This meta analysis provides evidence for a strong relationship between restriction of social and recreational activities and increased severity of depressive symptoms, in support of the activity restriction model of depressed affect (Williamson, 2000
; Williamson & Shaffer, 2000
). Interestingly, although behavioral models of depression have been well-known over the past 4 decades, examination of the relationship between activity restriction and depression is relatively new. In fact, half of the articles described in our analyses were published since 2006, and nearly one-third were published in 2009–2010. This increase in research attention likely coincides with the continued aging of the U.S. population, and an increased awareness of the impact of medical illnesses associated with aging on the emotional health of patients and their families. Indeed, over 75% of the studies included in this meta-analysis had samples with a mean age ≥55 years, and nearly half had a mean sample age ≥65 years.
The mean correlation between activity restriction and depressive symptoms across the 34 studies was 0.39, and this effect varied across selected moderators. Results of our secondary analyses indicated that the activity restriction/depressive symptoms relationship was strongest among medical patient populations, with an average effect size of 0.45. A particularly important aspect of this finding is that depressive symptoms are a known predictor of poor clinical outcomes in a variety of medical populations. For example, elevated symptoms of depression have been associated with 5-year, event-free chance of survival among patients with cancer (Watson, Haviland, Greer, Davidson, & Bliss, 1999
), a 2-fold risk of emergency room visits and 29% increase in total health care costs in patients with heart failure (Rutledge, Reis, Linke, Greenberg, & Mills, 2006
), and increased risk for morbidity and mortality among those with coronary artery disease (Burg, Benedetto, Rosenberg, & Soufer, 2003
; Burg, Benedetto, & Soufer, 2003
). Further, elevated depressive symptoms have been linked to functional decline (Lenze et al., 2005
) and poorer rehabilitation outcomes in medical patients (Lenze et al., 2004
; Lenze et al., 2007
). Although these results suggest that depression plays a role in negative health outcomes, it is still unclear whether this relationship is causal in nature. Still, demonstration that activity restriction may be a significant contributor to depressive symptoms in medical patients suggests that psychosocial/behavioral therapies, such as behavioral activation therapy, which emphasize re-engagement in pleasurable activities, may be particularly efficacious in these populations and may aid in producing residual benefits to health, well-being, and rehabilitation outcomes. Indeed, behavioral activation therapy, relative to other efficacious treatments for depression, specifically targets activity restriction through its emphasis on activating the patient toward engaging in more pleasurable activities (Jacobson, Martell, & Dimidjian, 2001
An important limitation of the secondary moderator analyses is that significant heterogeneity existed within some of the moderator groups. For the study population moderator, studies conducted with medical patients and community-dwelling adults displayed significant heterogeneity in effect size. Although the moderator analysis suggests that medical populations exhibit a stronger relationship between AR and depression overall, the heterogeneity within this group means that it cannot be assumed that AR will be an equally effective target for depression intervention for all types of medical patients. Some of the heterogeneity within the medical patient group may be because patients with a wide variety of medical problems were studied (e.g., cancer, osteoarthritis, limb amputation, chronic pain). Effect sizes for the relationship between AR and depression may differ across these subgroups of medical populations. For example, it appears that effect sizes were generally smaller for patients with osteoarthritis and larger for medical populations such as cancer patients; however, there were too few studies investigating each individual medical condition to examine each of these subgroups separately. It is also notable that, although the variation among illnesses was broad among medical patients, some common conditions were not represented. For instance, no studies focusing on patients with cardiovascular diseases, such as heart failure, were included in this review, despite the association with these illnesses and both depression and activity restriction. Therefore, these findings may not be applicable across the range of medical conditions. Future research might examine additional moderators to determine which subsets of medical populations display stronger relationships between AR and depression. Additional moderators should also be investigated in the population of community-dwelling individuals, which also displayed significant heterogeneity in effect sizes in this analysis.
Likewise, for quality of AR assessment, there was significant heterogeneity in the low quality AR assessment group and the medium quality AR assessment group, potentially impacting post-hoc analyses. Given that there was not significant heterogeneity in the high quality AR assessment group, these results possibly reflect the higher reliability in higher quality AR assessments. This observation suggests that future studies may benefit from the use of higher quality assessment of AR.
Additionally, to examine whether the larger effect size in medical patients as compared to caregiving and community-dwelling populations was related to differences in AR assessment quality, we examined the frequency with which each study population group used high quality AR assessments. Studies with medical patients did not use higher quality AR measures relative to studies with caregivers. However, studies with community-dwelling populations were less likely to use high quality AR measures than studies in medical patient or caregiver populations. Therefore, the lower effect size for the relationship between AR and depression observed in community-dwelling samples must be interpreted with caution, as this decreased effect size may be a result of poor quality AR measurement. This finding further reinforces the need for using high quality assessments of AR in future research, especially in community-dwelling populations.
A strong relationship between activity restriction and depression was also observed among caregivers of medical patients, with a mean effect size of 0.34. Indeed, high rates of depression have been observed in caregivers (Mahoney, Regan, Katona, & Livingston, 2005
; Schulz, O’Brien, Bookwala, & Fleissner, 1995
), and depressive symptoms have been reported to increase caregivers risk for cardiovascular illnesses (Mausbach, Patterson, Rabinowitz, Grant, & Schulz, 2007
) as well as emergency department visits and hospitalization (Schubert et al., 2008
). However, empirically validated treatments for reducing distress in caregivers exist (Gallagher-Thompson & Coon, 2007
), and many emphasize re-engagement in pleasurable activities and reduction of activity restriction as a primary treatment target.
As the studies reported here were cross-sectional, it is important to note that the direction of the relationship between activity restriction and depression may be bidirectional. It is possible that activity restriction may contribute to the onset of depression, and that, once depressed, a variety of symptoms (e.g., depressed mood, insomnia, anergia) may maintain or further worsen activity restriction. Indeed, Lewinson and colleagues (Lewinsohn & Graf, 1973
) have posited that loss of contact with positive reinforcement and avoidance related behaviors combine to produce and maintain depression, and our meta-analysis provides evidence these fundamental behavioral processes may account for substantial degree of depression across populations experiencing different life stressors. Longitudinal research is needed to identify the critical periods in the activity restriction, depression, and disablement cycle in which to intervene, particularly the earliest point at which prevention of depression may be possible.
Nevertheless, the primary clinical implication of this study is that it may be advisable to screen for activity restriction in routine clinical encounters in addition to depression in their patients. This would serve not only to help determine risk for depression in those who are currently experiencing subsyndromal depression, but also aid in determining treatment options. Specifically, in patients with both depression and activity restriction, behavior therapies may be utilized in conjunction with medication treatments to reduce depression. In patients with high activity restriction but subsyndromal depressive symptoms, primary care providers may consider ongoing monitoring of depression and/or recommend depression-prevention therapies. As a note, we found that quality of activity restriction assessments explained variability in the activity restriction/depression relationship. Thus, we advise against basic assessment methods such as asking whether or not patients restricted activities, and suggest more psychometrically sound methods yet brief scales be utilized such as the Activity Restriction Scale (Williamson & Schulz, 1992
In sum, activity restriction appears to be a significant correlate of depressive symptoms across a variety of populations, with largest effect in individuals with medical illnesses. More work is needed to delineate the mechanisms and direction of causality between activity restriction on depression, in order better inform interventions targeting sustaining activities and prevention of depression. Based on the results of this meta-analysis, we recommend routine assessment of activity restriction to determine possible risk for depression, and suggest that psychosocial treatments that address activity restriction may be utilized as an adjunct to medications for treating depressive symptoms.