East Tennessee State University Job Control and Heightened Risks Report: Psychology Answers 2021
East Tennessee State University Job Control and Heightened Risks Report
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Research Study Article
Know the structure of a research study article.
A research study article will consistently contain the following sections
Abstract, Introduction, Methods, Results, Discussion, and References.
Some section names may change slightly, e.g. Methods might be Research
Methods or Methodology. If you don?t find these sections in a journal
article, then you don?t have a research study article.
Know what each section contains.
Summary of the key points of the article: the purpose of the study and a
hypothesis, the methodology used, who was studied, and the findings. Read
this first, but don?t rely on it solely to draw conclusions about the study.
Contains a survey of the relevant background for a study, a context for the
study, and the hypothesis (i.e. the specific predictions to be tested). It will
also usually contain a review of prior studies related to the same topic.
Describes the approach taken in the study. This section provides detailed
information about the research instrument used, (e.g. questionnaire),
subjects (e.g. women between the ages of 50 and 70), procedures, and the
approach to data analysis.
Data is summarized in this section, and relationships among variables and/or
differences among groups are reported. These analyses should directly
reflect the predictions originally described in the Introduction. Further
comparisons may also be included to clarify findings or to explore
Results are summarized in narrative form as opposed to statistics or
numbers. The ways in which the study?s results coincide with the hypothesis
and previous studies will also be discussed, as well as suggestions for the
need for further studies on the topic.
Listing of the sources cited in the article such as books and articles, as well
as sources not directly used but are relevant to the topic. NOTE: Use the
Reference list to find still other sources on your topic!
Now you?re ready to read.
Not first to last page, unless you?re really familiar with the topic. Instead,
1. Start with the Abstract for an overview.
2. Read the first paragraph or so of the Introduction to get a sense of
the issue. Go to the last paragraph to read the hypothesis.
3. Skim the Discussion to see how the study turned out.
4. Now, go back to the middle part for the details. Read the Methods
section carefully and plan to reread it, even a couple of times to
digest it all.
5. Then, read the Results section. You may want to turn to the
Discussion section for clarification of what the reported statistics
demonstrate. Don?t get bogged down in the details of either the
Methods or the Results section, but try to get a good idea of how the
hypotheses were tested.
6. Read the Discussion section more closely.
7. Finally, read the whole article, first page to last page. Reread for the
Adapted from: Franzoi, S.L. & Ratlif-Crain, J. (2003). Guide to reading research articles. In
Instructor?s manual to accompany social psychology. 3rd ed. (pp.29-30). Boston:McGrawHill.
For additional assistance and an opportunity to practice these new skills, go to this
Research Report Analysis
Introduction to Psychology
Research Report Analysis (RRA)
You have received a research article to use in this analysis. Read the article and answer the
following questions. Be sure to clearly label your responses using the Roman numeral
headings as well as numbers beneath each heading. If you do not clearly number each
response, I will not grade your submission. This will keep you focused on the question being
addressed and make the job of evaluating your responses much easier. The evaluation form at the
end of this document is the one I?ll use to ?grade? each of your 18 responses.
Name of Research Article:
1. Describe the purpose of the study.
2. Identify the theories or issues that serve as a broad context for the study.
3. What does this study hope to add to the field of psychology? Why is this important?
4. Describe the author?s hypothesis.
5. What is the rationale for the hypothesis?
6. Identify the research design (e.g., correlational, experimental). Explain how you know it is
7. Identify the variables on interest.
8. Who were the participants in this study. Describe their key characteristics.
9. Describe the key features of the materials or apparatuses used in the study. (This includes
tests, blood work, video games, etc.)
10. Describe the procedures used in conducting this study. (What did they do? How was data
11. Clearly state the main findings of this study.
12. Did the results support the hypothesis or not? Explain.
13. Describe the major conclusions of the authors and how the data supported them.
14. Discuss any practical, social, or theoretical significance of the findings.
15. Provide a thoughtful critique of the article.
16. Discuss some limitations of the study.
17. Provide suggestions for improvement and future research.
Page 1 of 2
Research Report Analysis
Research Report Analysis
1. Purpose of the study clearly stated by the student.
2. Theme or issue that serves as a broad context for the study
3. Is what is added that is new clearly stated? Worth of study
4. Authors? hypothesis clearly stated.
5. Rationale for the hypothesis clearly stated.
6. Research design identified.
7. Variables of interest identified.
8. Important features of the subjects explained well.
9. Key features of the materials or apparatus clearly explained.
10. Procedures used in conducting the study clearly identified.
11. Main findings in this study clearly stated.
12. Whether the results support the hypothesis or not clearly stated.
13. Major conclusions of the authors, and how the data support them,
14. Practical, social, or theoretical significance of the findings.
15. Overall quality of the critique.
16. Limitations of the study noted.
17. Suggestions for improvement and future research clearly stated.
18. Overall technical quality of the paper (spelling, grammar,
Page 2 of 2
Journal of Occupational Health Psychology
1998, Vol. 3, No. 4,402-409
Copyright 1998 by the Educational Publishing Foundation
Job Control, Personal Characteristics, and Heart Disease
Hans Bosma, Stephen A. Stansfeld, and Michael G. Marmot
University College London Medical School
This study examined the role of several personal characteristics in the association between low job
control and coronary heart disease among male and female British civil servants. The logistic
regression analyses were based on a prospective cohort study (Whitehall II), comprising 6,895
men and 3,413 women, age 35-55 years. Men and women with low job control at baseline had 1.5
to 1.8 higher risks of new heart disease during the 5.3-year follow-up. Psychological attributes,
such as hostility, negative affectivity, minor psychiatric disorder, and coping, affected this
association very little. The personal characteristics were not confounders, intermediate factors, or
effect modifiers. Hence, increasing job control could, in principle, lower risks of heart disease for
There is increasing evidence that low job control,
high job demands, and low work support predict
coronary heart disease (CHD; Karasek & Theorell,
1990; Schnall, Landsbergis, & Baker, 1994; Theorell
& Karasek, 1996). These factors are components of
the widely used job strain model, as developed by
Karasek and Theorell (1990). Recent findings show
that job control may be the main, critical component
in a healthy work environment (Bosma et al., 1997;
Johnson, Stewart, Hall, Fredlund, & Theorell, 1996).
In a previous article (Bosma et al., 1997) based on
Whitehall II data, low job control, but not job
demands, was found to predict new reports of CHD
among London male and female civil servants. Odds
ratios of new CHD in a 5-year follow-up period for
Hans Bosma, Stephen A. Stansfeld, and Michael G.
Marmot, Department of Epidemiology and Public Health,
International Centre for Health and Society, University
College London Medical School, London, United Kingdom.
This work was supported by grants from the Health and
Safety Executive; the Department of Health; Medical
Research Council; British Heart Foundation; the National
Heart, Lung, and Blood Institute (2 RO1 HL36310); the
Agency for Health Care Policy Research (5 RO1 HS06516);
the Institute for Work and Health, Toronto, Ontario, Canada;
the John D. and Catherine T. MacArthur Foundation Research Network on Successful Midlife Development; and
the EU BIOMED network Socio-Economic Variations in
Cardiovascular Disease in Europe: The Impact of the Work
Environment (Heart at Work).
We thank all participating civil service departments and
their welfare and personnel officers, the Civil Service
Occupational Health Service and their directors, Elizabeth
McCloy, George Sortie, Adrian Semmence, and all participating civil servants.
Correspondence concerning this article should be addressed to Hans Bosma, Department of Epidemiology and
Public Health, International Centre for Health and Society,
University College London Medical School, 1-19 Torrington Place, London WC1E 6BT, United Kingdom.
participants with low job control compared with those
with high job control were about 1.8 (Bosma et al.,
1997). Johnson et al. reported a similar odds ratio for
cardiovascular mortality in a Swedish general population sample.
Some researchers have criticized the job strain
model for its disregard of individual differences in
susceptibility and coping (Kristensen, 1995; Parkes,
1989; Siegrist, 1996; Warr, 1994). The main emphasis
in the model is on the work environment. Personal
characteristics play only a modest role as intermediate
factors between job strain and CHD. In other words,
personality and personal attitudes are thought to be
partly shaped by accumulated (work) environmental
exposure (Karasek & Theorell, 1990; Landsbergis,
Schnall, Deitz, Friedman, & Pickering, 1992; Schnall
et al., 1994). Advocates of the job strain model think
that personality or psychological attributes are
unlikely confounders of the association between job
strain and heart disease (Schnall et al., 1994), and
they have hardly discussed the possibility that people
with varying psychological attributes may differ in
their vulnerability when faced with adverse working
conditions (Parkes, 1991). Karasek and Theorell
(1990) have further argued that ?decades of research
have still not identified the personality variables? (p.
96). Given the paucity of research in this context,
there is a need for a more detailed examination of the
associations among job strain, personal characteristics, and heart disease.
Longitudinal data from the Whitehall II study
among 10,308 male and female civil servants have
allowed the examination of seven personal traits (e.g.,
hostility) and states (e.g., minor psychiatric disorder)
and their role in the relation between low job control
and new reports of CHD. We are specifically
interested in the question of whether the previously
JOB CONTROL, PERSONAL CHARACTERISTICS, AND HEART DISEASE
reported job control-CHD association is independent
of any of the personal characteristics or whether some
participants are more susceptible to adverse health
effects of low job control than others. The availability
of self-reported and externally assessed job control
from more angina pectoris reports. Doctor-diagnosed
ischemia was less frequently reported by women. Because,
otherwise, numbers would become too small and because
the findings in the previous report were similar across CHD
outcomes (Bosma et al., 1997), the three outcomes were
enables us to study job control, dependent and
independent of the perceptions of job incumbents.
The Whitehall n study is a sequel to the first Whitehall
study, which began in 1967 (Marmot, Shipley, & Rose,
1984; Reid et al., 1974). The Whitehall II study was set up
primarily to investigate the degree and causes of the social
gradient in morbidity and mortality; to study work
characteristics, social support, and additional factors related
to these gradients; and, most important, to include women.
In the study, a cohort of civil servants was established
between 1985 and 1988 (Phase 1). All male and female civil
servants whose ages were between 35 and 55 years in 20
London-based civil service departments were sent an
introductory letter and screening questionnaire and were
offered a screening examination for cardiovascular diseases.
The response rate was 73%. The true response rate would
probably have been higher, however, because about 4% of
the civil servants on the lists provided by the civil service
had moved before the study and were therefore not eligible
for inclusion. In total, 10,308 civil servants were examined:
6,895 men (67%) and 3,413 women (33%).
After the initial participation at Phase 1, the participants
were approached again in 1989-1990 (Phase 2: mailed
questionnaire) and in 1991-1993 (Phase 3: mailed questionnaire and screening examination). The participation rates at
these two phases were 79% and 83%, respectively; 7,372
people (72%) were participants at all three phases, and 9,302
people (90.2%) participated at either Phase 2 or Phase 3.
Furthermore, although still eligible for participation, 1,286
participants (12.5%) had left the civil service before Phase 3.
The length of follow-up is 5.3 years on average, with a range
of 3.7 and 7.6 years. Full details of the screening
examinations are reported in Marmot et al. (1991).
Coronary Heart Disease
Reports of any of the following three outcomes were
coded as a CHD event: angina pectoris, severe pain across
the chest, and doctor-diagnosed ischemia. Angina pectoris
was measured by the Rose Angina Pectoris questionnaire
and denned as pain located over the sternum or in both the
left chest and the left arm that is precipitated by exertion,
that causes the person to stop, and that goes away in 10 min
or less (Rose et al., 1977). Severe pain across the chest was
denned as having ever had a severe pain across the front of
the chest lasting half an hour or more. Doctor-diagnosed
ischemia depended on whether the participant reported that a
general practitioner or hospital doctor ever suspected or
confirmed a heart attack or angina pectoris. This outcome
was assessed at all three phases. At Phases 2 and 3, there
were 401 new reports of CHD for men (8.8%) and 253 for
women (12.3%). The higher incidence in women resulted
Two methods were used to assess job control: self-reports
by the civil servants and ratings by personnel managers
(external assessments); skill discretion (six 4-point items)
and decision authority (nine 4-point items) were combined
in the self-report measure of job control (Cronbach?s
a = .84; Bosma et al., 1997). Results with skill discretion
and decision authority were highly similar to the results with
this combined measure of job control. Skill discretion and
decision authority were highly correlated (r = .8). Selfreported job control was available at all three phases. In
addition, at Phase 1, personnel managers assessed each job
regarding the level of control by responding to the following
12-point item: ?How often does the job permit complete
discretion and independence in determining how, and when,
the work is to be done?? In 18 out of 20 departments, 140
well-informed personnel managers undertook this rating.
Detailed information was obtained on individual jobs,
because 5,766 different jobs were rated and 8,838 participants occupied these jobs. We used tertiles for both the
external and self-reported assessments.
The following personal characteristics were used in the
analyses: hostility. Type A behavior, competitiveness, minor
psychiatric disorder, negative arfectivity, and two coping
patterns. We measured hostility with the Cook-Medley
Hostility Scale (Cook& Medley, 1954; Cronbach?s a = .83)
and Type A behavior with the Framingham Type A Scale
(Cronbach?s a = .72; Haynes, Feinleib, Levine, Scotch, &
Kannel, 1978). The competitiveness scale consisted of three
items from the Framingham Type A Scale (Cronbach?s
a = .70). This subscale was based on factor analysis of the
Type A items. Because of its likely relation to need for
control, we examined this subscale in more detail. Persons
with a high need for control are a plausible high-risk group
when confronted with low job control. The three items were
?Are you bossy or dominating?? ?Have you a strong need
to excel?? and ?Are you competitive?? We used the General
Health Questionnaire to measure minor psychiatric disorder
(Cronbach?s a = .93; Goldberg, 1972). Negative affectivity
was measured with the Negative Affect subscale of the
Affect Balance Scale (Cronbach?s u = .67; Bradburn, 1969;
Stansfeld, North, White, & Marmot, 1995). Negative
affectivity is the disposition to respond negatively to
questionnaires and may inflate correlations between selfreported work characteristics and self-reported disease
(Brief, Burke, George, Robinson, & Webster, 1988; Chen &
Specter, 1991). The two coping patterns were based on a
factor analysis of items addressing reactions to conflicts at
work (see Appendix): angry coping (Cronbach?s a ? .70)
and unassertive coping (Cronbach?s a = .60). Two other
coping subscales were not used, because of low reliabilities.
BOSMA, STANSFELD, AND MARMOT
Participants with one item missing on the General Health
Questionnaire or the angry coping scale were, for that item,
assigned the mean score of the remaining items. The
Cook-Medley Hostility and Negative Affect scales had
many missing values (4,275 and 2,773, respectively),
because these scales were not included in all versions of the
questionnaire at Phase 1. To allow for an optimal
comparison of odds ratios for job control before and after
adjustment for these characteristics, missing values were
estimated by a regression analysis using age, employment
grade level, and sex as predictors. Whereas the threshold for
the General Health Questionnaire was established and
validated in a subsample (Stansfeld & Marmot, 1992), all
other scales were dichotomized by using tertiles; they had
the following values: 0 (without negative attribute; two
lowest tertiles) and 1 (with negative attribute; highest
We used contingency tables to compare men and women
regarding the association between job control and the
personal characteristics at Phase 1. Separately for participants with and without negative personal characteristics at
Phase 1, age-adjusted logistic regression analysis was used
to examine the associations between low job control at
Phase 1 and any new CHD event during follow-up (at Phases
2 and 3). Interactions between job control and any of the
seven personal characteristics at Phase 1 were tested for
statistical significance. Two methods were used to evaluate
interactions: (a) introducing product terms in the logistic
regression model and (b) introducing product terms in an
equivalent linear probability model (Landerman, George,
Campbell, & Blazer, 1989). Interactions were examined
using both categorical and continuous variables. In a
subsequent analysis, the odds ratios for low job control were
adjusted for the separate personal characteristics (and age).
Finally, the models were controlled for e?
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