Physical Health Following a
Cognitive-Behavioral Intervention
Gregory
McClellan Buchanan
Department
of Psychology, Beloit College
Cara
A. Rubenstein Gardenswartz
Department
of Psychology, University of California, Los Angeles
Martin
E. P. Seligman
Department
of Psychology, University of Pennsylvania
ABSTRACT
One hundred and
twenty entering freshmen, at risk for depression on the basis of their
pessimistic explanatory style scores, were randomly assigned to 1 of 2
conditions: an 8-week, cognitive-behavioral intervention designed to prevent
future depression (seminar group) or to a no-intervention control group.We
assessed the physical health of these participants 6-30 months after entry into
the project. Participants in the seminar group had better physical health than
did control participants: fewer self-reported symptoms of physical illness,
fewer doctors’ visits overall, and fewer illness-related visits to Student
Health. They were more likely to visit a doctor for a checkup and had healthier
habits of diet and exercise. We postulate that the learning of antidepression
skills produces better physical health.
Peterson, Seligman, and Vallaint (1988)
outlined the requirements that need to be met in order to demonstrate a causal
relationship between psychological traits and physical health. First, the study
must be longitudinal because physical health can influence psychological
well-being. Second, the time span must be sufficient. Although some stressors
may cause immediate effects, it is likely that others operate in a more
insidious manner, taking months or years to affect one's health. Finally,
because poor health can take many forms, multiple health measures need to be
taken.
There are three main areas where these
criteria have been met. These are the Type A Behavior Pattern (TABP) and its
relationship with coronary heart disease (CHD), stress and its effect on the
development of ulcers, and the Type C Personality and its relationship with
cancer (Bakal, 1992;Genest & Genest, 1987;Haynes, Feinleib, & Kannel, 1980;Rosenman et al., 1975). Additionally, patients
who participate in intervention programs that modify TABP, stress, and Type C
Personality, experience benefits in terms of fewer physical symptoms, less
recurrence, and increased longevity (Brooks & Richardson, 1980;Friedman et al., 1984;Grossarth-Maticek & Eysenck, 1991).
The large literature on psychological
effects on physical health, however, even when it fulfills the rest of the
criteria, is almost entirely correlational., So, in a typical example,Peterson et al., (1988) demonstrated that
pessimistic men were more than twice as likely to have succumbed to chronic
disease at the time of follow-up than were their optimistic Harvard classmates.
In another example, hostility measured by the Minnesota Multiphasic Personality
Inventory (MMPI) predicted coronary heart disease and total mortality over a
25-year period (Barefoot, Dahlstrom, & Williams, 1983).
Even though sophisticated causal modeling techniques eliminate the possibility
of specified third variables in such studies, only an experiment in which
participants are randomly assigned to have the relevant psychological trait can
rule out all third variables conclusively enough to demonstrate causality.
There have been three prior studies that
have demonstrated a relationship between explanatory style and physical health:
The Peterson et al., (1998) study; the Virginia Polytechnic Study (Peterson, 1988), in which pessimistic students
reported more days of illness and made more doctor's visits than their
optimistic peers; and the Recurrent Coronary Prevention Pessimism Study (Buchanan, 1995), in which pessimism predicted
death from coronary events over a period of 8 1/2 years. Without intervention,
explanatory style is a stable variable (Burns & Seligman, 1989). It is well
documented, however, that explanatory style can be modified (Buchanan & Seligman, 1995;Evans et al., 1992). Current research has
indicated that group seminars based on the principles of cognitive-behavioral
therapy reliably change the explanatory style of pessimistic individuals (DeRubeis et al., 1990;Gillham, Reivich, Jaycox, & Seligman, 1995;Jaycox, Reivich, Gillham, & Seligman, 1994;Seligman et al., 1988). More importantly,
participants who were assigned to the seminar condition showed improvements,
relative to no-treatment controls, in terms of reduced incidence of depression
and anxiety (Gillham et al., 1995;Jaycox et al., 1994).
We now report a study that fulfills the
criteria of causality and that demonstrates that a cognitive intervention can
cause physical health benefits through reduction in depression mediated by
changes in level of hopelessness.
Method
The participants in this study (the
Health Extension) were selected from a larger study (the APEX Project). We will
thus provide an outline of the APEX Project before describing the methodology
of the Health Extension.
The
APEX Project
The primary goal of the APEX Project was
to explore prevention of depression through a group-based cognitive-behavioral
intervention. A secondary goal was to examine possible mediators of depressive
symptom reduction including explanatory style, hopelessness, and dysfunctional
attitudes.
Participants
The APEX participants were 231
undergraduates at the University of Pennsylvania who were part of the entering
classes of 1991, 1992, and 1993. All participants were identified as at-risk
for depression on the basis of their scores on the Attributional Style
Questionnaire (ASQ;Peterson et al., 1982). ASQs were mailed to
all incoming students in the summer before their first semester. The most
pessimistic students; that is, those scoring in the bottom quartile of the ASQ
full-scale score (CPCN; seeReivich, 1995, for scoring details) were
invited to participate in a pretraining evaluation to determine their
eligibility. Participants were eligible to participate if they met all of the
following criteria: (a) not currently in psychotherapy or taking psychoactive
medications; (b) still scoring in the bottom quartile of the ASQ at the
pretraining evaluation; (c) scoring 19 or less on the Beck Depression Inventory
(BDI:Beck,Ward, Mendelson, Mock, & Erbaugh, 1961)
to exclude those participants who were currently experiencing a depressive
episode; (d) not currently meeting criteria for an Axis I disorder and never
having met criteria for major depression with psychotic features, bipolar
disorder, any psychotic disorder, and alcohol or drug dependence.
The
Learned Optimism Training Program
Immediately following the pretraining
evaluation, those participants who satisfied all the criteria were assigned to
one of two conditions using stratified random sampling according to depression
history, gender, ASQ median, and BDI median. These conditions were a no
treatment control (control group) and a prevention training program, called the Learned Optimism program (seminar group). The prevention
training program consisted of eight 2-hr meetings, held over an 8-week period,
with homework to be completed between meetings. Training was delivered to the
participants in groups of 10 by a trainer and co-trainer. Participants also had
individual meetings with the trainers on six different occasions: the beginning
of training, the middle of training, 1 month posttraining, 3 months
posttraining; the fall of their sophomore year, and the spring of their
sophomore year. During these individual meetings, the skills taught in the
prevention training program were reviewed and any questions the participants
had about applying the skills to their lives were answered. The trainers were
all cognitive therapists with between 2 and 30 years experience. The
co-trainers were either these same therapists or doctoral students in the
clinical psychology program at the University of Pennsylvania.
Skills taught in the training program
were largely based on the cognitive-behavioral techniques developed by Beck and
his colleagues (Beck, 1964,1967,1976;Beck, Rush, Shaw, & Emery, 1979;Hollon & Beck, 1979).Reivich, Jaycox, and Gillham (1991) developed
a detailed training manual for the program. The format included lecturing,
audiovisual presentations, role- playing, games and activities, open
discussions, and homework reviews. Participants were also provided with a
detailed workbook for use throughout the program and beyond.
The
Health Extension
The Health Extension to the APEX Project
began in the spring of 1994—3½ years after the APEX Project began.
Participants thus formed five cohorts depending on when they joined the APEX
Project: Fall 1991, Spring 1992, Fall 1992, Spring 1993, and Fall 1993.
The Health Extension participants were
selected from the original APEX participant pool of 231. Attempts were made to
reach all participants who were still actively part of the APEX Project and
were still attending the University of Pennsylvania. Of these, 123 participated
in the first phase of the Health Extension. Three of these participants were
dropped from the study because of chronic ill health (systemic lupus and
juvenile diabetes) at the time of entry into the APEX Project, thus leaving a
pool of 120. Of these, 104 completed the second phase of the Health Extension,
which took place 2 weeks after the first phase.1
Health
Measures
Participants met with a research
assistant who had been given extensive training in interviewing participants.
After reading and signing a consent form, the following were completed:
§
Health Visits—Objective: Participants
were asked to read and sign a release of medical information form provided by
the University's Student Health Service. One hundred and eighteen of the 120
participants signed this consent form, which gave access to their student health
records. Records pertaining to psychiatric treatment or drug and alcohol
related problems were not obtained (as per Pennsylvania state law).
Participants' medical records were then reviewed for the following information:
health at entry to the university (all students must undergo a complete
physical following acceptance to the university—three participants were
dropped on the basis of physician's report), number of visits to the Student
Health Service, reason(s) for visit, diagnosis, and treatment. Because
participants were from different entering classes, number of visits was
quantified as number per semester. As previous research (e.g.Peterson, 1988) had indicated that pessimists
were more likely to experience ill health than were optimists, we hypothesized
that there would be a difference not only in the number of visits, but also the
reason for the visit. Therefore, all visits were coded as being either (a)
illness visits, (b) maintenance or check-up visits, (c) accident visits, or (d)
other/unknown. Illness visits were largely for discomforting symptoms such as
sore throats, vomiting, fever, and so on. Checkup visits included pap smears, influenza
shots, and health counseling for such things as weight loss and smoking
cessation. Accident visits were mainly due to sport injuries but also included
falls and fights. Other visits were those that did not fit the other three
categories and included such things as having a wart removed and receiving
medication for acne.
§
Health Visits—Subjective: Participants
were asked to recall all visits they had made to medical professionals
following their enrollment in the APEX Project. Participants were asked when
each visit occurred, where the visit took place, and the reason for the visit.
This provided a subjective measure of use of health care resources. These
visits were coded in the same way as the Health Visits—Objective measure.
Participants were, by and large, accurate in their recollection of visits to
Student Health Services, though both groups underestimated the number of
visits. The correlation between actual visits to Student Health Services and
self-reported visits was .71.
§
Health Behaviors Questionnaire (adapted from a
health habits and history of health behavior questionnaire designed by theNational Center for Health Statistics [1974]):
This measure was used to determine whether the seminar group participants were
taking better care of themselves by engaging in more health maintenance
behaviors and fewer health risk behaviors. This 30-item questionnaire asks
participants to indicate to what degree they engage in a variety of behaviors
to protect their health. Responses are given on a 7-point scale. Behaviors
include not smoking, visiting the doctor, wearing seat belts, and avoiding
parts of the city with lots of crime and pollution. Scores were summed across
the 30 items to yield a composite measure of health protective behaviors.
Additionally, to determine whether there were any subsets of behaviors over
which the two groups differed, a factor analysis was performed using varimax rotation
in which only factors with eigenvalues greater than 1.0 were maintained. This
analysis yielded a stable factor solution with three factors. Items with a
factor loading of at least +/- 0.4 were considered salient. The three factors
were labeled (a) Relaxation, (b) Diet
and Exercise, and (c)Prevention.
§
Physical Symptoms—Retrospective (Suls & Mullen, 1981): Participants were
asked to list any symptoms of illness they had experienced in the preceding 2
weeks. They were provided with a list of 16 common symptoms including sore
throat, rash, fever, headache, and so on. Space was also provided for
participants to write in any unlisted symptoms they may have experienced.
§
Physical Symptoms—Prospective: At the end
of the phase one interview for the Health Extension, participants were given 14
copies of the Daily Symptoms Questionnaire, one to be filled out each evening
for the next two weeks and returned at Phase 2 of the Health Extension. One
hundred and four of the original 120 participants returned these 14
questionnaires at the time indicated, and the total number of symptoms
experienced was calculated for each participant. Additionally, participants
were asked to indicate what response (if any) they made to these symptoms.
These responses where coded as active(took medication, saw a doctor, etc.) or passive(did nothing, ignored it, etc.). Dividing the number of active or
passive responses by the total number of symptoms reported thus created two
additional variables.
§
Global Health Rating—Objective: All APEX
participants were interviewed once a semester for the duration of their
undergraduate careers using the Longitudinal Interval Follow-up Evaluation
(LIFE;Keller et al., 1987). For part of this
interview, they answered questions about their interpersonal relationships,
their academic performance, and their health. Specifically, participants were
asked if they had suffered any physical illnesses, visited their physician, or
missed classes because of illness. From their answers, a global health measure
was generated for each month the evaluation covered. Health was rated on a 0-3
scale, where 0 = no health
problems, 1 = minor problems(e.g. cold, migraine), 2 = moderate problems(e.g. illness that caused them to fall behind
in schoolwork), and 3 = serious
problems(e.g. had to drop classes
because of illness). For use in the Health Extension, these ratings were
averaged across all months since the participants enrolled in the APEX Project.
The raters were blind to whether a participant was in the control group or the
seminar group.
Measures—Mediators
To the extent that differences did
emerge between the two groups, we hypothesized that they would be mediated
through changes in depression, explanatory style, dysfunctional attitudes
and/or hopelessness as a result of the Learned Optimism Training Program.
Instruments used were the ASQ, the BDI, the Dysfunctional Attitudes Scale (DAS;cr39Weissman & Beck, 1978), and the
Hopelessness Scale (HS;Beck, Weissman, Lester, & Trexler, 1974).
These mediator measurements were collected at entry into the APEX Project and
after completion of the training procedure 6 weeks later.
Statistical
Procedures
The two main hypotheses in this study
were that group differences would emerge in terms of physical symptoms and in
number of visits to physicians. These two predictions were analyzed using
separate Multivariate analyses of variance (MANOVAs) for symptoms and visits in
which group and time served as independent variables. For the symptoms
analysis, data from the Physical Symptoms Questionnaires (Prospective and
Retrospective) were combined with the Global Health Rating Measure. For the
visits analysis, the Health Visits-Subjective and Objective data were combined.
Because participants differed in the amount of time that had passed between the
conclusion of the APEX Seminar and the beginning of the Health Extension (6-30
months), both group and time were entered into the MANOVAs as independent
variables. The time interval used was number of semesters since entry into the
APEX Project and was included in the analyses to control for the effects time
may have had on reporting rates. Further, additional hypotheses related to the
symptoms and visits data and the Health Behaviors Questionnaire were analyzed
with independent t-tests or chi-squared tests as appropriate. These were that
seminar participants would take a more active stance to the symptoms they
experienced, and that they would make proportionally more check-up visits than
illness visits. The analyses of potential mediators followed the procedure
outlined byBaron and Kenny (1986).
Results
Seminar
Versus Control Groups
As mentioned, a sizable number of
participants who participated in the APEX Project did not participate in the
Health Extension. There were no significant differences between the
participants and nonparticipants on all key variables: gender, group
assignment, and pre- and post-APEX measures of depression and pessimism.
Physical
Symptoms. Participants in the
control group experienced more symptoms of physical illness than did
participants in the seminar group (all group means and standard deviations may
be found in Table 1). This analysis revealed a main effect
for group, F(3, 96) = 2.37, p(one-tailed)
= .038. There was no effect for time on the symptoms data, and no Group ×
Time interaction. Univariate F tests indicated that the seminar participants
reported significantly fewer symptoms on the Physical Symptoms-Prospective
Questionnaires than did controls, F(1,98) = 4.33, p(one-tailed)
= .020. The group seminar participants were also rated as healthier by the APEX
evaluators, F(1,98) = 2.83, p(one-tailed)
= .048. There were no differences between the groups on the Physical
Symptoms-Retrospective Questionnaire.
Participants had been asked to report on
the Physical Symptoms—Prospective Questionnaires what action they took in
response to the symptoms they experienced. These actions were blindly coded as
either active or passive; thus, the proportion of active to passive reactions
could be calculated. This revealed that seminar participants made
proportionally more active, and less passive, responses to their symptoms, c 2(1, N=119) = 5.24; p(one-tailed)
= .038.
Health
visits. There was a main
effect for group, F(2,109) = 2.45, p(one-tailed)
= .047. The main effect for time approached significance, F(2,109)
= 2.59, p(2-tailed) = .08. The interaction of Time ×
Group was not significant, F(2,109) = 1.017, ns.
Univariate tests revealed that the control participants reported having made
more doctors visits on the Health Visits—participantive measure F(1,110)
= 3.60, p(one-tailed) = .03.
The Health Visits—Objective
measure indicated that there was no difference in the number of visits actually
made to Student Health Services, F(1, 100) = 1.13, ns. Although
the MANOVA found no main effect for time, a univariate analysis revealed that
participants across both groups reported fewer visits per semester the longer
they were at the university, F(1, 110) = 4.78, p(two-tailed)
= .029. Participants were also asked to indicate the location of the visits
they had reported on the Health Visits—Subjective measure. This allowed for
a test of the participants' memory of visits because comparisons could be made
with the Health Visits—Objective measure of Student Health visits. When
broken down into location of visit, there was no significant difference in the
number of Student Health visits reported by the two groups, t(115)=
1.40, p(one-tailed) = .082. This parallels the finding
that there was no significant difference in the number of visits actually made
to Student Health. There was, however, a significant difference in the reported
number of visits made to other locations, t(115)/CITEREF>= 2.99, p(one-tailed)
= .002. Unfortunately, attempts to establish an objective measure of these
visits made outside of Student Health were not successful.
Health visits were also coded for type
of visit. Control group participants reported making more than twice as many
illness visits than seminar group participants, t(115)= 2.95, p(one-tailed) = .002. There were no differences
in the overall number of checkup, accident, or "other" visits made. When
type of visit was coded as a proportion of the total number of visits, control
participants were found to make proportionally more illness related visits
(48%) than were seminar participants (31%), t(100)= 2.40, p(one-tailed) = .009. They also made proportionally
fewer checkup visits (32% vs. 45%), t(100)= 2.06, p(one-tailed)
= .022. There were no differences between the two groups on the proportion of
accident and "other" visits made.
A similar pattern of findings for type
of visit from the Health Visits—Objective measure confirmed these
self-report results. Control participants made more illness visits to Student
Health than did the seminar participants, t(114)= 2.20, p(one-tailed)
= .015. There was also a trend for seminar grou participants to make more
check-up visits to Student Health, t(114)= 1.43, p(one-tailed)
= .078. When type of visits was coded as a proportion of total visits made,
there was a trend for control participants to make proportionally more
illness-related visits than seminar participants (50% vs. 42%), t(93)=
1.43, p(one-tailed) = .078. A significant difference
between groups in the proportion of check-up visits was found. Seminar
participants made proportionally more check-up visits than the control
participants (33% vs. 25%), t(93)= 2.13, p(one-tailed)
= .018. There were no differences in terms of the proportion of accident or
"other" visits. Again the close parallels between the findings from
the Health Visits—Subjective and Objective measures may be taken as an
indication that the participants' memory of health visits was valid.
Health
Behaviors
There was no difference between the
groups on the degree to which they endorsed the 30 health related behaviors, t(118)=
.13, ns. Comparisons between the two groups on the
three subscales revealed through factor analysis indicated that seminar
participants were significantly more likely to endorse items related to diet
and exercise, t(118)= 2.01, p(one-tailed)
= .047. There were no differences on the other two factors.
Potential
Mediators of the Health Effects
In order to maximize the sensitivity of
the outcome measures in the search for mediators, the three major significant
findings were combined. Z scores were calculated for Physical
Symptoms—Prospective, Global Health Rating, and Health
Visits—Subjective and summed to create a new variable labeled overall health effect. Analyses of mediation for depression (BDI),
explanatory style (ASQ), hopelessness (HPS), and dysfunctional attitudes (DAS)
were then performed with this variable.
Only depression (BDI) was found to be a
significant mediator of group to health (see Table 2). There was an effect of group on BDI,
which remained significant after the effect of health was partialled out. There
was also an effect of BDI on health, and the effect of group on health was
reduced when the effect of BDI was partialled out. A chi-square analysis (Olkin & Finn, 1990) revealed that
depression was a significant mediator of the relationship between group and
health, c 2(1, N= 99) = 3.20, .025 < p<
.05.
In turn, hopelessness was found to
mediate the relationship between group and BDI (see Table 3. There was an effect of group on HPS,
which remained significant after the variance attributable to BDI was
partialled out. There was an effect of HPS on BDI, and the effect of group on
BDI decreased after the effect of HPS was partialled out. A chi-square analysis
revealed that hopelessness was a significant mediator of the relationship
between group and depression, c 2(1, N= 119) = 4.67, .0125 < p<
.025.
Discussion
The central hypothesis that participants
who received cognitive behavioral depression prevention training would experience
fewer physical symptoms and report fewer doctors’ visits was confirmed. This
study also fulfilled the criteria for establishing a causal relation between a
psychological trait and physical health outcomes. These three criteria were the
longitudinal nature of the study, the adequate time span used, and the multiple
measures of physical health.
There were three measures of physical
symptoms in this study: the Physical Symptoms-Retrospective questionnaire, the
Physical Symptoms-Prospective questionnare, and the health rating made by the
APEX evaluators using the structured LIFE interview. Seminar participants were
found to be experiencing fewer physical symptoms on both the Daily
Questionnaire and the Health Rating Measure. This extends on the work ofPeterson (1988) who found that optimists
reported fewer physical symptoms than did pessimists in the Virginia
Polytechnic Study. No differences were found on the Physical
Symptoms-Retrospective Questionnaire; however, the Prospective—Daily
Questionnaire is a sounder measure as it did not rely on 2 weeks of memory.
The physical symptoms results also
extended the findings ofLin and Peterson (1990) andPeterson, Colvin, and Lin (1992), who reported
that pessimists were more passive in the face of ill health. Although the
control participants did make more illness-related visits (i.e., an active
stance), they also suffered more physical symptoms (thus necessitating more
visits) and generally responded in a passive manner more frequently than did
the seminar participants. Additionally, the Health Behaviors Questionnaire
indicated that seminar participants were taking more active steps to protect
their health, at least in terms of diet and exercise.
This study used two measures of doctor’s
visits: a self-report of visits made to all physicians and an objective record
of visits made to Student Health. There was an effect of the training program
on the number of doctor’s visits with seminar participants reporting fewer
visits. Again, this extended on the work ofPeterson (1988) who found that optimists made
fewer doctors visits than pessimists. On the objective measure of Student
Health visits, no difference between the groups was found. Similarly, when the
subjective data was code for location of visit, no difference between the
groups was obtained for reported visits to the Student Health. It can thus be
concluded that the difference in terms of overall number of visits made is the
result of the control participants making more visits outside of Student
Health. This is problematic because although the participantive data indicate
that the control participants did make more outside doctor’s visits, attempts
to objectively verify these reports were not successful. Attempts to confirm
visits made outside of Student Health through mailings and follow-up phone
calls met with an approximately 15% response rate. Therefore, the possibility
exists that control participants did not make more outside visits, but merely
overreported the number of visits made (or seminar participants underreported).
This is an interesting question in itself that can be answered in part by
comparing the reported number of Student Health visits with the actual number
made. Both groups underreported the number of Student Health visits made
(seminar: subjective, 0.57; objective, 0.67; control: subjective, 0.70; objective,
0.82). The overall accuracy of the two groups was virtually identical; both
seminar and control participants recalled approximately 85% of their visits to
Student Health. There appears no reason to believe that this level of accuracy
should be different when it comes to visits outside of Student Health, and
thus, although it cannot be verified, we believe that the control participants
did indeed make more doctors visits than seminar participants.
When visits were coded for type of
visit, it was found that the control participants both reported making more
illness visits and did make more illness visits to Student Health. This is
noteworthy as it suggests that the control participants were experiencing more
physical illness. An equally noteworthy finding was that the seminar
participants showed a trend toward making more check-up visits. This suggests
that the seminar participants were taking better care of themselves.
One final finding from the data on
visits was that the subjective number of visits was affected by the time the
participants entered the study. Specifically, the greater the duration between
the conclusion of the APEX seminar and the beginning of the Health Extension,
the fewer the visits reported. This finding was consistent across both
groups—there was no Group × Time interaction. It is believed that
the effect for time is simply the result of memory. For example, participants
who entered the APEX Project in the fall of 1991 were asked to recall visits
over a 30-month period, and they recalled fewer visits per semester than did
participants asked to recall visits over a shorter time span.
How did depression prevention result in
better physical health? The analyses of mediation showed empirically that
depression clearly plays a role. High levels of depression across groups
predicted poorer physical health. As the cognitive-behavioral intervention
significantly reduced and prevented depression, those participants in the
seminar condition would be expected to reap the health benefits of this reduced
depression.
We can also speculate on why reduced
depression might lead to better physical health:
§
Depression leads to immunosuppression (Schleifer, Keller, Siris, Davis, & Stein, 1985),
so it is possible that the health differences between the two groups were the
result of a depression-induced decrease in immune functioning in the control
participants. This may be the case, as the majority of symptoms the
participants reported, and the majority of illness visits they made, were
related to infectious illness (e.g., strep throat, mononucleosis, influenza,
etc.). We did not measure immune response.
§
Depressed individuals also suffer more
uncontrollable events, and the more uncontrollable events one experiences, the
more likely one will become ill (Rabkin & Struening, 1976). It is possible
that the APEX seminar taught the participants to be better problem solvers, and
thus they experienced fewer events that they could not handle. Unfortunately,
we have no measurement of the number of negative events experienced by the
participants and thus this must remain speculative.
§
Depression also produces passivity, and
passivity about physical health will produce further health problems. In this
current study, a difference in the level of depression between the groups was
mediated by HPS, a measure of passivity. Perhaps the seminar participants were
less hopeless and simply took better care of themselves. That is, as a result
of participating in the APEX seminar, they took a proactive, rather than a
reactive, stance to their problems, including their physical health. Three of
the findings indicated that seminar participants were taking better care of
themselves (checkup visits, active response to symptoms, and diet and exercise
habits). This attitude, in turn, should lead to fewer health problems in that
health habits reduce the incidence of physical illness.
The nature of the suspected link between
the degree to which participants took care of themselves and the amount of
illness they experienced needs to be assessed more closely.Peterson et al., (1992) provided evidence that
a participant's response (active or passive) to a cold has no effect on the
duration of the cold. But perhaps prior action may have prevented the cold in
the first place. We need to examine what it is that participants do (or what
they can do) to prevent illness and whether these behaviors are effective and
more common among seminar participants. We also need to track these
participants for longer periods. Although the time interval between the end of
the APEX seminar and the beginning of the Health Extension study was long
enough to detect some group differences, greater differences may emerge over
time. There is also a world of difference between having a sore throat or a
cold and developing cancer or heart disease. It remains to be seen whether the
benefits of the APEX Project will persist across a longer time and reduce the
incidence of these more chronic and serious illnesses in the seminar
participants.
A general shortcoming of this study is
the overall paucity of physical illness and symptoms in the population studied.
It may, therefore, be beneficial to administer the cognitive-behavioral seminar
to an older, and potentially less healthy, population. Further, we are in the
process of following this population over the next five years beyond college,
when the baseline incidence of physical illness rises.
Before concluding, it is necessary to
address the issue of nonparticipation. As mentioned, over half of the
participants who took part in the APEX Project declined participation in the
Health Extension. While participants and nonparticipants did not differ in
terms of group assignment and pessimism, depression and hopelessness pre- and
post-APEX, it is possible that they differed in terms of physical health. At
this point we may only speculate that this was not the case. When initially
asked to participate in the Health Extension, participants were not informed
that it concerned their physical health thus ruling-out the possibility that
“sicker” participants opted out of the study because they did not want to
reveal their health status. In fact, the primary reasons given for
non-participation were lack of time and lack of incentive (the monetary
compensation for the Health Extension was quite modest compared with the
payment for APEX participation).
In conclusion, by randomly assigning
pessimistic students to a control group or a prevention group that reduced
depression, we found that prevention training caused better physical health. We
speculate that learning the skills that prevent depression improved physical
health by causing the students to take a more pro-active stance toward physical
illness.
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1By the spring of 1994, 7
participants had dropped out of the APEX Project, while 5 were still part of
the project, but were enrolled at different schools. Additionally, 8
participants were studying abroad at the time the Health Extension began
leaving a potential pool of 211. Of these, 14 were never reached (despite
persistent efforts), while 9 agreed to participate, but never showed up
although they were rescheduled three times. The largest decrease in the
participant pool was the result of students who declined participation.
Sixty-five of the original APEX participants opted not to participate in the
Health Extension. Participants did not differ from nonparticipants in terms of
BDI pre- and post-APEX, CPCN pre- and post-APEX, and group assignment (seminar
vs. control).
Correspondence
concerning this article should be addressed to Martin E. P. Seligman,
Department of Psychology, University of Pennsylvania 3815 Walnut Street,
Philadelphia, PA 19104
E-mail: seligman@psych.upenn.edu
Table 1. Means and Standard
Deviations of Health and Apex Measures for Seminar and Control Participants
Table 2. Analysis of Depression as
a Potential Mediator of the Relationship Between Group and Overall Health
Table 3. Analysis of Hopelessness
as a Potential Mediator of the Relationship Between Group and Depression