Sep 6, 2010 - dictor of HRQoL after base control in contrast to De Moor et al. ..... Montgomery GH, David D, Goldfarb AB, Silverstein JH, Weltz CR,. Birk JS, et ...
Jpn J Clin Oncol 2011;41(1)87 – 94 doi:10.1093/jjco/hyq168 Advance Access Publication 6 September 2010
Pessimism Predicts Anxiety, Depression and Quality of Life in Female Cancer Patients Markus Zenger 1,*, Heide Glaesmer 2, Michael Ho¨ckel 2 and Andreas Hinz 1 1
Department of Medical Psychology and Medical Sociology, University of Leipzig and 2Department of Gynecology and Obstetrics, University of Leipzig, Leipzig, Germany *For reprints and all correspondence: Markus Zenger, Department of Medical Psychology and Medical Sociology, University of Leipzig, Philipp-Rosenthal-Str. 55, 04103 Leipzig, Germany. E-mail: markus.zenger@medizin. uni-leipzig.de Received June 7, 2010; accepted August 8, 2010
Objective: The aim of this study was to investigate the predictive value of optimism/pessimism for anxiety, depression and health-related quality of life in female cancer patients, quantified with and without controlling the corresponding base level. Methods: A total of 97 women with breast cancer and other gynaecological cancer completed the Life Orientation Test, the Hospital Anxiety and Depression Scale and the Health Survey SF-8 at three time points: during their stay in the hospital (T1), 2 weeks later (T2) and 3 months later (T3). Results: The degree of self-assessed pessimism at T1 was significantly associated with anxiety, depression and health-related quality of life at T3. After controlling for the base levels of anxiety, depression and health-related quality of life, only the predictive value of pessimism remained significant and substantial. Conclusions: Especially, women with a high level of pessimism are at risk for higher levels of anxiety and depression in addition to lowered health-related quality of life in the course of the disease. The results indicate that it seems to be more important not to be pessimistic than to be optimistic. Key words: oncology – optimism – anxiety – depression – quality of life
INTRODUCTION Not only invasive medical treatment but also psychological adjustment to a life-threatening disease is required when facing a diagnosis of cancer. Additionally, patients have to cope with the tentativeness of the success of the treatment and the insecurity of the course of their disease. This has a strong impact on psychological outcome variables such as anxiety and depression as well as health-related quality of life (HRQoL). During the last decades, the influence of personality factors such as optimism has attracted growing interest. On the one hand, researchers are interested in the stabilizing effects of protective factors, whereas on the other hand, clinicians are more interested in predisposing markers for vulnerability to adjustment difficulties. At this juncture, optimism is defined as a generalized tendency to expect positive versus negative life outcomes (1). Following the results of many investigations, this tendency causes or at
least co-occurs with remarkable differences between individuals according to their psychological adjustment to stressful life events (2 – 8). Optimism was found to go along with more adaptive and active coping strategies such as problem-focused coping and seeking of social support, whereas a more pessimistic view of individuals is attended by denial and avoiding coping styles in dealing with upcoming problems (9 – 12). In this way, being more optimistic may act as a buffer against stress (4). Moreover, mildly positive self-relevant distortions are supposed to be helpful in coping with critical life events (8). Schou et al. (6, p. 1813) pointed out that optimism affects well-being ‘by influencing how individuals approach and react to critical life situations’. While more active coping styles can lead to a reduction of anxiety through doing something, passive coping styles enhance feelings of anxiety and depressive mood. Optimism is generally hypothesized to be a relatively stable dispositional construct. However, negative life events
# The Author (2010). Published by Oxford University Press. All rights reserved.
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Pessimism predicts anxiety, depression and QoL
may have a destabilizing effect on the level of optimism (13). This might also hold for facing a diagnosis of a lifethreatening disease like cancer, and a comparison of cancer patients with the general population would help to support this assumption. Several studies in cancer patients explored the relationship between optimism and distress, well-being and HRQoL (2 – 6,8,12,14 – 30). However, the results are inconsistent. Studies examining the influence of optimism on distress and depression mostly found a significant predictive value in prospective studies (4,6,17,27,28,30) and in crosssectional studies (2,3,5,15,18,24). On the other hand, there are longitudinal investigations that found optimism not to be a predictor of later distress (25,26). In a more elaborated study design, the predictive value of optimism was controlled for the base levels of distress, anxiety or depression at study entrance (8,16,19,23,29). In three studies (16,23,29), the predictive value of optimism remained significant but small. Contrary to this, De Moor et al. (19) found no additional predictive value of optimism for later distress after base level control in ovarian cancer patients. Using the same kind of statistics, Stiegelis et al. (8) found an additional predictive value of optimism for anxiety, but not for depression. In the field of HRQoL, the current state of research is similarly controversial. While most studies found a substantial correlation between optimism and HRQoL in cancer patient populations (6,14,20,30,31), others studies did not consistently (21,22). Although we can act on the assumption that there are no meaningful differences in the level of optimism and pessimism between men and women (13), in one study, gender differences were found in the relationship of optimism and HRQoL. In the study of Carver et al. (16), optimism remained a significant predictor of HRQoL after base control in contrast to De Moor et al. (19). Furthermore, the magnitude of optimism in cancer patients seems to be unrelated to socio-demographic and cancerspecific characteristics (4,8,12,15,19), even though one study has shown that a higher tumor stage goes along with more optimism in men but not in women (21). Most of the studies mentioned above used the Life Orientation Test (LOT) for measuring optimism versus pessimism as a uni-dimensional construct, but recent studies have shown that optimism and pessimism can be seen as distinct dimensions (13,32– 35). Therefore, in this study, we examine the influence of optimism and pessimism separately, in addition to the uni-dimensional sum scale, especially since recent studies indicated that pessimism is a stronger predictor than optimism for psychological outcome variables (13) and a stronger predictor for mortality in younger cancer patients (27). Robinson-Whelen et al. (13, p. 1352) assume that ‘the widespread use of the LOT as a unidimensional measure might have camouflaged such effects’. The present study has six specific aims: (i) to examine the influence of socio-demographic and cancer-specific
characteristics on optimism and pessimism; (ii) to compare the level of optimism of cancer patients with that of the general population; (iii) to examine the temporal stability of optimism and pessimism up to 3 months after a stressful event in female cancer patients; (iv) to investigate the relationships between optimism and anxiety, depression and HRQoL; (v) to quantify the predictive value of optimism/ pessimism for anxiety, depression and HRQoL with and without controlling the corresponding base level; and (vi) to answer the question whether optimism helps female cancer patients to recover from psychological distress and lowered HRQoL, since studies have shown that more optimistic expectations are associated with more active coping styles.
PATIENTS AND METHODS STUDY DESIGN A sample of 215 patients with gynaecological and breast cancer was recorded for this longitudinal study in the Department of Gynecology and Obstetrics, University Hospital Leipzig (Germany), between September 2007 and November 2008. Information about potential study participants was available from an internal electronic registration system of the hospital. All eligible patients were included in this study if they were at least 18 years old, had histologically proven carcinoma and were able to understand German well enough to answer the questionnaires. Trained interviewers introduced the patients to the aims of this study and afterwards patients had given informed consent. After the initial survey in the hospital (T1), questionnaires were sent by mail 2 weeks (T2) and 3 months (T3) after discharge from hospital. QUESTIONNAIRES Beside socio-demographic and cancer-related parameters, the following questionnaires were adopted: DISPOSITIONAL OPTIMISM The Life Orientation Test (LOT-R) of Scheier et al. (36) was administered to the participants, a six-item scale (along four filler items) containing three items each for positive and negative general life expectations. Patients were asked to indicate the extent to which they agreed with each statement on a five-point Likert scale, ranging from 0 (strongly disagree) to 4 (strongly agree). Even though the LOT was originally composed as a uni-dimensional scale with the endpoints optimism and pessimism, some studies suggest a bi-dimensionality of two independent factors: optimism and pessimism (12,33 – 35). Characteristic values of reliability of the LOT-R are within an acceptable range: Cronbach’s a ¼ 0.78, test– retest reliability ¼ 0.68 (36). The convergent and discriminant validity of the questionnaire was shown to be appropriate (1,34,36). In the present study, separate scores
Jpn J Clin Oncol 2011;41(1)
for optimism and pessimism as well as the total sum score were used. The total sum score was calculated by the addition of raw scores of the optimism subscale and the inverted pessimism raw scores. In the case of missing items, the value was replaced with the rounded mean of the remaining items of the corresponding subscale when at least two items of the scale were answered. REFERENCE DATA The LOT norm data of Glaesmer et al. (37) were used to compare the results of the study population with the German general population. This norm sample consisted of 4938 healthy people who visited primary care institutions for preventative reasons. The influences of gender and age on optimism were found to be marginal. Therefore, we used the calculated overall mean scores. ANXIETY AND DEPRESSION The Hospital Anxiety and Depression Scale (HADS) is a 14-item questionnaire for screening clinically significant anxiety, depression and distress in patients with somatic illness (38). It has been used frequently in other cancer studies and consists of two subscales, anxiety and depression, with seven items each, rated on a four-point Likert scale. The scores of each subscale range from 0 to 21, with higher scores reflecting more severe symptoms. Patients were included for further analysis if they had completed at least six of the seven items of each subscale. Cronbach’s a at 0.80 for the anxiety and 0.80 for the depression subscale has been rated as acceptable (39), and the convergent and discriminant validity of the HADS was found to be satisfactory or good (39). QUALITY OF LIFE The SF-8 is a short screening instrument designed to provide an HRQoL profile (40). It consists of eight items, where each item represents one of the eight subscales of the original version SF-36. In this questionnaire, patients were asked to rate their HRQoL during the last 24 h. Furthermore, a physical component summary (PCS) and a mental component summary (MCS) can be calculated through regression coefficient weights. Scores from each summary measurement range from 0 to 100. Higher scores represent better HRQoL. Several studies have been conducted to demonstrate that the SF-8 meets the standard criteria for the evaluation of the content, construct and criterion validity in the USA (40). The test – retest reliability for the PCS and MCS was 0.88 and 0.82, respectively (40). STATISTICAL METHODS To enhance the validity of the findings, only patients who participated in all three examinations (T1, T2, and T3) were included in the statistical procedure.
89
To examine the differences for statistical significance, the T-test was used at least at the 5% level. Pearson’s correlation coefficients were calculated to analyze the temporal stability of optimism and, furthermore, to examine the relationship of the expressed optimism during the time in the hospital and the experienced anxiety, depression and HRQoL 3 months after discharge. For this last purpose, only data from T1 and T3 were used to allow conclusions to be drawn about a longer time span. More specific details are presented in the Results section. The statistical analysis of the data was conducted with the SPSS 15.0 software.
RESULTS Socio-demographic and cancer-related characteristics of participants are shown in Table 1. Finally, 97 (45.1%) out of 215 eligible patients took part in all three examinations of this study. Participants were mostly living together with a partner. The main intervention was surgery. Half the patients received chemotherapy. In the group of non-respondents (n ¼ 118), 65 patients (30.3%) refused the participation, 31 patients (14.4%) felt too much distress, 5 patients (2.3%) died during the study period, 2 patients (0.9%) were illiterates and 15 (7.0%) failed to answer at least at one of the three occasions or had too many missing values in at least one of the questionnaires. The group of non-respondents was on average 8 years older, had higher tumor stages and differed from the study group relating to the distribution of the tumor locations. THE INFLUENCE OF SOCIO-DEMOGRAPHIC AND CANCER-SPECIFIC CHARACTERISTICS ON LOT AT T1 According to the approximate median, the study population was divided into two age groups, using a cut-off at 55 years. At T1, no significant LOT differences were found between both subgroups. Concerning education, better educated patients (12 years) had higher values in the optimism subscale and lower values in the pessimism subscale, but these differences were not of statistical significance. Four tumor stages were defined on the basis of the TNM classification system (41), using the complete information of tumor size, nodes and metastases in this categorization. Each group within the same tumor stage was as homogenous as possible concerning the survival rate. Group differences were tested using analysis of variance. The only statistical significant difference was found in the pessimism subscale, where patients with tumor stage IV showed more pessimism than the other groups (F ¼ 2.97; P ¼ 0.04). Concerning the time since diagnosis, two groups were compared (8 and .8 weeks). Patients with a time more than 8 weeks experienced since diagnosis showed significant more pessimism (D ¼ 1.03; P ¼ 0.04) than those with a shorter time experienced since diagnosis. To examine the relationship between religiousness and optimism, the patients were asked
Pessimism predicts anxiety, depression and QoL
90
Table 1. Socio-demographic and cancer-related characteristics of the study population Respondents (n ¼ 97)
Non-respondents (n ¼ 118)
Total (n ¼ 215)
Socio-demographic variables Age (years) 55
48 (49.5%)
35 (29.7%)
83 (38.6%)
.55
49 (50.5%)
83 (70.3%)
132 (61.4%)
Mean (SD)
54.0 (12.0)
61.7 (13.6)
58.2 (13.4)
Living with partner Yes
63 (65.0%)
No
33 (34.0%)
Missing
1 (1.0%)
Education 8 years
23 (23.7%)
9 –11 years
42 (43.3%)
12 years
23 (23.7%)
Missing
9 (9.3%)
OPTIMISM AND PESSIMISM FROM T1 GENERAL POPULATION
TO
IN
COMPARISON
The means of the optimism subscale of patients in the three points in time (M1 ¼ 8.9, M2 ¼ 8.7 and M3 ¼ 8.7) and the general population (M ¼ 9.0) were nearly equal (t ranges from 0.40 to 1.24; P . 0.10), whereas patients surprisingly reported less pessimism (general population M ¼ 6.8 compared with study population M1 ¼ 4.6, t ¼ 8.02, P , 0.01; M2 ¼ 4.9, t ¼ 6.81, P , 0.01; and M3 ¼ 4.7, t ¼ 7.49, P , 0.01) and hence higher scores in the sum scale (general population M ¼ 14.2 compared with study population M1 ¼ 16.4, t ¼ 5.98, P , 0.01; M2 ¼ 15.9, t ¼ 4.67, P , 0.01; and M3 ¼ 16.0, t ¼ 4.93, P , 0.01). Similar mean scores over time do not imply the temporal stability on the individual’s level. In order to test the temporal stability of the LOT scores, Pearson’s correlation coefficients of the sum scales were calculated as follows: T1 – T2: r ¼ 0.72 (P , 0.001); T1 – T3: r ¼ 0.71 (P , 0.001); and T2 – T3: r ¼ 0.67 (P , 0.001). THE PREDICTIVE POWER OF OPTIMISM HRQOL
Clinical variables
T3
TO THE
ON
ANXIETY, DEPRESSION
AND
Tumor stage I
31 (31.9%)
29 (24.6%)
60 (27.9%)
II
26 (26.8%)
17 (14.4%)
43 (20.0%)
III
22 (22.7%)
34 (28.8%)
56 (26.1%)
IV
16 (16.5%)
32 (27.1%)
48 (22.3%)
2 (2.1%)
6 (5.1%)
8 (3.7%)
Missing Tumor location Cervix uteri
44 (45.4%)
30 (25.4%)
74 (34.5%)
Breast
16 (16.5%)
35 (29.7%)
51 (23.8%)
Ovar
13 (13.4%)
21 (17.8%)
34 (15.8%)
Corpus uteri
10 (10.3%)
18 (15.3%)
28 (13.0%)
Vulva
7 (7.2%)
2 (1.7%)
9 (4.1%)
Vagina
4 (4.1%)
4 (3.4%)
8 (3.7%)
Retroperitoneum
2 (2.1%)
3 (2.5%)
5 (2.3%)
Tube
1 (1.0%)
5 (4.2%)
6 (2.8%)
Therapy Surgery
76 (78.4%)
Radiation therapy
28 (28.9%)
Chemotherapy
49 (50.5%)
Hormone therapy
7 (7.2%)
Time since diagnosis (days) Mean (SD) Median
238.6 (830.4)
Mean scores of anxiety (HADS-A), depression (HADS-D) and QoL (PCS and MCS) at T3 depending on LOT scores at T1 are shown in Table 2. Special subgroups of patients were constituted to extract the specific influence of optimism versus pessimism. The first categorization was conducted according to Benyamini (32). Primarily, the sample was divided into two subgroups on each disposition using median splits. Later, they were combined to create four groups (2 2). Patients who scored high in the optimism (.9) and low in the pessimism (4) subscale were categorized as ‘True Optimists’, and patients who scored in the opposite direction were categorized as ‘True Pessimists’. The others were called ‘Undifferentiated High Scorer’ if they had high scores in both subscales and ‘Undifferentiated Low Scorer’ if they had low scores in optimism and pessimism. The other classifications of subgroups in Table 2 were based on the separate consideration of both subscales and the sum score. The highest distress scores (anxiety and depression) and the lowest scores for QoL were found in the groups of pessimists (including true pessimists, pessimism solo and pessimism sum score) and ‘Undifferentiated High Scorer’. In contrast to that, ‘True Optimists’ and ‘Non-Pessimists’ had the lowest distress scores and the highest QoL scores of the study sample.
49
SD, standard deviation.
OPTIMISM AS AN INDEPENDENT PREDICTOR OF ANXIETY, DEPRESSION AND HRQOL
whether they were members of a religious community. No significant differences were found between members and non-members.
The aim of the following analysis was 2-fold. The upper part of Table 3 shows correlations between LOT at T1 and anxiety, depression and both QoL scales at T3. The
Mean scores; standard deviations in parentheses; Op, optimism sub-scale; Pe, pessimism sub-scale; PCS, physical component summary; MCS, mental component summary.
51.68 (10.86)
56.17 (10.69) 62.10 (8.61)
55.27 (9.54)
56.04 (11.01)
62.80 (7.65)
50.96 (11.15)
59.79 (9.92)
58.70 (10.29)
54.90 (9.99)
54.58 (10.87) 56.84 (11.17)
61.93 (8.04)
50.89 (10.26) 51.00 (11.77)
63.40 (7.47) MCS
PCS
57.68 (8.96)
54.29 (7.74)
52.34 (10.53)
56.29 (8.55)
6.37 (3.70)
8.02 (4.02) 5.22 (3.32)
4.33 (3.76) 4.11 (3.57) 6.40 (3.84)
4.77 (2.95) 8.14 (4.05)
5.59 (3.81) 5.00 (3.92)
7.10 (3.81) 5.98 (4.00)
4.61 (4.16) 6.78 (4.32) 6.19 (3.60) 3.77 (3.14)
5.33 (3.40) 8.28 (4.60) 8.06 (3.78) 4.38 (2.59)
HADS-depression
HADS-anxiety
48 (49.5%) 49 (50.5%) 45 (46.4%) 52 (53.6%) 53 (54.6%) 44 (45.4%) 18 (18.6%) 18 (18.6%) 34 (35.0%) 27 (27.8%) n (%)
Optimists .16 Pessimists, Pe . 4 Optimists, Op . 9 Undifferentiated Low Scorer: Op 9; Pe 4 Undifferentiated High Scorer: Op . 9; Pe . 4 True Pessimists: Op 9; Pe . 4 True Optimists: Op . 9; Pe 4
Optimism and pessimism scale combined
Table 2. The relationship between optimism at T1 and anxiety, depression and quality of life at T3
Optimism solo
Non-optimists, Op 9
Pessimism solo
Non-pessimists, Pe 4
Sum score
Pessimists 16
Jpn J Clin Oncol 2011;41(1)
91
pessimism subscale and the sum score are substantially associated with psychological distress and QoL. Correlations vary between 0.27 and 0.51 (absolute scores). The pessimism score in the hospital (T1) was the best predictor of anxiety, depression and QoL 3 months later (T3). Using squared correlation coefficients, pessimism explained 25.9% of the variance of anxiety, 15.8% of depression, 7.3% of PCS and 16.2% of MCS. The optimism subscale had no significant predictive value for none of the dependent variables. Since optimism and anxiety, depression and QoL are mutually related, it is important to test the independent contribution of optimism on anxiety, depression and QoL, beyond the initial values of these variables. Therefore, partial correlation coefficients between optimism at T1 and the target variables at T3 were calculated, controlling for the values at T1 (Table 3, lower part). Only the pessimism scale could significantly add explained variance in all questionnaires, with proportions between 15.7% in HADS-A to 6.0% in PCS.
OPTIMISM AS
A
PREDICTOR OF RECOVERY
For the HADS and the SF-8 scales, differences in raw scores between the first and the last assessment were calculated (later assessment score minus earlier assessment score) to indicate the degree of recovery during the study period. Afterwards, correlation coefficients with all LOT subscales (T1) were calculated. Coefficients and significance levels are shown in Table 4. A significant negative correlation was found only for the pessimism subscale and PCS. Table 3. Correlations and partial correlation coefficients of LOT scales at T1 and anxiety, depression and HRQoL at T3 Variables
Optimism
Pessimism
Sum score
r
P value
r
P value
r
P value
HADS-anxiety T3
20.16
0.12
