Journal of Consulting and Clinical Psychology 1978, Vol. 46, No. S, 854-859
Mood, Pleasant Events, and Unpleasant Events: Two Pilot Studies Lynn P. Rehm University of Pittsburgh The relationship between mood and both pleasant and unpleasant events is assessed in two studies. Undergraduates made self-ratings of mood and kept daily logs of pleasant and unpleasant events for approximately 2 weeks. Intrasubject correlations in both studies suggested that mood was related to pleasant and unpleasant events independently. Intersubject correlations were consistent but nonsignificant. Cross-lagged correlations were significantly less than same-day correlations. Weighted event scores produced marginally higher correlations with mood than unweighted scores. Minor sex differences are noted. The implications of these results for theory and practice are discussed.
A common assumption in the behavioral literature on depression is that mood is a function of reinforcement (e.g., Ferster, 1973; Lewinsohn, 1974). Although some basic questions relating to the precise definition of reinforcement in daily life remain unanswered, empirical relationships have been obtained between mood and pleasurable events or activities that have a likely correspondence to reinforcement. Using the Pleasant Events Schedule (MacPhillamy & Lewinsohn, Note 1), a 320-item list empirically developed to assess potentially reinforcing events in daily experience, intraindividual correlations have been demonstrated between mood and number of pleasant events (Lewinsohn & Graf, 1973; Lewinsohn & Libet, 1972). Depressed persons have been found to report fewer pleasant events than nondepressed psychiatric and normal groups (MacPhillamy & Lewinsohn, 1974). Wener and Rehm (1975) demonstrated a causal relationship between manipulated rate of positive feedback in a laboratory task and subsequent mood. The writing of this article was supported in part by National Institute of Mental Health Grant MH27822. Requests for reprints should be sent to Lynn P. Rehm, Clinical Psychology Center, 606 Old Engineering Hall, University of Pittsburgh, Pittsburgh, Pennsylvania 1S260.
Self-monitoring of mood and pleasant events has been a part of a number of treatment programs for depression with a variety of rationales and functions. Lewinsohn's (1974) clinical research program employed the Pleasant Events Schedule as a means of empirically selecting targets for behavioral intervention. Events that correlate with mood for a specific individual are increased in order to influence mood (Lewinsohn, 1976). Fuchs and Rehm (1977) developed the Positive Activities Schedule, consisting of 20 categories of instrumental behavior likely to be associated with reinforcement. Depressed subjects kept a log of their daily activities using the schedule as a guide. Logs were used as a basis for self-selection of target behaviors and were also assumed to be an intervention in and of themselves, that is, an intervention modifying depressive, pessimistic self-monitoring. Anton, Dunbar, and Friedman (1976) used activity logs as part of a therapy program that included scheduling of individual reinforcing activities. Enjoyability ratings of each activity logged were described as a potential dependent variable. Ad hoc activity schedules were used in three case studies described by Rush, Khatami, and Beck (197S). Activity data were used to confront clients' cognitively distorted interpretation of their behavior. Another ad hoc use of activity logs
Copyright 1978 by the American Psychological Association, Inc. 0022-006X/78/4605-0854$00.75
854
MOOD AND EVENTS
855
Table 1 Average Mood and Events Data Across Subjects: Study 1 Females11
Males" Variable
Mean daily mood rating Mean daily pleasant events Mean daily unpleasant events a
Total
M
SE
M
SE
M
4..91
.76 1.05 1.36
5 .99 4.,12 2.,51
.76 1.66 1.28
5.63 3.97 2.62
3, 66 2. 85
SE .91 1.48 1.29
n = 10. n = 20.
b
was described by McLean (1976), who used them primarily to assess improvement in behavioral productivity as one alternative component of therapy for depression. Given the widespread use of pleasant event or activity monitoring in depression therapy programs and the empirical support for the relationship between pleasant events and mood, it is somewhat surprising that only activities associated with reward have been studied. All of the research cited has dealt with "pleasant events" or "positive activities," yet aversive events have been related to depression in a number of ways. Aversive, stressful life events have been found to precede clinical depression (cf. Dohrenwend & Dohrenwend, 1974). Seligman (1975) has demonstrated empirically that noncontingent aversive events lead to a state of learned helplessness, which he associates with depression. Lewinsohn, Lobitz, and Wilson (1973) found that depressed persons were particularly sensitive to aversive events. It would seem logical that mood would be related to aversive events in the daily life of normal persons. Two pilot studies were conducted to explore the feasibility of assessing the relationship between unpleasant events and mood in a manner that could be adapted to clinical usage. In both studies events were listed by individuals in positive or negative columns on a daily log with a general definition as a guide. Pleasant events were defined as any event that is pleasant, enjoyable, or rewarding, and unpleasant events were defined as any event that is unpleasant, aversive, or punishing. Mood was assessed on a daily basis on a 0-10 rating scale, anchored at 0 = worst
mood ever to 10 = best mood ever. This scale was adopted for simplicity and ease of administration. Aitken (1969; Aitken & Zealley, 1970) described the use of a similar simple scale that correlated well with psychiatric ratings of depression. In both studies subjects were instructed to make their mood ratings and then fill out the events logs daily at the end of the day. Study 1 Method Log sheets and standard instructions were given as a class assignment to 33 undergraduates enrolled in a psychology course. Usable data were obtained from 30 subjects (10 males and 20 females) who kept logs for approximately 2 weeks (1 for 13 days, 13 for 14 days, IS for IS days, and 1 for 16 days).
Results The actual events recorded varied somewhat in specificity and type. Some sample pleasant events that were recorded by students included "read Sunday paper," "good lunch," "sunny day," "letter from Adrienne," "bought albums," "good grade on bio test," "Joni Mitchell concert," "party," "saw good movie," "got high," and "complimented by Mrs. F." Some examples of unpleasant events were "bio test," "dentist appointment," "got parking ticket," "missed bus," "got blister playing squash," "Pitt lost game," "argument with roommate," "did the laundry," and "dull Geography class." Means for data collected are shown in Table 1. Males' ratings of their mood were significantly lower than those for females, £(28) = 3.66, p < .01. Differences in number
LYNN P. REHM
856 Table 2
Average Intraindiiridual Correlations: Study 1 M
Correlated variables
Mood and pleasant events Mood and unpleasant events Pleasant and unpleasant events
Mood and events (R)
Males"
1
Females '
.65
.55
-.36 -.15
-.48 -.28
.75
.68
With previous Total" .58 -.45 -.22
.70
events
0
.11 -.11
— —
With subsequent events
0
.15 .00 — —
"ra = 10. b n = 20. 0 n = 30.
of events were not significant though in directions consistent with the mood differences. Mean correlations were calculated using Fisher's 2 transformation and were then converted back to Pearson product-moment correlations. No significant differences in correlations were found between sexes. Looking at the total group, the average correlations between pleasant and unpleasant events with mood were all statistically significant. The relatively low, negative, average correlation between the two classes of events suggests that pleasant and unpleasant events make relatively independent contributions to mood. The average multiple correlations for pleasant and unpleasant events correlated with mood (see Table 2) were larger than either single correlation and this further suggests mood is a function of both pleasant and unpleasant events. Lcwinsohn and Libet (1972) posed the question of whether mood would be affected by the previous day's activity or whether mood would affect the subsequent day's activity. This question can be answered by looking at correlations between mood and events of the previous clay and between mood and events of the subsequent day. Table 2 shows that these mean cross-lagged correlations are quite low and comparable to those obtained by Lewinsohn and Libet. The same-day correlations were significantly larger than those for mood and events of the previous day: For mood and pleasant events, t ( 2 9 ) — 9.30, p < .01; for mood and unpleasant events, t ( 2 9 ) = S.40, p < .01, or for those for mood
and events of the subsequent day, for mood and pleasant events, t ( 2 9 ) — 6.55, p < .01; for mood and unpleasant events, £ ( 2 9 ) = 5.95, p < .01. Thus there was no indication of causality from events of one day to mood on the next or from the mood of one day to the events of the next. Lewinsohn and Libel's finding for pleasant events and mood was replicated and extended to unpleasant events as well. Although the methodology is directed toward intrasubject questions, intersubject data can also be derived. For the 30 subjects, average mood correlated .31 with average pleasant events and —.28 with average unpleasant events. The multiple correlation between mood and both event scores was .57. These data are consistent with the intrasubject data, though only the latter correlation is statistically significant (dj — 28, p < .01). A correlation of .46 (df = 28, p < .05) between average pleasant and average unpleasant events suggests individual differences in list length for this self-monitoring format. Study 2 The second study had three purposes: (a) to replicate the first study with regard to monitoring pleasant events; (b) to determine whether a value weighting for each event would yield an obtained reinforcement measure that would enhance correlations with mood; and (c) to determine whether perceived contingency contributes to mood correlations.
MOOD AND EVENTS
857
Table 3 Average Mood and Events Data Across 14 Subjects: Study 2 Raw score
Variable Mean daily mood ratings Mean daily pleasant events Mean daily unpleasant events
Contingent score
Weighted score
M
SE
M
.Vfi
M
5.83 5.53 3.68
.80 1.96 1.71
32.52 21.00
12.51 10.60
19.33 11.22
SE
7.66 8.27
Method
= 2.050, p < .05, than subjects in Study 1. These differences may be due to a different Thirty-four undergraduates enrolled in a psyset acquired from the class discussion of the chology course were assigned a choice of projects, one of which was to participate in this study. Four- project or to self-selection differences. In teen students elected to participate and kept moni- either case they do not effect the hypotheses toring data for 14 days. Instructions were the same in question. as in Study 1, except for the addition of weighting Mean correlations between mood and and perceived contingency instructions. After recording each event, subjects were instructed to give events (see Table 4) were slightly smaller it a value on a 0-10 scale. For pleasant events, 10 but comparable to those obtained in Study 1. was to signify "an extremely enjoyable or pleasant Again, pleasant and unpleasant events were event," and for unpleasant events, 10 was to signify uncorrelated with each other on the average, "an extremely aversivc or unpleasant event." Zero but each contributed to mood variance. signified neutrality on either scale. To assess perceptions of contingency, participants The use of weightings enhanced the averwere asked to indicate how many of the value points age intraindividual correlations to a minor assigned to each event were directly attributable to degree. A comparison of pairs of correlations themselves or their own behavior (i.e., their effort or lack of effort or their skills or lack of skill). This with mood between unweighted and weighted pleasant events scores indicated that the method allowed for a more continuous assessment of degree of perceived response contingency than would weighted correlations were larger to a mara dichotomous yes or no. Attribution research (cf. ginally significant degree, J(13) = 1.809, Weiner et al., 1971) suggests that such judgments p < .05, one-tailed. The increase in the mean are continuous. unpleasant events correlation with weighting was not significant, 2(13) = 1.240. Thus the Results evidence suggests that weighting event scores The average daily mood rating for these may have only a slight value in identifying subjects was 5.83, which corresponds closely relationships with mood more accurately. The average correlations of mood and with Study 1. Subjects in this study (see self-attributed points were of the same magTable 3) recorded more events, both pleasant, < ( 4 2 ) = 2.652, p < .05, and unpleasant £ ( 4 2 ) nitude as the correlations between mood and Table 4 Average Intrasubject and Inter subject Correlations: Study 2 Intersubject M
Intrasubject M Correlated variables Mood and pleasant events Mood and unpleasant events Pleasant and unpleasant events Mood and events (R)
Raw scores .51
-.35 .08 .70
Weighted Contingent scores scores .59
-.41 -.01 .75
.52 -.27
.03 .70
Raw scores
.12 -.13
.71 .33
Weighted Contingent scores scores .18 -.12 .62 .34
,09 -.13 .50 .22
858
LYNN P. REHM
number of events. No particular advantage appears to accrue from specifying reinforcement value that is perceived as contingent on the person's own behavior. Again it is notable that the average correlation between pleasant and unpleasant events was close to zero. Each class of events appears to contribute to mood independently. Average multiple correlations between mood and both sets of event scores (Table 4) bear out this assertion, As can be seen in Table 4, interindividual correlations between mood and events were in the predicted directions but were quite small and not statistically significant. Correlations between pleasant and unpleasant events scores were significant for raw scores (p < .01) and weighted scores (p < .05). These suggest significant individual differences in reporting rates for pleasant and unpleasant events even though these classes are relatively independent within subjects. Multiple correlations for mood with the events scores combined were again consistent with intrasubject findings but were not statistically significant. It is particularly interesting that perceived contingent 'event scores do not enhance correlations with mood. As an additional way of examining whether perceived contingency is related to mood, a ratio of self-attributed points to total weighted scores was calculated for each subject for both pleasant and unpleasant events. Averaged across all individuals, 59.4% of the value of pleasant events was self-attributed, whereas 49.5% of the value of unpleasant events was self-attributed. Correlations between these ratios and average mood would indicate whether subjects who tend to attribute a greater proportion of their pleasant or unpleasant events value to themselves would be more or less depressed than subjects who see these events as less contingent. The correlation between the ratio of perceived contingent pleasant events and mood was —.14. The correlation between the ratio of perceived contingent unpleasant events and mood was .004. Needless to say, neither was significant. Thus there was no evidence that tendency to perceive contingency between events and behavior influenced mood in this study.
Discussion These two studies suggest that even with this simple methodology, it is feasible to assess the relationships between mood and events, both pleasant and unpleasant, in meaningful ways. Despite individual differences in recording rates, pleasant and unpleasant events were recorded with relative independence, and each correlated with mood. The magnitude of correlations between mood and pleasant events using these less structured methods was comparable to that obtained by Lewinsohn and Libet (1972) and Lewinsohn and Graf (1973). Although the correlations with unpleasant events were regularly of a lesser magnitude, they nevertheless make a significant additional contribution to mood. Evidence from the second study suggests that a simple scaling of event magnitude contributes only marginally to greater precision in identifying relationships between mood and events. Differentiating the value by the degree to which events are self-attributed did not seem to contribute to correlations with mood for either pleasant or unpleasant events. Events are related to mood whether contingent on one's own behavior or entirely external in origin. Thus there appears to be a potential clinical value to self-monitoring unpleasant as well as pleasant events in conjunction with behavior therapy for depression. Unpleasant events that correlate with mood may also be appropriate target activities for modification (Lewinsohn, 1976). The data generated by monitoring unpleasant events may also contribute to helping clients make more accurate discriminations about functional relationships between their behavior and their mood. As a result, they may be able to make more realistic evaluations and set more realistic goals via techniques analogous to those used by Fuchs and Rehm (1977) or Rush et al. (1975). Certain qualifications must accompany these conclusions. First, these studies should indeed be considered as only promising pilot studies. Problems concerning the precise definition and validity of unpleasant events remain, as they remain for pleasant event re-
MOOD AND EVKNTS
cording. Further basic research is certainly necessary. Second, these studies suggest potential for monitoring unpleasant events only in terms of intrasubject investigations. Intersubject correlations were largely nonsignificant; individual differences in recording rates were evident; and sex differences were obtained. The development of structured methods for assessing unpleasant events, parallel to those available for assessing pleasant events, may allow for valid nomothetic studies. Reference Note 1. MacPhillamy, D., & Lcwinsohn, P. M. The Pleasant Events Schedule. Unpublished manuscript, University of Oregon, 1971.
References Aitken, R. C. B. Measures of feeling using analogue scales. Proceedings oj the Royal Society oj Medicine, 1969, 62, 989-993. Aitken, R. C. B., & Zealley, A. K. Measurement of mood. British Journal oj Hospital Medicine, 1970, 4, 214-224. Anton, J. L., Dunbar, J., & Friedman, L. Anticipation training in the treatment of depression. In J. D. Krumboltz & C. E. Thoresen (Eds.), Counseling methods. New York: Holt, Rinehart & Winston, 1976. Dohrenwcnd, B. P., & Dohrenwend, B. S. (Eds.). Stressful life events: Their nature and effects. New York: Wiley, 1974. Fcrster, C. B. A functional analysis of depression. American Psychologist, 1973, 28, 857-870. Fuchs, C. Z., & Rehm, L. P. A self-control behavior therapy program for depression. Journal of Consulting and Clinical Psychology, 1977, 45, 206-215.
859
Lcwinsohn, P. M. A behavioral approach to depression. In R. M. Friedman & M. M. Katz (Eds.), The psychology oj depression: Contemporary theory and research. New York: Wiley, 1974. Lewinsohn, P. M. Activity schedules in treatment of depression. In J. D. Krumboltz & C. E. Thoresen (Eds.), Counseling methods. New York: Holt, Rinehart & Winston, 1976. Lewinsohn, P. M., & Graf, M. Pleasant activities and depression. Journal oj Consulting and Clinical Psychology, 1973, 41, 261-268. Lewinsohn, P. M., & Libet, J. Pleasant events, activity schedules and depression. Journal oj Abnormal Psychology, 1972, 79, 291-295. Lewinsohn, P. M., Lobitz, W. C., & Wilson, S. Sensitivity of depressed individuals to aversive stimuli. Journal oj Abnormal Psychology, 1973, 81, 259263. MacPhillamy, D. J., & Lewinsohn, P. M. Depression as a function of levels of desired and obtained pleasure. Journal of Abnormal Psychology, 1974, 83, 651-657. McLean, P. Therapeutic decision-making in the behavioral treatment of depression. In P. 0. Davidson (Ed.), The behavioral management oj anxiety, depression and pain. New York: Brunner/Mazel, 1976. Rush, A. J., Khatami, M., & Beck, A. T. Cognitive and behavior therapy in chronic depression. Behavior Therapy, 1975, 6, 398-404. Seligman, M. E. P. Helplessness: On depression, development and death. San Francisco: Freeman, 1975. Weiner, B, et al. Perceiving the causes oj success and failure. Morristown, N.J.: General Learning Press, 1971. Wener, A. E., & Rehm, L. P. Depressive affect: A test of behavioral hypotheses. Journal oj Abnormal Psychology, 1975, 84, 221-227. Received March 2, 1977 •
Mood, Pleasant Events, and Unpleasant Events: Two Pilot Studies Lynn P. Rehm University of Pittsburgh The relationship between mood and both pleasant and unpleasant events is assessed in two studies. Undergraduates made self-ratings of mood and kept daily logs of pleasant and unpleasant events for approximately 2 weeks. Intrasubject correlations in both studies suggested that mood was related to pleasant and unpleasant events independently. Intersubject correlations were consistent but nonsignificant. Cross-lagged correlations were significantly less than same-day correlations. Weighted event scores produced marginally higher correlations with mood than unweighted scores. Minor sex differences are noted. The implications of these results for theory and practice are discussed.
A common assumption in the behavioral literature on depression is that mood is a function of reinforcement (e.g., Ferster, 1973; Lewinsohn, 1974). Although some basic questions relating to the precise definition of reinforcement in daily life remain unanswered, empirical relationships have been obtained between mood and pleasurable events or activities that have a likely correspondence to reinforcement. Using the Pleasant Events Schedule (MacPhillamy & Lewinsohn, Note 1), a 320-item list empirically developed to assess potentially reinforcing events in daily experience, intraindividual correlations have been demonstrated between mood and number of pleasant events (Lewinsohn & Graf, 1973; Lewinsohn & Libet, 1972). Depressed persons have been found to report fewer pleasant events than nondepressed psychiatric and normal groups (MacPhillamy & Lewinsohn, 1974). Wener and Rehm (1975) demonstrated a causal relationship between manipulated rate of positive feedback in a laboratory task and subsequent mood. The writing of this article was supported in part by National Institute of Mental Health Grant MH27822. Requests for reprints should be sent to Lynn P. Rehm, Clinical Psychology Center, 606 Old Engineering Hall, University of Pittsburgh, Pittsburgh, Pennsylvania 1S260.
Self-monitoring of mood and pleasant events has been a part of a number of treatment programs for depression with a variety of rationales and functions. Lewinsohn's (1974) clinical research program employed the Pleasant Events Schedule as a means of empirically selecting targets for behavioral intervention. Events that correlate with mood for a specific individual are increased in order to influence mood (Lewinsohn, 1976). Fuchs and Rehm (1977) developed the Positive Activities Schedule, consisting of 20 categories of instrumental behavior likely to be associated with reinforcement. Depressed subjects kept a log of their daily activities using the schedule as a guide. Logs were used as a basis for self-selection of target behaviors and were also assumed to be an intervention in and of themselves, that is, an intervention modifying depressive, pessimistic self-monitoring. Anton, Dunbar, and Friedman (1976) used activity logs as part of a therapy program that included scheduling of individual reinforcing activities. Enjoyability ratings of each activity logged were described as a potential dependent variable. Ad hoc activity schedules were used in three case studies described by Rush, Khatami, and Beck (197S). Activity data were used to confront clients' cognitively distorted interpretation of their behavior. Another ad hoc use of activity logs
Copyright 1978 by the American Psychological Association, Inc. 0022-006X/78/4605-0854$00.75
854
MOOD AND EVENTS
855
Table 1 Average Mood and Events Data Across Subjects: Study 1 Females11
Males" Variable
Mean daily mood rating Mean daily pleasant events Mean daily unpleasant events a
Total
M
SE
M
SE
M
4..91
.76 1.05 1.36
5 .99 4.,12 2.,51
.76 1.66 1.28
5.63 3.97 2.62
3, 66 2. 85
SE .91 1.48 1.29
n = 10. n = 20.
b
was described by McLean (1976), who used them primarily to assess improvement in behavioral productivity as one alternative component of therapy for depression. Given the widespread use of pleasant event or activity monitoring in depression therapy programs and the empirical support for the relationship between pleasant events and mood, it is somewhat surprising that only activities associated with reward have been studied. All of the research cited has dealt with "pleasant events" or "positive activities," yet aversive events have been related to depression in a number of ways. Aversive, stressful life events have been found to precede clinical depression (cf. Dohrenwend & Dohrenwend, 1974). Seligman (1975) has demonstrated empirically that noncontingent aversive events lead to a state of learned helplessness, which he associates with depression. Lewinsohn, Lobitz, and Wilson (1973) found that depressed persons were particularly sensitive to aversive events. It would seem logical that mood would be related to aversive events in the daily life of normal persons. Two pilot studies were conducted to explore the feasibility of assessing the relationship between unpleasant events and mood in a manner that could be adapted to clinical usage. In both studies events were listed by individuals in positive or negative columns on a daily log with a general definition as a guide. Pleasant events were defined as any event that is pleasant, enjoyable, or rewarding, and unpleasant events were defined as any event that is unpleasant, aversive, or punishing. Mood was assessed on a daily basis on a 0-10 rating scale, anchored at 0 = worst
mood ever to 10 = best mood ever. This scale was adopted for simplicity and ease of administration. Aitken (1969; Aitken & Zealley, 1970) described the use of a similar simple scale that correlated well with psychiatric ratings of depression. In both studies subjects were instructed to make their mood ratings and then fill out the events logs daily at the end of the day. Study 1 Method Log sheets and standard instructions were given as a class assignment to 33 undergraduates enrolled in a psychology course. Usable data were obtained from 30 subjects (10 males and 20 females) who kept logs for approximately 2 weeks (1 for 13 days, 13 for 14 days, IS for IS days, and 1 for 16 days).
Results The actual events recorded varied somewhat in specificity and type. Some sample pleasant events that were recorded by students included "read Sunday paper," "good lunch," "sunny day," "letter from Adrienne," "bought albums," "good grade on bio test," "Joni Mitchell concert," "party," "saw good movie," "got high," and "complimented by Mrs. F." Some examples of unpleasant events were "bio test," "dentist appointment," "got parking ticket," "missed bus," "got blister playing squash," "Pitt lost game," "argument with roommate," "did the laundry," and "dull Geography class." Means for data collected are shown in Table 1. Males' ratings of their mood were significantly lower than those for females, £(28) = 3.66, p < .01. Differences in number
LYNN P. REHM
856 Table 2
Average Intraindiiridual Correlations: Study 1 M
Correlated variables
Mood and pleasant events Mood and unpleasant events Pleasant and unpleasant events
Mood and events (R)
Males"
1
Females '
.65
.55
-.36 -.15
-.48 -.28
.75
.68
With previous Total" .58 -.45 -.22
.70
events
0
.11 -.11
— —
With subsequent events
0
.15 .00 — —
"ra = 10. b n = 20. 0 n = 30.
of events were not significant though in directions consistent with the mood differences. Mean correlations were calculated using Fisher's 2 transformation and were then converted back to Pearson product-moment correlations. No significant differences in correlations were found between sexes. Looking at the total group, the average correlations between pleasant and unpleasant events with mood were all statistically significant. The relatively low, negative, average correlation between the two classes of events suggests that pleasant and unpleasant events make relatively independent contributions to mood. The average multiple correlations for pleasant and unpleasant events correlated with mood (see Table 2) were larger than either single correlation and this further suggests mood is a function of both pleasant and unpleasant events. Lcwinsohn and Libet (1972) posed the question of whether mood would be affected by the previous day's activity or whether mood would affect the subsequent day's activity. This question can be answered by looking at correlations between mood and events of the previous clay and between mood and events of the subsequent day. Table 2 shows that these mean cross-lagged correlations are quite low and comparable to those obtained by Lewinsohn and Libet. The same-day correlations were significantly larger than those for mood and events of the previous day: For mood and pleasant events, t ( 2 9 ) — 9.30, p < .01; for mood and unpleasant events, t ( 2 9 ) = S.40, p < .01, or for those for mood
and events of the subsequent day, for mood and pleasant events, t ( 2 9 ) — 6.55, p < .01; for mood and unpleasant events, £ ( 2 9 ) = 5.95, p < .01. Thus there was no indication of causality from events of one day to mood on the next or from the mood of one day to the events of the next. Lewinsohn and Libel's finding for pleasant events and mood was replicated and extended to unpleasant events as well. Although the methodology is directed toward intrasubject questions, intersubject data can also be derived. For the 30 subjects, average mood correlated .31 with average pleasant events and —.28 with average unpleasant events. The multiple correlation between mood and both event scores was .57. These data are consistent with the intrasubject data, though only the latter correlation is statistically significant (dj — 28, p < .01). A correlation of .46 (df = 28, p < .05) between average pleasant and average unpleasant events suggests individual differences in list length for this self-monitoring format. Study 2 The second study had three purposes: (a) to replicate the first study with regard to monitoring pleasant events; (b) to determine whether a value weighting for each event would yield an obtained reinforcement measure that would enhance correlations with mood; and (c) to determine whether perceived contingency contributes to mood correlations.
MOOD AND EVENTS
857
Table 3 Average Mood and Events Data Across 14 Subjects: Study 2 Raw score
Variable Mean daily mood ratings Mean daily pleasant events Mean daily unpleasant events
Contingent score
Weighted score
M
SE
M
.Vfi
M
5.83 5.53 3.68
.80 1.96 1.71
32.52 21.00
12.51 10.60
19.33 11.22
SE
7.66 8.27
Method
= 2.050, p < .05, than subjects in Study 1. These differences may be due to a different Thirty-four undergraduates enrolled in a psyset acquired from the class discussion of the chology course were assigned a choice of projects, one of which was to participate in this study. Four- project or to self-selection differences. In teen students elected to participate and kept moni- either case they do not effect the hypotheses toring data for 14 days. Instructions were the same in question. as in Study 1, except for the addition of weighting Mean correlations between mood and and perceived contingency instructions. After recording each event, subjects were instructed to give events (see Table 4) were slightly smaller it a value on a 0-10 scale. For pleasant events, 10 but comparable to those obtained in Study 1. was to signify "an extremely enjoyable or pleasant Again, pleasant and unpleasant events were event," and for unpleasant events, 10 was to signify uncorrelated with each other on the average, "an extremely aversivc or unpleasant event." Zero but each contributed to mood variance. signified neutrality on either scale. To assess perceptions of contingency, participants The use of weightings enhanced the averwere asked to indicate how many of the value points age intraindividual correlations to a minor assigned to each event were directly attributable to degree. A comparison of pairs of correlations themselves or their own behavior (i.e., their effort or lack of effort or their skills or lack of skill). This with mood between unweighted and weighted pleasant events scores indicated that the method allowed for a more continuous assessment of degree of perceived response contingency than would weighted correlations were larger to a mara dichotomous yes or no. Attribution research (cf. ginally significant degree, J(13) = 1.809, Weiner et al., 1971) suggests that such judgments p < .05, one-tailed. The increase in the mean are continuous. unpleasant events correlation with weighting was not significant, 2(13) = 1.240. Thus the Results evidence suggests that weighting event scores The average daily mood rating for these may have only a slight value in identifying subjects was 5.83, which corresponds closely relationships with mood more accurately. The average correlations of mood and with Study 1. Subjects in this study (see self-attributed points were of the same magTable 3) recorded more events, both pleasant, < ( 4 2 ) = 2.652, p < .05, and unpleasant £ ( 4 2 ) nitude as the correlations between mood and Table 4 Average Intrasubject and Inter subject Correlations: Study 2 Intersubject M
Intrasubject M Correlated variables Mood and pleasant events Mood and unpleasant events Pleasant and unpleasant events Mood and events (R)
Raw scores .51
-.35 .08 .70
Weighted Contingent scores scores .59
-.41 -.01 .75
.52 -.27
.03 .70
Raw scores
.12 -.13
.71 .33
Weighted Contingent scores scores .18 -.12 .62 .34
,09 -.13 .50 .22
858
LYNN P. REHM
number of events. No particular advantage appears to accrue from specifying reinforcement value that is perceived as contingent on the person's own behavior. Again it is notable that the average correlation between pleasant and unpleasant events was close to zero. Each class of events appears to contribute to mood independently. Average multiple correlations between mood and both sets of event scores (Table 4) bear out this assertion, As can be seen in Table 4, interindividual correlations between mood and events were in the predicted directions but were quite small and not statistically significant. Correlations between pleasant and unpleasant events scores were significant for raw scores (p < .01) and weighted scores (p < .05). These suggest significant individual differences in reporting rates for pleasant and unpleasant events even though these classes are relatively independent within subjects. Multiple correlations for mood with the events scores combined were again consistent with intrasubject findings but were not statistically significant. It is particularly interesting that perceived contingent 'event scores do not enhance correlations with mood. As an additional way of examining whether perceived contingency is related to mood, a ratio of self-attributed points to total weighted scores was calculated for each subject for both pleasant and unpleasant events. Averaged across all individuals, 59.4% of the value of pleasant events was self-attributed, whereas 49.5% of the value of unpleasant events was self-attributed. Correlations between these ratios and average mood would indicate whether subjects who tend to attribute a greater proportion of their pleasant or unpleasant events value to themselves would be more or less depressed than subjects who see these events as less contingent. The correlation between the ratio of perceived contingent pleasant events and mood was —.14. The correlation between the ratio of perceived contingent unpleasant events and mood was .004. Needless to say, neither was significant. Thus there was no evidence that tendency to perceive contingency between events and behavior influenced mood in this study.
Discussion These two studies suggest that even with this simple methodology, it is feasible to assess the relationships between mood and events, both pleasant and unpleasant, in meaningful ways. Despite individual differences in recording rates, pleasant and unpleasant events were recorded with relative independence, and each correlated with mood. The magnitude of correlations between mood and pleasant events using these less structured methods was comparable to that obtained by Lewinsohn and Libet (1972) and Lewinsohn and Graf (1973). Although the correlations with unpleasant events were regularly of a lesser magnitude, they nevertheless make a significant additional contribution to mood. Evidence from the second study suggests that a simple scaling of event magnitude contributes only marginally to greater precision in identifying relationships between mood and events. Differentiating the value by the degree to which events are self-attributed did not seem to contribute to correlations with mood for either pleasant or unpleasant events. Events are related to mood whether contingent on one's own behavior or entirely external in origin. Thus there appears to be a potential clinical value to self-monitoring unpleasant as well as pleasant events in conjunction with behavior therapy for depression. Unpleasant events that correlate with mood may also be appropriate target activities for modification (Lewinsohn, 1976). The data generated by monitoring unpleasant events may also contribute to helping clients make more accurate discriminations about functional relationships between their behavior and their mood. As a result, they may be able to make more realistic evaluations and set more realistic goals via techniques analogous to those used by Fuchs and Rehm (1977) or Rush et al. (1975). Certain qualifications must accompany these conclusions. First, these studies should indeed be considered as only promising pilot studies. Problems concerning the precise definition and validity of unpleasant events remain, as they remain for pleasant event re-
MOOD AND EVKNTS
cording. Further basic research is certainly necessary. Second, these studies suggest potential for monitoring unpleasant events only in terms of intrasubject investigations. Intersubject correlations were largely nonsignificant; individual differences in recording rates were evident; and sex differences were obtained. The development of structured methods for assessing unpleasant events, parallel to those available for assessing pleasant events, may allow for valid nomothetic studies. Reference Note 1. MacPhillamy, D., & Lcwinsohn, P. M. The Pleasant Events Schedule. Unpublished manuscript, University of Oregon, 1971.
References Aitken, R. C. B. Measures of feeling using analogue scales. Proceedings oj the Royal Society oj Medicine, 1969, 62, 989-993. Aitken, R. C. B., & Zealley, A. K. Measurement of mood. British Journal oj Hospital Medicine, 1970, 4, 214-224. Anton, J. L., Dunbar, J., & Friedman, L. Anticipation training in the treatment of depression. In J. D. Krumboltz & C. E. Thoresen (Eds.), Counseling methods. New York: Holt, Rinehart & Winston, 1976. Dohrenwcnd, B. P., & Dohrenwend, B. S. (Eds.). Stressful life events: Their nature and effects. New York: Wiley, 1974. Fcrster, C. B. A functional analysis of depression. American Psychologist, 1973, 28, 857-870. Fuchs, C. Z., & Rehm, L. P. A self-control behavior therapy program for depression. Journal of Consulting and Clinical Psychology, 1977, 45, 206-215.
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Lcwinsohn, P. M. A behavioral approach to depression. In R. M. Friedman & M. M. Katz (Eds.), The psychology oj depression: Contemporary theory and research. New York: Wiley, 1974. Lewinsohn, P. M. Activity schedules in treatment of depression. In J. D. Krumboltz & C. E. Thoresen (Eds.), Counseling methods. New York: Holt, Rinehart & Winston, 1976. Lewinsohn, P. M., & Graf, M. Pleasant activities and depression. Journal oj Consulting and Clinical Psychology, 1973, 41, 261-268. Lewinsohn, P. M., & Libet, J. Pleasant events, activity schedules and depression. Journal oj Abnormal Psychology, 1972, 79, 291-295. Lewinsohn, P. M., Lobitz, W. C., & Wilson, S. Sensitivity of depressed individuals to aversive stimuli. Journal oj Abnormal Psychology, 1973, 81, 259263. MacPhillamy, D. J., & Lewinsohn, P. M. Depression as a function of levels of desired and obtained pleasure. Journal of Abnormal Psychology, 1974, 83, 651-657. McLean, P. Therapeutic decision-making in the behavioral treatment of depression. In P. 0. Davidson (Ed.), The behavioral management oj anxiety, depression and pain. New York: Brunner/Mazel, 1976. Rush, A. J., Khatami, M., & Beck, A. T. Cognitive and behavior therapy in chronic depression. Behavior Therapy, 1975, 6, 398-404. Seligman, M. E. P. Helplessness: On depression, development and death. San Francisco: Freeman, 1975. Weiner, B, et al. Perceiving the causes oj success and failure. Morristown, N.J.: General Learning Press, 1971. Wener, A. E., & Rehm, L. P. Depressive affect: A test of behavioral hypotheses. Journal oj Abnormal Psychology, 1975, 84, 221-227. Received March 2, 1977 •
