhibit degrees of all types of behaviors. Behavior traits, however,

tend to cluster more around one particular dimension.

Marston identified clusters of traits for each primary emotion.

Figure 3 lists these traits. Allport and Odbert (1936) and Geier

(1980) used factor analyses to confirm these findings. Geier (1980)

obtained an overall correlation of, at least, R=.60 between the

suggested traits and the emotions.

Building on Marston's work, Geier (1967) attempted to formulate

a trait approach to leadership. He found that subjects used trait

terminology to describe their own behavior traits as well as to describe

the behavior and leadership style of others. He also discovered that

subjects reported themselves in terms of behaviors they least exhibited.

These findings were the basis for the Marcus Paul Placement Profile

that discerned work behavior types from descriptions of traits which

were most and least like the subject. Geier also developed an updated

list of cluster traits (Figure 4).


































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Geier clarified Marston's terminology and redefined Dominance

as "active positive movement in an antagonistic environment"

(Geier, 1979, p. 2). Compliance was "a cautious tentative response

designated to reduce antagonistic factors in an unfavorable environment"

(p. 2). Submission was defined as "passive aggressiveness in a

favorable environment" (p. 2) and Inducement was "active positive

movement in a favorable environment" (p. 2).

He also added the idea to the two-axis model that people with

traits centered around the Dominance or Inducement dimension were

process-oriented and wanted to shape the environment according to their

own particular viewpoint. Individuals with traits centered around the

Submission or Compliance dimensions were product-oriented and focused

on the how and why of things and events.

Marcus Paul Placement Profile

Bauch (1981) used Marston's model and Geier's research to develop

the Marcus Paul Placement Profile. This instrument was designed to'

identify work behavior types in order to match people to jobs. In the

educational setting, it could provide a basis for counseling, career

development, and selection. Organizations could use it for recruiting,

job placement, training, and team building.

The intent of the MPPP was to increase understanding of work

behaviors. Therefore, Bauch modified some of Marston's and Geier's

terminology to remove any judgmental overtones from these terms. He

replaced words with negative connotations with positive or neutral

terms. In place of Marston's categories of Dominance, Inducement,

Submission, and Compliance or Geier's Dominance, Influence, Steadiness,











and Compliance, Bauch described work behavior types as Energizer,

Inducer, Concentrator, and Producer.

Bauch (1981) defined these work types as follows:

1. Energizer type workers actively engaged in getting
results. They are assertive, impatient with detail,
and desire direct answers and actions from associates.
They are also creative and have many ideas for improving
the work process (p. 16).

2. Inducer type workers involve others as they pursue
objectives. They are sensitive to the needs of their
associates and have optimistic attitudes as they
influence others. They are good at using group processes
to accomplish goals, being able to clarify ideas for
themselves and others. They place more emphasis on
people and interpersonal relations than on the
organization (p. 16).

3. The Concentrator types can apply their skills in orderly
ways resisting distractions. They are steady workers,
and are loyal to the organization, showing great patience.
They are systematic, effective, and help maintain
moderation in these situations (p. 17).

4. Producers strive for quality as they carefully follow
procedures, guidelines, or standards. They can support
their decisions and actions with irrefutable documentation.
Producers expect their directions but they can be relied
on to meet their deadlines, follow orders and carry out
their assignments with precision (p. 17).

Figure 5 presents the MPPP work behavior traits characteristic of

each work behavior type. These traits are used in the MPPP in the form

of 24 sets of forced choice items. In each set, subjects indicate

which term is most descriptive of their work behavior and the term which

least represents their work behavior.

A computer analysis of the responses generates the individual's

work behavior profile in terms of one of the four major work behavior

types. It also provides a more detailed description of the individual's

strengths and tendencies by identifying one of 18 possible types.

These descriptions reflect varying intensities of work behavior along


























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the four major dimensions and the complex relationship between the

dimensions. They also differentiate among individuals in the same

category. In general, the profile describes the individual's style of

interacting with others, ability to complete tasks, leadership potential,

need for supervision, and preference for working in a technical or

data-oriented position or in one that is people-oriented (Bauch, 1981).

Approximately 20% of the population are Energizers and about 20%

are Inducers. Concentrators and Producers make up the remaining 60%.

Although certain job descriptions or roles show preference for one

specific type, most organizations work best with a combination of all

types.

Using the MPPP, Glenn (1982) studied the relationship among work

behavior type, personality function, job satisfaction, and effectiveness

of vocational education administrators. She found that some work

behavior types were significantly related to some personality functions

as measured by the Myers-Briggs Type Indicator (MBTI). Although there

was no significant relationship between overall job satisfaction and

work behavior type, there was a significant relationship between work

behavior type and specific areas of job satisfaction.

Energizers were satisfied by opportunities for promotion, volume

of work, unanticipated job tasks,and recognition for accomplishments.

Inducers were interested in the physical working conditions, volume of

work, and section/division meetings. Concentrators indicated that

opportunity for job promotion, volume of work, unanticipated job tasks,

amount of supervision, and recognition for accomplishments were

important to them. Producers listed physical working conditions,











communication with clients, and section/division meetings as important

for their job satisfaction.

In summary, although there has been an urgent need to effectively

match people to jobs, little research has been done on work behavior

types. Many fields of study form the basis for an understanding and

application of work behavior types. Industrial psychology has

contributed selection methods and job analysis. Educational psychology

has provided theories of vocational development and choice. Trait and

type theories have provided a foundation for an instrument to measure

work behavior type. Work behavior types may affect employee job

satisfaction and turnover.


Job Satisfaction, Attrition, Work Behavior Type of Medical Technologists

This section will present an overview of literature on job

satisfaction, attrition, career development, and work behavior type

among medical technologists.

Since 1970, several authors have published studies on job

satisfaction among laboratory personnel. Gerstenfeld and Whitt (1970)

examined goal priorities of medical technologists. Medical technologists

listed good working conditions as the number one priority, followed by

challenging work and higher earnings. Supervision, administrative

policies, schedules, available equipment, interaction among personnel,

and the quality of work influenced good working conditions.

In a study of senior medical technology students, Karni and Husted

(1970) reported that as students progressed through their rotations,

they became more dissatisfied and discouraged. Students perceived a

lack of recognition accorded to medical technologists by other health











professionals and the general public. Students also perceived a lack

of identity for the profession of medical technology.

In 1971, Jeswald conducted an extensive study of job satisfaction

among medical technologists. Using Maslow's theory of needs hierarchy,

he found that medical technologists considered security and self-

actualization needs as primary factors for job satisfaction, whereas the

need for autonomy was least important. Jeswald's results also indicated

that self-actualization and esteem were the least satisfied needs

across all categories of laboratory personnel. Clinical practitioners

consistently reported they felt lack of appreciation and recognition

for their work.

Showery's (1976) survey of 300 medical technologists revealed that

only 30.8% of those surveyed with more than 5 years experience

indicated they would choose medical technology again if given the

choice and 49.5% stated they were uncertain. The major reason offered

by 83.5% of the subjects was lack of respect and recognition for

laboratorians by other hospital personnel.

French and Rezler (1976) reported that clinical practitioners

were less satisfied with their work, co-workers, and opportunities for

advancement than medical technologists who were educators or

administrators. All technologists were least satisfied with pay and

promotion. Poor communication was a major source of frustration and

dissatisfaction in all work settings. Most technologists found their

work moderately stressful.

Matteson, Ivancewich and McMahon (1977) examined the relationship

among medical technologists' needs, organizational practices, and job

satisfaction. Their results suggested that job satisfaction was a











function of how well a job or organization met the individual's needs

which, in turn, was a function of organizational practices or

characteristics. Like Jeswald (1971), they found that attainment of

higher order needs was strongly associated with job satisfaction.

However, they were also the least satisfied needs. All subjects listed

self-actualization as the least satisfied need. Security was the most

satisfied need. The most important organizational practice related to

satisfaction was coordination, the degree to which technologists were

given necessary information. Yet, it was also the practice technologists

found most dissatisfying.

While factors influencing job satisfaction were the same for

administrative and nonadministrative technologists, administrators

experienced higher levels of self-actualization, esteem, and autonomy.

Satisfaction levels were also lowest in small hospitals and may be

related to availability of modern technology in these facilities.

Love (1977) found that organizational stratification was related

to job satisfaction. He defined stratification as "the degree of an

organization's dispersion of power, prestige, monetary compensation,

rewards, and other social resources to its members" (p. 1136). Of the

10 stratification-satisfaction relationships studied, the most

significant was the inverse relationship between both social distance

and authority distinction and satisfaction with supervision. Social

distance was comparable to the dimension of the leadership behavior,

consideration, discussed earlier in the job satisfaction text.

Authority distinction is comparable to authoritarian leadership style.

When social distance and authority distinction are high in an

organization, there is less social interaction and support from











supervisors and fewer opportunities for autonomy. There was a

significant positive relationship between authority distinction and

satisfaction with work. The author concluded medical technologists

preferred a cordial, supportive, well-structured work setting that

permitted them an opportunity to participate in making decisions related

to the goals, methods, and activities of their department.

The work of McMahan, Ivancewich, and Matteson (1977) confirmed

the findings of several other authors. Comparing administrative to

nonadministrative medical technologists, males to females, and hospital

to nonhospital workers, they examined the relationship of organizational

climate and job satisfaction. The organizational climate dimensions

of thrust (refers to management's desire to motivate employees to

accomplish the job through task oriented behavior), consideration and

esprit most significantly related to need satisfaction among all

categories of medical technologists.

Relating their interpersonal values to job satisfaction, Oliver

(1978) found that medical technologists who valued independence and

recognition were the least satisfied with their jobs. Those who valued

benevolence (doing things for others) and conformity were more

satisfied with their work. These findings are consistent with those of

Love (1977), Karniand Husted (1970), Jeswald (1971), Showery (1976),

and Matteson et al. (1977).

Harting and Oliver (1978) investigated the perceptions of

bench-level and supervisory medical technologists regarding their work

role and working conditions. The work role included the job itself,

rewards, helping relationships, interpersonal relations, and recognition.

Results were comparable to those found in earlier studies. All medical











technologists were least satisfied with recognition and rewards. They

perceived few opportunities for advancement and little recognition or

prestige associated with their work. Supervisors were generally more

satisfied with their jobs than bench-level technologists.

Using the JDI, Broski and Cook (1978) determined job satisfaction

levels for medical dietitians, physical therapists, occupational

therapists, and medical technologists. All groups had significantly

lower mean scores compared to national norms. However, dietitians

reported the lowest satisfaction scores on all job facets except pay.

Medical technologists followed dietitians with regard to overall

satisfaction and were the most dissatisfied group on the pay subscale.

All groups were equally dissatisfied with promotion opportunities.

In 1982, Broski, Manuselis, and Noga conducted a similar study

and found that medical technologists had become the most dissatisfied

group on four of the five subscales of the JDI. They were more

satisfied than dietitians or occupational therapists on the supervision

subscale and as equally satisfied as physical therapists. They also

scored lower than the national sample on these same job facets. Many

technologists provided supplementary comments that indicated they saw

little opportunity for advancement, received inadequate pay to support

a family, were overprepared for the tasks they performed, had limited

authority, experienced high job stress,and perceived lack of respect

and recognition from other health professionals.

Spencer (1982) attempted to determine the relationship between a

sense of accomplishment on the job and career commitment and the

relationship between sense of accomplishment and job satisfaction. His











findings also indicated intrinsic factors were important for job

satisfaction and career commitment of medical technologists.

A recent study by Myers et al. (1982) related job dissatisfaction

in medical technology to the acquisition of unrealistic expectations

during clinical training. They claimed these expectations were later

translated into unmet professional role expectations and were

concentrated in the areas dealing with lack of upward mobility, respect

from other health practitioners, poor pay, and job stress.

Rogers (1983) examined the problem of job stress as it related to

job satisfaction in the hospital laboratory setting. She demonstrated

that stress was significantly related to job dissatisfaction, with 78%

of the highly stressed technologists in the sample also reporting high

levels of job dissatisfaction. Stress stemmed from job pressure

(workload and time pressure), job scope (having authority commensurate

with responsibilities), and rapport with management.

Recent studies into the causes of job dissatisfaction among medical

technologists have also addressed the related issue of the rising

attrition rates among this group of laboratory workers. Medical

technologists are not merely dissatisfied with their jobs, they are

disenchanted with the profession of medical technology and are defecting

to other professions.

Hajek and Blumberg (1982) surveyed 83 former medical technologists

to determine their reasons for leaving medical technology. Although

medical technology is dominated by women, the investigators found that

73% of the sample left the profession for nondomestic reasons. Job

related factors, particularly those related to self-actualization, were

cited as the principal causes of attrition. Participants expressed











disappointment and frustration with their work experiences in medical

technology. While they had been highly trained for careers as

responsible members of the health care team, they found themselves in

"jobs," unrecognized and disregarded by other health care professionals

as well as by the public. In addition, these jobs became routine,

lacked challenge, were stressful, and provided little opportunity for

advancement. In light of these results, the authors recommended

re-evaluation of the medical technologist's role in health care, and

creation of career ladders to permit advancement within the profession.

Based on the work of Hajek and Blumberg (1982), Irwin (1983)

investigated the causes of dissatisfaction and attrition among medical

technologists in New Jersey and obtained comparable results. Of the 115

participants, 66 (57%) indicated they would definitely leave medical

technology within 5 years and 10% were undecided. The decision to

continue in the field or go elsewhere was primarily related to

self-actualization and esteem factors. Technologists who planned to

leave felt overtrained and frustrated with their jobs because those with

less training were performing the same tasks. They also found the work

monotonous and had few opportunities to use their knowledge of laboratory

medicine. In terms of esteem factors, they felt that they were invisible

members of the health care team, received too little pay and recognition

for their training and responsibilities, and that there was little

prestige associated with being a medical technologist. Increased

opportunities for career advancement and more attractive financial

rewards were the major incentives cited by technologists that might

encourage them to remain in the profession.











Inadequate career planning by students and incomplete selection

criteria for program admission may, later, contribute to technologists'

job dissatisfaction and turnover. Students may select medical

technology as a career based on misinformation as to what the occupation

actually involves and requires. Educators may select students into

programs on the basis of criteria that do not relate to on-the-job

performance.

In 1975, Holstrom surveyed freshman medical technology majors

about the factors influencing them to select medical technology as a

career. Students cited the availability of jobs, high earnings, a

chance for career advancement, and prestige of the occupation as major

reasons for choosing medical technology. Yet, earlier Jeswald (1971)

and Karni and Husted (1970) reported that clinical practitioners felt

medical technologists were not held in esteem and did not have

opportunities for career advancement.

Zufall (1976) determined that the majority of medical technology

students made a career choice based on information they had obtained

from visiting hospital programs, talking to students enrolled in

programs, writing to national sources, and visiting an employment site.

Parents, friends, and health professionals were the most influential

persons involved in student career decisions while counselors played a

minor role.

Youse and Clark (1977) demonstrated that medical technology students

had little understanding of the qualities and interests needed for

medical technology and did not have accurate perceptions of what the

profession entailed. These investigators developed a vocational

competency test to find out how much entering students knew about











medical technology and how much their knowledge increased over time.

After six months in clinical rotations, graduating seniors correctly

answered only 71% of the general information questions about medical

technology. Juniors answered 59% accurately and entering students

had an accurate response rate of 42%. In response to a question about

the most valuable trait for a medical technologist, 20% of the seniors,

and 34% of the juniors responded, "Speed." Other responses were

honesty, creativity, and high I.Q. Many students (12%) were unaware

that technologists worked weekends and holidays in hospital laboratories.

A majority of all levels of students stated they chose medical

technology because they enjoyed science courses. They also cited job

security as a major factor in selection.

Results suggested that selection of students earlier than the

junior year could contribute to a high attrition rate and to a

population of students poorly matched to the profession. At this stage

students have little awareness of the major responsibilities of medical

technology.

Gleich (1978) also demonstrated that preclinical medical technology

students did not make a career choice based on knowledge of the work or

the profession. Friends, family, and relatives were the leading sources

of information about medical technology. Only 14% had worked as lab

aides or clerks and only 2% had spoken to a practicing technologist

about the field. Students ranked the type of work involved in medical

technology as the leading factor influencing their career choice.

Choosing students for positions in medical technology programs may

also be based on inadequate information about the student. During the

1970s, medical technology programs were popular among undergraduates.











At a time when graduates of other programs had limited employment

opportunities, medical technology students were assured a job after

graduation. As a result, medical technology programs had more applicants

than available slots. Competition for slots was keen and criteria were

established to select students who would most likely succeed in the

program and thus graduate. Criteria included gradepoint average (GPA),

key course grades, aptitude test scores, work records, volunteer

service, recommendations, and personal interviews (Love, Holter & Krall,

1982).

Although research indicates that these selection criteria are

valid measures for predicting academic success in the program (Eberfield

& Love, 1970; Love et al., 1982; Lundgren, 1968), they do not adequately

predict clinical or professional performance (Duntman, Anderson, &

Barry, 1966). With the decrease in the numbers of applicants for medical

technology programs and the high attrition rate among clinical

practitioners, new selection criteria may be in order. Students who

have lower academic credentials may demonstrate other essential traits

for success in medical technology.

Information about the work behavior traits of satisfied clinical

practitioners would be useful in career planning, job counseling, and

student placement. Although research on the work behavior types of

medical technologists is nonexistent, the existing literature suggests

that certain traits and types are related to success and satisfaction

in this occupation.

French and Rezler (1976) found a higher proportion of sensing

people among medical technologists who were in clinical practice but a

higher percentage of intuitive types among educators and administrators.











In an earlier study, Rezler and French (1975) found more intuitive,

feeling, and perceiving types among medical technology students. The

authors hypothesized these types of students left medical technology

before entering practice or shortly thereafter because they were

disappointed with the actual work situation.

Williams (1975) stated that "the prospective medical technology

student should possess manual and finger dexterity, must be able to

accept responsibility, and have intellectual integrity, a high degree

of persistence, and a high capacity for patient, thorough effort"

(p. 36). She added they should also like people.

Oliver (1978) determined that medical technologists who valued

independence and recognition were least satisfied with their jobs.

Those interested in doing things for others and valuing conformity were

most satisfied.

In conclusion, medical technologists, like other workers, bring

expectations, needs, values, goals, skills, abilities, interests,

motivation, and personality traits to the work setting. These factors

determine the work behavior type of the individual technologist. When

the work behavior type is consistent with the demands and requirements

of the job, the individual is more likely to experience job satisfaction

and remain in the profession. Students, educators, and employers need

more information on work behavior types to make adequate career,

selection, and placement decisions.

















CHAPTER III
DESIGN AND METHODOLOGY


This chapter includes the design and methodology of the study.

In it are the research design, population, description, data

collection, instrumentation, and data analysis procedures.


Design

The investigator used a descriptive research design to investigate

job satisfaction, work behavior type, attrition, and demographic

characteristics of practicing and former medical technologists in the

state of Florida. Specifically, she sought answers to the following

questions:

1. What are the work behavior types of medical technologists
in Florida?

2. Does a relationship exist between the work behavior type
of the technologist and overall job satisfaction?

3. Does a relationship exist between work behavior type and
specific aspects of job satisfaction?

4. Do participants' work behavior types relate to attrition
or the intention to leave medical technology?

5. Do medical technologists working in hospital laboratories
differ from those working in nonhospital laboratories or
other fields in overall job satisfaction?

6. Do medical technologists working in hospital laboratories
differ on specific aspects of job satisfaction from those
working in nonhospital laboratories or other fields?

7. Does a relationship exist between the sex of the participant
and job satisfaction?











8. Does a relationship exist between the sex of the participant
and attrition or the intention to leave medical technology?

9. Can some combination of demographic variables, work
behavior type, and job satisfaction predict attrition
among medical technologists.


Population

The sample population consisted of two groups of medical

technologists. Practicing medical technologists employed in various

laboratory settings (hospitals, clinics, private laboratories, blood

banks, reference laboratories) located in a Florida community comprised

the first group. These were bench-level technologists, primarily

responsible for performing the technical work in the laboratory. All

technologists holding a bachelor's degree were invited to participate.

Supervisory technologists, educators, and medical technicians were

excluded to assure homogeneity of the sample.

The second group included former medical technologists, currently

employed in occupations other than medical technology. The investigator

selected these participants from business contacts, former employees,

and lists of University of Florida medical technology graduates from

the past 5 years who lived in the community.


Data Collection

The researchers mailed a letter to the chief technologist, or

administrator at each facility (see Appendix A). The letter contained

an explanation of the purpose of the project and a request for

participation by the staff of the facility. Willingness to participate

in the study was determined by a followup telephone call. At that time,

the researcher also ascertained the number of technologists employed at











the facility and made an appointment to deliver questionnaires to a

contact person. The contact person served as a coordinator to

distribute and collect the materials. The investigator returned on a

specified date to collect the completed packets. When it was more

convenient to mail materials to a participating facility, the

researcher enclosed a stamped, addressed envelope with a request that

subjects return completed packets by a specified date. She telephoned

nonrespondents after 7 days.

The investigator gave volunteers a packet of instruments (see

Appendix B) to complete and a cover letter (see Appendix C) explaining

the purpose and importance of the study. Instruments were numerically

coded to eliminate personal identification but to permit correlation

of responses. Participants were instructed, however, to put their

names on the MPPP if they wanted an assessment of their work behavior

type.

The investigator sent a copy of the instruments and a cover letter

(see Appendix D) to former medical technologists. She instructed them

to return the completed questionnaires in the enclosed stamped,

addressed envelope by December 15, 1983. After 7 days, she telephoned

nonrespondents or individuals who did not complete all instruments.

Of the seven hospitals and nine nonhospital laboratories the

investigator contacted, six hospitals and eight nonhospital facilities

agreed to participate. Table 1 shows the number of questionnaires

distributed to each group of technologists. Hospitals are listed

individually. Responses for nonhospital technologists are pooled

because each facility only employed up to three technologists. The











Table 1. Response rate on questionnaire by group of respondents.


No. No. Useable
Questionnaires Questionnaires Percent
Group Distributed Returned Returned


Hospital
Technologists
1 13 8 62
2 20 10 50
3 48 12 25
4 28 26 93
5 15 14 93
6 10 10 100
TOTAL 134 80 60

Nonhospital
Technologists 20 12 60

Former
Technologists 29 19 66

GRAND
TOTAL 183 111 61



table also contains the number of useable questionnaires returned by

each group of technologists and the percentage returned.

The percentage of questionnaires returned by hospital respondents

ranged from 25% to 100% for an overall response of 60%. Nonhospital

respondents returned 60% of the questionnaires and former medical

technologists contacted returned 66% of the questionnaires. Nonuseable

packets returned from all groups totaled 19. These respondents either

failed to meet the education requirements for inclusion in the study or

did not complete all instruments. Efforts to retrieve missing data were

unsuccessful. The final population consisted of 111 technologists--

80 from hospitals, 12 from nonhospital facilities, and 19 former

technologists. The overall response rate was 61%.










Instrumentation

Job Descriptive Index

Job satisfaction was assessed by the Job Description Index (JDI)

developed by Smith, Kendall, and Hulin (1969). The JDI is the most

reliable and valid measure of job satisfaction currently available

(Bass & Barrett, 1974; Crites, 1969; Gruneberg, 1979; Vroom, 1964).

The JDI contains 72 items measuring satisfaction with five facets of

the job: the work itself (18 items), supervision (18 items), pay

(9 items), promotion (9 items), and co-workers (18 items). Smith and

co-workers derived these items by performing factor analyses on

numerous job satisfaction inventories available at the time of their

study.

The items are descriptive adjectives or short phrases arranged in

a checklist form. The 72 items are approximately half favorable and

half unfavorable items. The JDI does not directly ask respondents how

satisfied they are with their work. The instrument contains a provision

for respondents to describe their work. However, in describing their

jobs, they provide information that may be used to infer satisfaction.

Some items include evaluative words and others describe objective

features of the job.

Respondents mark a "Y" for yes next to the item if it describes

their job, "N" for no if it does not describe their job, and "?" if they

are undecided. Smith et al. selected the checklist format with short

descriptive phrases to permit administration of the questionnaire across

a variety of educational levels and jobs.

Values are assigned to responses and scores are derived from a

scoring key by adding the values for items in each subscale. A yes











response to a negative item and a no response to a positive item

receive a zero. A yes response to a positive item and a no response

to a negative item receive three points. An indecision receives one

point. Smith et al. found that the "?" response was more indicative

of dissatisfaction than satisfaction and assigned the "?" response a

weight of one instead of two. The maximum score for each JDI subscale

is 54. Scores for the nine-item scales are doubled to achieve an

equivalence of total points and ranges. In addition to subscale scores,

the JDI also generates an overall index of job satisfaction by adding

the subscale scores for a total score. A score of 18 on a subscale

signifies indifference (all items answered with a question mark) and a

score of 27 indicates a balanced attitude toward a job facet.

The JDI has internal consistency coefficients, corrected by the

Spearman-Brown formula, in the .80s. The coefficients of reliability

for the five subscales are: work (a = .79), supervision (a = .85),

co-workers (a = .88), pay (a = .81), and promotion (a = .79) (Smith

et al., 1969). Crites (1969) determined that scale ordering did not

affect scores. Schneider and Dachler (1978) stated that the JDI had

retest reliability of .57 after a 16-month interval.

Marcus Paul Placement Profile

The Marcus Paul Placement Profile (MPPP) describes work behavior

patterns of people under normal working conditions. These patterns are

stable over time as long as the work environment is stable. Although

individuals exhibit all patterns to some degree, one pattern of behavior

predominates.

A computer program developed to score the instrument analyzes the

subject's responses and designates the predominant work behavior type.











The program will also generate a subtype based on the strength and

interaction of responses on the other work dimensions. The subject's

scores on each work behavior dimension are printed on a graph. Scores

range from -15 to 15. The major work behavior type will have the

highest score. The historical background and other details of the MPPP

were described in Chapter II.

In order to obtain validity data on the MPPP, Gene Wiggington

(personal communication, February 10, 1984) administered a questionnaire

to 96 students who had taken the MPPP as part of a career education

course. The single-item questionnaire follows:

Please check the statement that is most accurate for you.

1. Both paragraphs of the Placement Profile are a fairly
accurate description of my work behavior.

2. The first paragraph of the Placement Profile is a fairly
accurate description of my work behavior; the second
paragraph is not.

3. The second paragraph of the Placement Profile is a fairly
accurate description of my work behavior; the first is not.

4. My Placement Profile is not a very accurate description of
my work behavior.

A total of 85 students (88.6%) indicated that both paragraphs of

the MPPP accurately described their work behavior. Seven (7.3%)

responded to the second choice, 3 (3.1%) to the third choice, and only

one student (1%) indicated the MPPP was not an accurate description of

that person's work behavior.

The MPPP requires less than 10 minutes to complete. The items are

written to make the instrument useful for a variety of educational

backgrounds. Test-retest reliability is about 98% (J. Nickens, personal

communication, November, 1983).











Questionnaires for Practicing and Former Medical Technologists

The investigator developed two closed-form questionnaires to

collect demographic data and career information from practicing and

former medical technologists. Based on previous research, the

questionnaire for practicing technologists included items to measure

perceived existence of alternative careers (Mobley et al., 1978;

Mobley et al., 1979; Steers & Mowday, 1981), intention to search for

alternative careers (Mobley, 1977; Mobley et al., 1978), met

expectations (Muchinsky & Tuttle, 1979; Porter & Steers, 1973), and

intention to leave (Mobley, 1982; Mobley et al., 1979). Behavioral

intention to leave is the immediate precursor to turnover and may be

assessed by a single-item measure of intention (Kraut, 1975; Waters

et al., 1976).

Data Treatment and Analysis

The researcher scored the JDI manually according to the key

described by Smith et al. (1969). She derived five subscores and a

total score for each participant.

A computer program developed by Marcus Paul Computer Systems was

used to score the MPPP. Subjects' responses to the 24 frames are

entered into the computer. The program generated a score for each work

behavior type and denoted the major work behavior type and subtype for

each subject. Scores were rounded off to the nearest half-point for

statistical analyses.

The researcher entered data from the Profile, index, and demographic

questionnaire directly into the computer terminal. After printing and

checking these entries for accuracy, she used the Statistical Analysis

System (SAS) with appropriate subprograms to answer the research questions.











The program generated frequencies and means to determine the work

behavior types of medical technologists. Analysis of variance (ANOVA)

showed the relationships between work behavior type and overall job

satisfaction or specific aspects of job satisfaction. Tukey's test of

Honestly Significant Differences was used to make pairwise comparisons

between groups. This test controls for the Type I error rate. The

relationship between work environment and job satisfaction was also

tested by ANOVA and Tukey's test. The chi-square test assessed the

relationship between intention to leave medical technology, sex, and

work behavior type. Sex differences on total JDI scores were determined

by the t test. Stepwise discriminant analysis was performed to see

which combinations of variables, if any, would be the best predictors

of attrition. Significance for all tests was determined at the .05

confidence level.


















CHAPTER IV
RESULTS


This section contains results of the study and provides answers to

the research questions posed in Chapter III. The first section

describes the sample population and contains analyses of data relevant

to each question.


Description of Population

Practicing Medical Technologists

Table 2 summarizes the data on practicing technologists obtained

from the demographic questionnaire. The majority of the subjects were

females (N = 72, 78.3%). More than 60% had practiced medical technology

for more than 5 years and most (56.5%) worked in large (more than 400

beds), teaching hospitals.

When asked about their future in medical technology, 32.6% of the

respondents expected to leave and 22.8% were uncertain. Furthermore,

22.8% indicated they would most likely leave within the next year.

More than three fourths of the subjects (77.2%) felt it would be easy

for them to find other jobs.

Medical technology met the professional expectations of three

fourths (76.1%) of the sample. However, only one third indicated that,

if they had it to do again, they would select medical technology as a

career.

Fewer than one half (48.9%) of those surveyed felt they had

received adequate career information to make an informed choice about











Table 2. Characteristics of practicing medical technologists.


Characteristics N Percent


A. Sex
1. Male 20 21.7
2. Female 72 78.3

B. Age
1. Under 25 years 9 9.8
2. 25-35 59 64.2
3. 36-45 15 16.3
4. 46-55 5 5.4
5. Over 55 years 4 4.3

C. Years at current job
1. Less than 1 year 20 21.7
2. Between 1 and 3 years 22 23.9
3. Between 3 and 5 years 26 28.3
4. Between 5 and 10 years 15 16.3
5. More than 10 years 9 9.8

D. Total years of experience
1. Less than 1 year 3 3.3
2. Between 1 and 3 years 15 16.3
3. Between 3 and 5 years 13 14.1
4. Between 5 and 10 years 25 27.2
5. More than 10 years 36 39.1

E. Work setting
1. Hospital
a) small (fewer than 200 beds) 8 8.7
b) medium (200-400 beds) 20 21.7
c) large (more than 400 beds) 52 56.5
2. Private laboratory 3 3.3
3. Blood bank 3 3.3
4. Research laboratory 1 1.1
5. Clinic 5 5.4

F. Future in medical technology
1. Definitely will not leave 14 15.2
2. Probably will not leave 27 29.4
3. Uncertain 21 22.8
4. Probably will leave 23 25.0
5. Definitely will leave 7 7.6

G. Perceived ease of finding an alternative job
1. Very easy 24 26.1
2. Fairly easy 47 51.1
3. Not easy at all 12 13.0
4. Uncertain 9 9.8











Table 2 (continued)


Characteristic N Percent


H. Likelihood of leaving medical
technology within a year
1. Highly likely 12 13.0
2. Most likely 9 9.8
3. Not likely 58 63.0
4. Uncertain 13 14.2

I. Met expectations of the profession
1. Exceeded expectations 2 2.2
2. Met expectations 33 35.9
3. Somewhat met expectations 35 38.0
4. Did not meet expectations 22 23.9

J. Would choose medical technology
again as a career
1. Would choose again 30 33.0
2. Would choose again with reservations 6 6.6
3. Probably would not choose again 35 38.4
4. Definitely would not choose again 20 22.0

K. Adequate career information to choose
medical technology
1. More than adequate 15 16.3
2. Adequate 30 32.6
3. Some information but more needed 38 41.3
4. Very little 9 9.8

L. Perceived usefulness of work behavior
characteristics in career decision making
1. Very helpful 34 37.4
2. Probably helpful 34 37.4
3. Would not help 15 16.4
4. Uncertain 8 8.8



entering medical technology. A total of 68 technologists (74.8%) felt

that information about work behavior types would have been helpful in

career decision making.

Former Medical Technologists

Table 3 contains the demographic data for former medical

technologists. Of the 19 former technologists surveyed,.10 (52.6%)











Table 3. Characteristics of former medical technologists.


Characteristics N Percent


A. Sex
1. Male 10 52.6
2. Female 9 47.4

B. Age
1. Under 25 years 1 5.3
2. 25-35 8 42.0
3. 36-45 9 47.4
4. 46-55 1 5.3
5. Over 55 years 0 0

C. Years since practicing medical technology
1. Less than 1 year 1 5.3
2. Between 1 and 3 years 6 31.6
3. Between 3 and 5 years 6 31.6
4. Between 5 and 10 years 5 26.2
5. More than 10 years 1 5.3

D. Total years experience as a medical
technologist
1. Less than 1 year 0 0
2. Between 1 and 3 years 4 21.1
3. Between 3 and 5 years 4 21.1
4. Between 5 and 10 years 6 31.6
5. More than 10 years 5 26.2

E. Present profession
1. Physician's assistant 2 10.5
2. Sales representative (health related) 9 47.3
3. Biomedical engineer 2 10.5
4. Hospital administrator 1 5.3
5. Chef 1 5.3
6. Small business owner (electronics) 1 5.3
7. Technical rep. (health related) 2 10.5
8. Pathology resident 1 5.3

F. Would recommend medical technology to others
1. Would strongly recommend it 4 21.1
2. Would recommend it with reservation 4 63.1
3. Would probably recommend it 2 10.5
4. Would strongly advise against it 1 5.3

G. Adequate career information to choose
medical technology
1. More than adequate 3 15.8
2. Adequate 6 31.6
3. Some information but more needed 8 42.1
4. Very little 2 10.5











Table 3 (continued)


Characteristics N Percent


H. Would return to medical technology
1. Yes 4 21.1
2. No 10 52.6
3. Uncertain 5 26.3



were males. More than half the subjects (52.7%) were over 35 years,

and 57.9% had practiced as medical technologists more than 5 years.

Former technologists worked in a variety of occupations. Only two,

however, worked in nonhealth related fields (chef, electronics

business owner). The majority (68.5%) had left medical technology

less than 5 years ago.

When asked if they would return to medical technology, 52.6% of

the subjects responded "NO" and 26.3% were uncertain. The majority

(63.1%) would recommend the field to others. More than half the

respondents (52.6%) indicated they had received little or insufficient

information about medical technology before making a decision to enter

this field.

Table 4 contains a comparison of medical technologists' responses

to items asking them to list, in order of importance,- the five factors

that influenced them to enter medical technology and the five factors

most influential in their decision to leave. Practicing technologists

ranked interest in science and medicine, desire to help the sick, job

opportunities, security, and expected salary as major reasons for

selecting medical technology as a career. Former medical technologists

listed interest in science and medicine, desire to help the sick,

availability of an educational program, job opportunities, and security.











Table 4. Comparison of the five major factors influencing medical
technologists in selecting, leaving, or intending to leave
medical technology.


Factor "Intention"/Attrition
Group rank Selection factors factors


Practicing
Technologists 1 Interest in science Lack of career advance-
and medicine ment
2 Desire to help the Inadequate salary
sick
3 Job opportunities Routine nature of work
4 Job security Stressful nature of work
5 Expected salary Lack of status and
recognition


Former
Technologists 1 Interest in science Lack of career advance-
and medicine ment
2 Desire to help the Inadequate salary
sick
3 Availability of Lack of status and
educational program recognition
4 Job opportunities Stressful nature of work
5 Job security Routine nature of work



Reasons for leaving or intending to leave the field were the same

for both groups of technologists. In order of importance, former

medical technologists left for the following reasons: lack of career

advancement, inadequate salary, lack of status and recognition,

stressful nature of work, and routine nature of work. Practicing

technologists also ranked lack of career advancement and inadequate

salary as the two major factors for desiring to leave followed by the

routine nature of work, stressful nature of work, and lack of status

and recognition.

Technologists' responses in this study were comparable to those

reported by previous researchers. Showery (1976) reported that only











30.8% of the technologists in his survey would choose medical technology

again if given the choice. Irwin (1983) found that 57% of the

participants in her study definitely planned to leave medical technology

within 5 years and 10% were undecided. Reports of inadequate career

information are consistent with studies by Youse and Clark (1977) and

Gleich (1978).

Holstrom (1975) and Koneman (1982) also reported that medical

technologists chose this field because they desired to help people,

had an interest in science and medicine, saw a potential for

advancement and financial rewards, and felt it offered security.

Technologists in studies by Hajek and Blumberg (1982), Irwin (1983),

Miller (1982), Myers et al. (1982), Rogers (1983), and Showery (1976)

cited the same reasons for leaving or intending to leave medical

technology as the subjects in this study: lack of recognition, poor

pay, no upward mobility, job stress, and boredom (from over

specialization and mechanization).


Research Questions


Question 1: What are the work behavior types of medical

technologists in Florida? Table 5 contains the frequencies and

percentages of work behavior types among practicing and former medical

technologists. Of the 92 practicing technologists, 55 (59.8%) were

Producers. Almost a third (32.6%) were Concentrators. Only four (4.3%)

and three (3.3%) of those surveyed were Energizers and Inducers

respectively.

The most common work behavior type among former technologists was

the Concentrator type (36.8%). More than one fourth (26.3%) were Inducers.











Table 5. Work behavior types of medical technologists.

Practicing technologists Former technologists Total
Type N Percent N Percent N Percent


Energizer 4 4.3 4 21.1 8 7.2

Inducer 3 3.3 5 26.3 8 7.2

Concentrator 30 32.6 7 36.8 37 33.3

Producer 55 59.8 3 15.8 58 52.3



Of the remaining seven subjects, four (21.1%) were Energizers and three

(15.8%) were Producers.

Overall, the majority (52.3%) of technologists in the study were

Producers. One third (33.3%) were Concentrators and the remaining

subjects were equally divided between Energizer (7.2%) and Inducer

types (7.2%).

Concentrators and Producers work to maintain the organization in

its present form. They can be counted on to do the job and follow the

rules and regulations of the organization. Energizers and Inducers

seek to alter the system and effect change in the organization. Chapter

II contains detailed descriptions of the types.

Medical technology contains a higher proportion of Producers and

Concentrators than occurs in the general population. Approximately

60% of the general population are either Producers or Concentrators,

with Producers predominating. Energizers and Inducers represent an

additional 20% each (Bauch, 1981). The proportion of work behavior

types among former technologists, however, approximates these figures

more closely than the proportions of work behavior types among practicing

technologists.











Table 6 contains the means and standard deviations for scores of

work behavior types on each dimension of the Profile. Compared to

Energizers and Inducers, Producers and Concentrators scored high on

their respective scales. Producers had a mean score of 9.68. The

mean score for Concentrators was 8.12. Energizers and Inducers

scored an average of 3.63 and 4.81 respectively. As mentioned in

Chapter III, scores on the MPPP can range from -15 to 15 with zero as

the mean score.

Producers' scores on the other dimensions indicate they also

scored high on the Concentrator scale (x = 4.49) and low on the Inducer

and Energizer scales. Concentrators scored high on the Producer

scale (x = 3.34) and also scored low on the Energizer and Inducer

scales. Although not high, Energizers' second strongest scores were

on the Producer dimension (x = -.75). For Inducers, the Concentrator

dimension had the second highest mean score (x = 1.38).



Table 6. Mean scores and standard deviations for each work behavior
type on each work dimension.


Type Work Behavior Dimension

Energizer Inducer Concentrator Producer

Energizer x 3.63 -2.81 -0.13 .75
SD 1.33 5.49 2.39 3.19

Inducer x .50 4.81 1.38 -2.88
SD 3.89 0.59 3.09 4.50

Concentrator x -5.05 -3.08 8.12 3.34
SD 4.46 4.23 2.82 3.72

Producer x -3.83 -5.41 4.49 9.68
SD 4.64 4.14 3.61 2.74











As discussed in Chapter II, the MPPP generates, in addition to one

of the four major work behavior types, a more detailed description of

an individual's work behavior. This "subtype" is based on the

interactions among all choices and the strength of the individual's

responses on each dimension of work behavior.

Almost two thirds (65%) of practicing technologists fell into

three subtypes. Descriptions of these types are as follows:

Type 9 has characteristics of the worker types who apply
their skills in nonthreatening situations. They will
cautiously follow procedures and rules. They are committed
to doing the job correctly, and try hard to be prepared to
do their best. They like predictable work environments where
their jobs are clearly defined, but will enthusiastically
accept new assignments if the assignments are in their area
of expertise. They will take the time to be sure they
understand exactly what is desired of them, get the facts
relating to the assignment, and if they make a commitment,
they produce accordingly. An important value to the
organization is the precision and quality of their work and
their personal identity with their product. (Bauch, 1981,
p. 23)

Type 11 has traits of perfectionist workers. These
individuals follow directions exactly and strive for
flawless products. When procedures and deadlines are
clear and specific, they attend to all the detail and
quality work. Thus, no backing up or correcting will be
needed. They ask for clarification frequently to make
sure things are being done right. They can explain the
rules and operating procedures to the new employee as
well as the author. They accept the system without great
concern about why and do not require intensive supervision
once the job is described. They are noted for dependability
in completing work when expected and doing their best to
attain quality. (Bauch, 1981, p. 24)

Type 16 has characteristics of the specialist group. These
people are noted for good planning and persistence on the
job over long periods. They are quite accepting of the
varieties of styles of co-workers but will maintain a small
group of good friends. They like consistency in their work
environment as they value the tried and proven methods.
They establish a steady pace and follow it with or without
supervision. They appreciate recognition for their staying
at the job until it is done. (Bauch, 1981, p. 27)











Subtypes of the former medical technologists were heterogeneous.

No one type predominated.

These findings on work behavior types among medical technologists

are consistent with results of personality types reported by other

researchers. Bowling (1973) determined that 57% of the medical

technologists in her sample had a strong preference for the sensing-

judging dimensions on the Myers Briggs Type Indicator (MBTI). They

were predominately introvert-sensing-thinking-judging (ISTJ),

extravert-sensing-thinking-judging (ESTJ), or introvert-sensing-

feeling-judging (ISFJ) types.

Fellers (1974), French and Rezler (1976), Hill (1974), and

Rezler and French (1975) also reported that medical technologists

preferred sensing, thinking, and judging. About 20% of the clinical

practitioners in the French-Rezler (1976) study were ISTJ or ESTJ

types.

Compared to practicing technologists,student technologists were

more intuitive, feeling, and perceiving (Rezler & French, 1975;

Williams, 1974). French and Rezler (1976) speculated these types found

working conditions disappointing and left medical technology before or

shortly after entering the field.

Glenn's (1982) research demonstrated significant relationships

between personality functions measured on the MBTI and work behavior

types measured by the MPPP. She found significant correlations between

the Producer type work behavior and the introvert (r = .35), sensing

(r = .48), and judging (r = -.36) scores on the MBTI. Producers who

are exacting in their work were also introverts, prefering the sensing

and judging modes.











Bauch's description of Producers (presented in Chapter II) and

Myers' (1976) description of the introvert-sensing-judging type are
i
very similar. According to Myers, the introvert-sensing-judging

types are those who

like quiet for concentration, tend to be careful with
details, and seldom make errors of fact. They tend not
to mind working on one project for a long time
uninterruptedly, and like to think a lot before they act,
sometimes without acting. They are patient with routine
details, and tend to be good at precise work. They are
at their best when they plan their work and follow their
plan. (pp. 17-18)

Glenn also reported that Concentrators were most likely to be

sensing and judging, introverted or extraverted, with a preference for

the feeling function. Energizer scores correlated significantly with

the intuitive and thinking personality functions. Inducer scores, as

expected, correlated with the extravert, intuitive, and perceptive

personality functions.

In light of these studies on personality types among medical

technologists and correlations of personality type to work behavior

type, it is not surprising, then, to find the high proportion of

Producers and low proportion of Energizers and Inducers among medical

technologists. Producers have the qualities required and desired for

medical technology. They carefully follow procedures and strive for

precision. The subtypes of medical technologists also reflect

essential work behavior characteristics for this field. In addition

to producing precise, quality work and following directions, these

subtypes complete the work on time with little supervision.

As a bench-level technologist, the Inducer would not have many

opportunities for contacts with fellow workers or patients.











The Energizer would find few outlets for new ideas, solving

problems, or bringing about change. However, Energizers and Inducers

would probably find avenues for expressing their work behavior traits

as administrative or teaching technologists.

Former technologists work in a variety of occupations. Therefore,

it is reasonable to find that the proportions of work behavior types

among this group approximate those of the general population.

Question 2: Does a relationship exist between the work behavior

type of the technologist and overall job satisfaction? The researcher

used a one-way analysis of variance (ANOVA) to answer this question.

The findings are reported in a summary table (Table 7). A significant

relationship occurred between work behavior type and the overall job

satisfaction score of the subject.

The investigator used Tukey's test of Honestly Significant

Differences (HSD) to determine the source of variance between the work

behavior types. The mean scores of Inducers differed significantly

from scores of Producers and indicated higher levels of overall job

satisfaction. There were no significant differences among the total

JDI scores of the other work behavior types.

Glenn (1982) found no significant relationship between overall job

satisfaction, measured by a Job Satisfaction Questionnaire, and work

behavior types of vocational education administrators. French and

Rezler (1976) could not correlate overall job satisfaction with

personality type among medical technologists. Williams (1976), however,

determined that medical technologists with introvert personality types

as measured by the MBTI were, in general, less satisfied with their











Table 7. Analysis of variance results for JDI scores by work behavior
type.

Total JDI Scores
Source df Sum of squares Mean square F ratio F prob.

Between Groups 3 17,657.32 5,885.77 3.44 .02*
Within Groups 107 182,868.92 1,709.06

x Group
145.71 (4) Producer
162.16 (3) Concentrator
166.375 (1) Energizer
190.00* (2) Inducer
(2 was different from 4, but not from 1 or 3)

Work Subscale of JDI
Source df Sum of squares Mean square F ratio F prob.

Between Groups 3 671.30 223.77 2.26 .09
Within Groups 107 10,602.97 99.09

x Group
28.79 (4) Producer
32.38 (3) Concentrator
33.88 (1) Energizer
36.63 (2) Inducer

Promotion Subscale of JDI
Source df Sum of squares Mean square F ratio F prob.

Between Groups 3 2,855.11 951.70 5.21 .002*
Within Groups 107 19,557.00 182.78

x Group
9.12 (4) Producer
13.97 (3) Concentrator
16.00 (1) Energizer
28.38* (2) Inducer
(2 was different from 3 and 4, but not from 1)

Pay Subscale of JDI
Source df Sum of squares Mean square F ratio F prob.

Between Groups 3 1,832.02 610.67 2.88 .04*
Within Groups 107 22,667.56 211.85

x Group
21.47 (4) Producer
25.92 (3) Concentrator
32.12 (2) Inducer
34.25 (1) Energizer