Psychology and Aging 2014, Vol. 29, No. 3, 601-611
© 2014 American Psychological Association 0882-7974/14/$ 12.00 http://dx.doi.org/10.1037/a0036784
Mediators of the Impact of a Home-Based Intervention (Beat the Blues) on Depressive Symptoms Among Older African Americans Laura N. Gitlin, David L. Roth, and Jin Huang Johns Hopkins University Older African Americans (N = 208) with depressive symptoms were randomly assigned to a home-based nonpharmacologic intervention (Beat the Blues, or BTB) or wait-list control group. BTB was delivered by licensed social workers and involved up to 10 home visits focused on care management, referral and linkage, depression knowledge and efficacy in symptom recognition, instruction in stress reduction techniques, and behavioral activation through identification of personal goals and action plans for achieving them. Structured interviews by assessors masked to study assignment were used to assess changes in depressive symptoms (main trial endpoint), behavioral activation, depression knowledge, formal care service utilization, and anxiety (mediators) at baseline and 4 months. At 4 months, the intervention had a positive effect on depressive symptoms and all mediators except formal care service utilization. Structural equation models indicated that increased activation, enhanced depression knowl edge, and decreased anxiety each independently mediated a significant proportion of the intervention’s impact on depressive symptoms as assessed with 2 different measures (PHQ-9 and CES-D). These 3 factors also jointly explained over 60% of the intervention’s total effect on both indicators of depressive symptoms. Our findings suggest that most of the impact of BTB on depressive symptoms is driven by enhancing activation or becoming active, reducing anxiety, and improving depression knowledge/ efficacy. The intervention components appear to work in concert and may be mutually necessary for maximal benefits from treatment to occur. Implications for designing tailored interventions to address depressive symptoms among older African Americans are discussed. Keywords: depression, mediation models, mental health disparities
Depression in older adults is well recognized as a debilitating condition that heightens the risk for functional decline, comorbid ity, poor quality of life, dementia, and mortality (Ciechanowski et al., 2004; Cuijpers, Beekman, & Reynolds, 2012; Glaser, Robles, Sheridan, Malarkey, & Kiecolt-Glaser, 2003; Lenze et al., 2001). Even mild to moderate symptoms, if not successfully treated, may lead to poor health outcomes and increased health care utilization and costs (Arean, 2006; Glaser et al., 2003; Grabovich, Lu, Tang, Tu, & Lyness, 2010; Lee et al., 2012; Lyness, Chapman, McGriff, Drayer, & Duberstein, 2009). Older African Americans, one of the fastest growing minority segments of the aging population (Institute of Medicine [IOM], 2012), are at risk for depressive symptoms due to their high rates of chronic illnesses (e.g., heart disease, high blood pressure, dia betes) and exposure to other jeopardies and chronic adversities including poor access to needed resources, low income, poor
housing, and unsafe neighborhoods, as well as a history of dis crimination, all factors that increase burdens and risk for depres sion (Arean et al„ 2010; Pickett, Bazelais, & Bruce, 2013). Recent estimates of prevalence rates for this group are higher than the 7% to 15% previously reported (National Institute of Mental Health, 2010; Woodward, Taylor, Abelson, & Matusko, 2013; Zivin, Pirraglia, McCammon, Langa, & Vijan, 2013). In the African American Health Study of 998 community-dwelling Af rican Americans, 21.1% had clinically relevant depressive symp toms (Miller et al., 2004). A survey of 150 older poor African Americans attending outpatient rehabilitation found that 30% scored positively for depression (Kurlowicz, Outlaw, Ratcliffe, & Evans, 2005). Similarly, in a survey of 153 urban African Amer ican senior center members, 24.2% reported mild to moderate depressive symptoms (Gitlin, Harris, McCoy, Chemet, Jutkowizt, Pizzi, 2012). Of 440 temporarily homebound older African Amer icans evaluated for depressive symptoms, 31% (n = 137) screened positively for mild to severe symptoms (Gitlin, Harris, et al., 2012 ). Nevertheless, older African Americans with depressive symp toms continue to be underdiagnosed and undertreated in primary care and mental health clinics (Arean & Uniitzer, 2003; Tai-Seale, McGuire, Colenda, Rosen, & Cook, 2007). Contributing to their underrepresentation in depression care are system- (lack of access to treatment and trained health providers) and person- (stigma, lack of knowledge about symptoms, lack of trust of providers) level factors (Conner et al., 2010; Ell, 2006; Gum et al., 2009). Studies also show that older African Americans may prefer nondrug ap-
Laura N. Gitlin, School of Nursing Center for Innovative Care in Aging, Johns Hopkins University; David L. Roth and Jin Huang, Center on Aging and Health, Division of Geriatric Medicine and Gerontology, Johns Hop kins University. Clinicaltrials.gov: NCT00511680; National Institutes of Mental Health #R01 MH 079814. Correspondence concerning this article should be addressed to Laura N. Gitlin, Johns Hopkins University School of Nursing Center for Innovative Care in Aging, Johns Hopkins University, 525 Wolfe Street, Suite 316, Baltimore, MD, 21205. E-mail: [email protected] 601
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proaches and have poorer compliance to drug therapies than their White counterparts (Kales et al., 2012). Moreover, drug therapies may not be as effective for those with mild to moderate symptoms and of short duration (Nelson, Delucchi, & Schneider, 2013). Although a growing evidence base supports the use of nonpharmacologic approaches including collaborative and integrated care models (Uniitzer et al., 2002) and psychotherapies (Lee et al., 2012; Peng, Huang, Chen, & Lu, 2009; Scogin, 2005; Wilson, Mottram, & Vassilas, 2008), their efficacy for minority popula tions has not been extensively examined (Fuentes & Aranda, 2012). Thus, a limited evidence base and persistent mental health disparities have prompted a national call for new models of care that address access and treatment preferences for nondrug ap proaches and which evaluate mechanisms by which approaches are effective for minority populations (Alexopoulos & Bruce, 2009; Bartels & Naslund, 2013; Callahan & Hendrie, 2010). Over the past decade, novel promising nonpharmacologic com munity and home-based care models have been tested. A system atic review of 23 effective models revealed that most were multicomponent and included care management and a behavioral approach such as problem solving, cognitive-behavioral or behav ioral activation therapies, addressed unmet needs and provided participants specific skills to cognitively reframe and manage situational stressors such as poor health, housing, or social needs (Gitlin, 2014). These models are unified in their attempts to identify and tackle the multiple contextual factors that may con tribute to or reinforce poor mood and which drug treatments cannot address (Frederick et al., 2007; Fuentes & Aranda, 2012; Gitlin, 2014). These models are also unified in their adoption of a social ecological framework for understanding the etiology of depres sion. This framework favors a behavioral explanation that links mood to daily life stressors and seeks to address contextual triggers of depressive symptoms such as unmet health and care manage ment needs as well as helping participants become behaviorally activated and also reengage in meaningful or pleasant activities (Kanter et al., 2010; Meeks, Looney, van Haitsma, & Teri, 2008; Scogin, Morthland, Kaufman, Chaplin, & Kong, 2011). To address depressive symptoms in urban, low-income older African Americans, we developed and tested the Beat the Blues (BTB) program. This multicomponent home-based intervention was informed by previously effective interventions and findings from focus group and in-depth interviews conducted for the pur poses of this trial to identify preferred treatment approaches. Treatment components included: care management (identifying unmet needs and deriving a plan of action), referral and linkage (making referrals to formal care and social service resources based on the care management assessment), education about depression and symptom recognition (instruction in early detection of symp toms, discussing feelings with physicians and those of a different race, therapeutic modalities including medication use and psycho therapy), stress reduction techniques (instruction in different ap proaches including deep breathing or counting, to reduce situationalinduced anxiety), and behavioral activation (identifying daily routines, a behavioral goal, an action plan, introducing pleasant events in routines). As keeping busy and being engaged in activity was identified in focus groups and in-depth interviews as preferred coping mechanisms, we included behavioral activation as a treat ment component versus more cognitive-based therapies such as
structured problem solving (Agarwal, Hamilton, Crandell, & Moore, 2010). Each component was designed to address situa tional conditions that may be reinforcing depressed mood for this low resource population. Addressing unmet health management and daily living needs through care management and a behavioral activation plan may be particularly salient for this group (Arean et al., 2010). For example, this might include setting a goal for disease self-management and an action plan for how to achieve that goal which specifies the necessary behavioral steps. Tested in a randomized trial involving 208 older African Amer icans, we found that study participants receiving the BTB program reported reduced severity in depressive symptoms with 43.8% in BTB versus 26.9% in the control group (p = .020) in remission by 4 months. Following treatment, control group participants demon strated benefits (4 to 8 months) similar in magnitude to the ad justed treatment effects for BTB participants in the first 4 months; and the initial BTB group maintained 4-month benefits at 8 months (Gitlin et al., 2013). Although mounting evidence supports multicomponent, non drug, behavioral treatment approaches, the active ingredient(s) by which these approaches have their desired effects is unclear. Also unclear is whether all treatment components are necessary for benefits to be realized. Mediation analysis provides an analytic framework for evaluating underlying mechanisms or how inter ventions may work, whether intervention components are neces sary, which components may need to be strengthened, and how to enhance intervention efficiency and design more effective and replicable treatments (Gitlin et al., 2000; Kraemer, Kieman, Essex, & Kupfer, 2008; Roth & MacKinnon, 2012). With few exceptions, mediational processes have not been ex amined in depression trials. Only a few caregiver studies address ing depression have examined mediators. These studies suggest different mediational processes may be operative depending upon treatment properties. A problem solving therapy for stroke care givers found that perceived health, threat appraisals and use of rational problem solving significantly mediated the intervention effect on caregiver depressive symptoms (King et al., 2012). A counseling and support intervention for spouse caregivers of per sons with dementia found that positive change in satisfaction with one’s social support network mediated a significant proportion of the impact of the intervention on caregiver depression; and this was further mediated by changes in caregiver stress appraisals (Roth, Mittelman, Clay, Madan, & Haley, 2005). Only one trial to our knowledge that tested a home-delivered cognitive-behavioral therapy with 134 participants, most of whom were African American, has examined mediational processes. Scogin et al. (2007) found that although their intervention im proved quality of life, cognitive and behavioral variables were not impacted and hence they did not mediate the positive benefits of the intervention. Thus, it remains unclear as to the underlying mechanisms re sponsible for the effectiveness of home-based nonpharmacologic treatment approaches to reduce depressive symptoms in older adults, and specifically for African Americans. In this study, we applied a mediational framework to understand the active ingre dients) of BTB. We examined four possible mediators of BTB’s impact on depressive symptoms: a measure of the change in levels of behavioral activation, or the extent to which participants be come actively engaged; a measure of the change in depression
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knowledge and confidence in recognizing and managing symp toms; a measure of the change in anxiety levels; and a measure of formal care service utilization. These measures served as indica tors of or broadly corresponded to each of the five intervention components; behavioral activation, depression knowledge/efficacy, stress reduction, and care management/ referral/ linkage respectively. As we did not have a direct measure of engagement in stress reduction techniques, we used state anxiety as an indica tor. Also, as we did not have a direct measure of care management and referral/linkage components, we examined formal care service utilization as one indicator of these intervention processes. The treatment components of BTB were conceptualized to com plement and work in concert with each other. Thus, we expected each indicator of mediation to independently and significantly contribute to reducing depressive symptoms. We further expected that their joint effect would be even greater than their individual contributions.
Method Participants As described in depth elsewhere (Gitlin, Harris, et al., 2012; Gitlin et al., 2013), a total of 208 African Americans were enrolled in the trial. Participants were >: 55 years of age, English speaking, cognitively intact (Mini Mental Status Examination > 24), and scored > 5 on the Patient Health Questionnaire (PHQ-9), a mea sure of depressive symptoms, on two sequential testing occasions. Other enrollment criteria to enhance study retention included hav ing a home telephone and planning to live in the area for 8 months. Individuals were not eligible with a history of serious mental illness, life-limiting illnesses, involvement in another clinical de pression trial, or who lived in assisted living or nursing home facilities. Antidepressant or other medication use did not exclude participation. The trial reflected a partnership between a senior center and an academic research center who shared recruitment, interviewing, and intervention responsibilities. Recruitment targeted individuals enrolled in a short-term in-home support program for medically compromised individuals through ongoing systematic screening, and the community at-large through media announcements and presentations at local events and social agencies. Analyses for this present study were based on 179 participants (86.1%) who were retained through the 4-month assessment and provided complete data for all variables of interest in the mediation analyses. Of the 29 with incomplete data, 26 did not complete the 4-month follow-up (missing PHQ-9, CES-D and all mediators), one participant had missing data on the depression knowledge scale, one participant had missing data for both the behavioral activation and anxiety scales, and one had missing data for the CES-D and mediators. A comparison of the 179 participants in cluded in the analyses to the 29 participants who were not, re vealed no large or statistically significant differences at baseline on basic characteristics, indicators of mediation, and the two mea sures of depressive symptoms which were the outcome variables (all ps > .05). Participants recruited from the two venues (in-home support group and community at-large) differed at baseline along certain characteristics as anticipated. The in-home group (n = 51) partic
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ipants were older, had more pain and more health conditions (ps < .05) compared to the community at-large group (n = 128). For baseline depression measures, the two groups had similar PHQ-9 scores but did differ on CES-D scores (p = .04). The in-home group reported on average less symptomatology (M = 13.06, SD = 6.08) than the community at-large group (M = 15.09, SD = 5.73) on the CES-D, although both groups scored in a high range of symptomatology indicative of clinical depression. The groups did not statistically differ on the four measures of mediation. As we used a stratified randomization scheme based on recruitment source (in home support group vs. community at-large), all groups were comparable at baseline; that is, no large or statistically significant differences were found at baseline between the in-home participants assigned to experimental and control groups nor be tween the community at-large participants assigned to experimen tal and control groups.
Procedure Enrollment procedures included two sequential depression screenings of individuals by trained senior center staff over 2 weeks using the Patient Health Questionnaire (PHQ-9). Those eligible (PHQ-9 a 5) and willing to participate in the trial pro vided written consent using an approved Institutional Review Board (IRB) form, completed a baseline home interview, and were then randomized to receive BTB immediately or 4 months later (wait-list control). All participants were reassessed at 4 and 8 months in their homes using the same interview battery conducted by assessors masked to participant group allocation. Participants did not incur any study-related expenses and were provided $15 for completion of each interview (baseline, 4 and 8 months) to recognize their time and participation in the study. This article used data from the baseline and 4-month assess ments.
Intervention Beat the Blues. The Beat the Blues intervention involved up to 10, 1-hr sessions that occurred at home over 4 months and was conducted by licensed social workers who were trained in the protocol. The first few sessions focused on building rapport and assessing for unmet care management needs from which to derive a plan of action including referral and linkage to formal care, community and social services. Interventionists also educated par ticipants about depressive symptoms and specifically, the link between behavior and mood, how to identify the onset of depres sive symptoms and use specific strategies to manage symptoms early on including having discussions about symptoms with phy sicians and when physicians are of a different race. Participants also learned about the effects of stress and how to use a basic deep breathing technique before or during stressful points in the day. In the next few sessions, interventionists helped participants resolve identified unmet care management needs (medical, housing re pairs, relocation needs, social, financial, benefits/entitlements), and worked on care management plans involving coordination, and referral and linkages to services if necessary. Additional stress reduction techniques (e.g., counting, music) were also introduced to provide other easy-to-use stress-reduction tools to address sit uational anxiety. In Sessions 4 and 5, interventionists continued
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addressing care management needs and began behavioral activa tion exercises. First, interventionists reviewed daily routines and helped participants select a behavioral goal and a specific activity to add pleasure and personal satisfaction to daily or weekly rou tines. Active problem solving and motivational interviewing tech niques helped participants achieve identified activity goals. Poten tial barriers to carrying out selected activities were identified and solutions derived that might also have required care management (arranging transportation) to engage in desired activities. Sessions 6 - 8 involved reinforcement of activity engagement, identification of new activity goals and specific steps to achieve them. In Sessions 9 and 10, interventionists reviewed and reinforced all techniques, continued to help participants identify activity goals, break them down to achievable steps, and learn this process for future independent use. All participants received all five treatment components. The content of each component reflected or was tailored to the partic ipants’ specific care management and referral/linkage needs, level of depression knowledge and ability to recognize symptoms, pre ferred stress reduction techniques, and self-identified goals and behavioral activation plans. For example, although all participants were exposed to stress reduction techniques, if a participant ex pressed a preference, that particular technique was reinforced. Similarly, all participants were exposed to the same behavioral activation steps but the specific goals and action steps identified were individualized. Further, the treatment components were in tegrated such that a care management need could be the basis of a behavioral activation goal (e.g., preparing and eating the right foods to manage diabetes), and depression knowledge/efficacy was linked to self-management and becoming actively engaged in one’s own health care. Interventionists presented each of their assigned cases in weekly one-on-one supervisor meetings and biweekly group debriefing sessions to assure protocol adherence and to review care management, referral/linkage and behavioral activation plans. Approximately seven sessions involved care management and behavioral activation, five sessions involved teaching and practic ing a stress reduction technique, and about four sessions involved referral and linkage and depression knowledge/efficacy (Gitlin et al., 2013). Wait-list control group. The wait-list control group did not receive any study-related intervention or contact following the baseline interview. Participants in this group, as those in the BTB group, were free to engage in any nonstudy services, depression treatments or programs they chose. After completing the 4-month assessment, participants received BTB in its entirety and as deliv ered to the initial group. This study examined mediational pro cesses at 4 months only given that by 8 months, all participants received the intervention.
Measures Measures included the following background characteristics: marital status (not married/married, living as married), living ar rangement (alone/with others), sex, education (< high school, high school or > high school level of education), age, financial diffi culty (0 = not very difficult to 3 = very difficult paying fo r basics), self-reported health conditions, and use of depression, anxiety, or pain medications (yes/no).
Outcome Variable The primary dependent variable was depressive symptoms (main trial endpoint). We used two different scales with psycho metric adequacy for African Americans in order to examine the robustness of our effects across two measures that tapped into slightly different types of depressive symptoms (Huang, Chung, Kroenke, Delucchi, & Spitzer, 2006; Nguyen, Kitner-Triolo, Ev ans, & Zonderman, 2004). The PHQ-9 provided a brief, psychometrically sound 9-item self-report severity measure (Kroenke & Spitzer, 2002). As the scale was administered on two subsequent occasions 2 weeks apart to determine eligibility, the second screen was used as the participants’ baseline value for the present anal yses. A total severity score was calculated by summing responses across the nine items which were rated as occurring not at all (0), several days (1), more than half the days (2), or nearly every day (3). Possible scores ranged from 0-27 (Cronbach’s alpha = .78 for this sample). We also used the 10-item Center for Epidemiology Studies Depression Scale (CES-D; Santor & Coyne, 1997). Participants indicated symptomatology in the past week (0 = rarely/never, 3 = most or all o f time). Scores were summed across items (range = 0-30) with a score > 8 indicative of clinical symptoms. Higher scores indicated greater symptomatology (a = .77 for this sample). There is some overlap of items for the CES-D and PHQ-9 (e.g., sleep quality, felt sad). However, CES-D items tend to emphasize affective components (e.g., felt lonely, enjoyed life), whereas PHQ-9 items tend to emphasize somatic aspects (e.g., poor appe tite, trouble concentrating or moving, or speaking slowly) of depressed mood.
Indicators of Mediation The measures used as mediating variables included depression knowledge/efficacy, state anxiety, behavioral activation, and for mal care service utilization. We assessed depression knowledge/efficacy using 10-items re flecting symptom awareness (“can identify depression symptoms”) and efficacy (“know how to explain feelings”) rated from 1 = not at all confident to 4 = absolutely confident. A total mean score was derived by summing across items and dividing by the number of items (range = 1-4). Higher scores represented greater knowl edge/efficacy (a = .72 for this sample; Cretin, Shortell, & Keeler, 2004). To measure anxiety, we used the 10-item State Anxiety Scale. Participants rated feelings (“I felt calm,” “tense”) from 1 = very much to 4 = not at all. A total anxiety score was computed as the mean across all items (a = .85 for this sample). Higher scores indicated greater anxiety (Speilberger, Gorsuch, Lushene, Vagg, & Jacobs, 1983). Activation was assessed using a modification of the Behavioral Activation Scale which included eliminating 14 items (“My work/ schoolwork suffered . . . ”) that were not relevant to this sample and rewording three items to heighten their relevance. Participants rated the resulting 17-items from 0 = not at all to 6 = completely. Items reflect broad content including positive engagement (“ac complished goal,” “engaged in activities,” “did things even though hard because fit with goals”), avoidance of difficult situations (“there were certain things that I needed to do that I didn’t do”), or
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dwelling on negative feelings (“. . . spent time thinking about my past, people who have hurt me, mistakes I’ve made”). A total activation score was computed as the mean across items (a = .83 for this sample). Higher scores indicated greater activation (Kanter, Mulick, Busch, & Berlin, 2007). The use/nonuse of formal care services in the past month was measured by 14 items reflecting four service types: psychosocial (e.g., talking to clergy, social worker, counselor, psychologist, psychiatrist, attending support groups), home health (e.g., assis tance with daily chores, self-care), social (e.g., transportation), and health care (e.g., physician visits, outpatient clinics) services. A total utilization index was computed by summing the number of services used.
group (in-home support group and community at-large) separately. As consistent results across mediators and outcomes were found, we only report analyses for the entire sample. After the mediators were examined individually, those that were identified as statistically significant mediators were examined si multaneously to test for independent versus overlapping mediation effects. The c’ from those models represented any intervention effect on depressive symptoms that was independent of the other mediating mechanisms and was used to calculate a jointly medi ated proportion. All statistical analyses were conducted using Mplus Version 7 (Muthen & Muthen, 2012).
Statistical Analysis
Table 1 provides descriptive data on the background character istics and the baseline measures of behavioral activation, depres sive symptoms, anxiety, and formal care service utilization for the 179 participants included in this study for both the total sample and by treatment assignment. For this sample, participants had a mean age of 69.44 (SD = 8.57). Most were female (N = 142, 79.33%), not employed (N = 164, 91.62%), not married (N = 157, 87.71%), had > high school education (N = 86, 48.04%), lived alone (TV = 106, 59.22%), and reported financial difficulties (N = 121, 67.60%). Participants reported an average of 6.56 (SD = 3.05) health conditions such as high blood pressure (n = 141, 78.77%), high cholesterol (n = 106, 59.22%), arthritis (n = 136, 75.98%), and diabetes (n = 79, 44.13%). Most were not taking medications for mood: 38 (21.35%) reported antidepressant and 29 (16.29%) antianxiety medication use. However, most were on a pain man agement drug (N = 92, 51.69%) suggesting this sample had significant health concerns. Participants reported a moderate level of depressive symptoms on the PHQ-9 (M = 12.87, SD = 4.96) with close to one third expressing mild symptoms, more than one third expressing mod erate symptoms, close to one quarter indicating moderately severe symptoms and about 11% having severe symptoms. Similarly, for the CES-D, participants scored above the clinical cutoff for de pressive symptoms and in the moderate symptom range (M = 14.51, SD = 5.89). As to mediators, participants reported some to moderate anxiety (M = 2.52, SD = 0.65), some confidence recognizing symptoms (M = 3.11, SD — 0.43), low activation (M = 2.89, SD = 1.00), and using an average of four formal services (M = 4.04, SD = 4.90; see Table 1). The correlations among the variables analyzed in the mediation models are displayed in Table 2. As expected, there were signif icant correlations across the different mediating variables, both at baseline and for the 4-month change scores. The two measures of depression were moderately correlated, both at baseline (r = .49) and in terms of changes over time (r = .50). This indicates some overlap, but also differences in the way depressive symptoms were measured in the two instruments (see Table 2).
The general analytic approach to examine the proposed media tors individually is illustrated in Figure 1. The primary aim of the analyses was to determine whether improvements in four mediat ing variables (depression knowledge, anxiety, behavioral activa tion, formal care use) independently and jointly, mediated the beneficial impact of the intervention on depressive symptoms at 4 months. There are multiple ways to statistically test for mediation effects even with relatively straightforward, two-wave (prepost) data from a randomized trial. In particular, the b path illustrated in Figure 1 can fluctuate substantially depending on whether covariated-adjusted change scores or 4-month scores are analyzed as the effects (Roth & MacKinnon, 2012). In our analyses, simple change scores (4 month minus baseline) were calculated for the mediators (behavioral activation, depression knowledge, anxiety, formal care service use) and the depressive symptoms measures (PHQ-9, CES-D). These change scores were then analyzed as a function of their baseline values and the interven tion effect as illustrated in Figure 1. The mediated or indirect effect represents the joint impact of the a and b paths on the outcome, and is estimated as a*b. The c’ path represents unmediated or direct effect, and the sum of a*b and c’ comprises the total (baseline-adjusted) effect of BTB on depressive symptoms. These estimates were tested for statistical significance and used to estimate the proportion of the total effect that could be attributed to that mediator, (a’b)/((a*b)+c’). We also conducted stratified analyses for each recruitment source
Results
Effects of BTB on Depressive Symptoms and Mediators Figure 1. Two-wave mediation model used to examine mediators indi vidually. BL = baseline observation. A = 4-month score minus baseline score.
Using standard analyses of covariance, with the baseline score as the covariate, the BTB intervention was found to have significant effects on both measures of depressive symptoms and on three (all
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Table 1 Baseline Characteristics o f Analytical Sample (N = 179) Characteristic Age Sex, n (%) Male Female Education, n (%) CHS HS/GED >H S Employment status, n (%) Employed Unemployed Paying for basics, n (%) Not difficult at all Not very difficult Somewhat difficult Very difficult Marital status, n (%) Not married Married Number of health conditions Antidepressant medication, n (%) Anxiety medication, n (%) Pain medication, n (%) PHQ-9 Score (second screen) PHQ-9 Score (second screen), n (%) Minimal/no depression (0-4) Mild depression (5-9) Moderate depression (10-14) Moderate/severe depression (15-19) Severe depression (&20) CES-D score Behavioral activation Depression knowledge Anxiety Formal care service use Note.
Total sample (.N = 179)
Treatment group (.N = 86)
Control group (V = 93)
69.44 (8.57)
69.00 (8.70)
69.84 (8.48)
37 (20.67) 142 (79.33)
17(19.77) 69 (80.23)
20 (21.51) 73 (78.49)
40 (22.35) 53 (29.61) 86 (48.04)
18(20.93) 22 (25.58) 46 (53.49)
22 (23.66) 31 (33.33) 40 (43.01)
15 (8.38) 164(91.62)
11 (12.79) 75 (87.21)
4 (4.30) 89 (95.70)
(20.11) (12.29) (38.55) (29.05)
12(13.95) 13(15.12) 33 (38.37) 28 (32.56)
24(25.81) 9 (9.68) 36 (38.71) 24(25.81)
157 (87.71) 22 (12.29) 6.56 (3.05) 38 (21.35) 29(16.29) 92 (51.69) 12.87 (4.96)
72 (83.72) 14(16.28) 6.73 (2.75) 22 (25.58) 12(13.95) 44(51.16) 12.99 (5.27)
85 (91.40) 8 (8.60) 6.40(3.31) 16(17.39) 17(18.48) 48 (52.17) 12.75 (4.67)
0 (0.00) 54 (30.17) 63 (35.20) 41 (22.91) 21 (11.73) 14.51 (5.89) 2.89(1.00) 3.11 (0.43) 2.52 (0.65) 4.04 (4.90)
0 (0.00) 27 (31.40) 30 (34.88) 16(18.60) 13(15.12) 14.53 (5.88) 2.94(1.01) 3.09 (0.46) 2.51 (0.66) 4.36(6.19)
0 (0.00) 27 (29.03) 33 (35.48) 25 (26.88) 8 (8.60) 14.48 (5.93) 2.85(1.00) 3.13 (0.40) 2.53 (0.64) 3.75 (3.31)
p value .51 .77
.35
.04
.18 36 22 69 52
.12
.47 .18 .41 .89 .75 .39
.95 .57 .51 .83 .41
PHQ-9 = Patient Health Questionnaire; CES-D = Center for Epidemiologic Studies-Depression scale.
ps < .0001) of four proposed mediating variables. In each case, the findings indicated that improvements were observed in the BTB group that exceeded any changes observed in the wait-list control group for behavioral activation, depression knowledge/efficacy, and anxiety. There was no intervention effect for formal care service utilization. The significant intervention effects were previously pub lished for the entire sample (Gidin et al., 2013). The estimates for these effects on the mediators comprise the “a” paths in the mediation models and are provided in that column of Table 3.
Single Mediator Models The unstandardized estimates that correspond to the paths illus trated in Figure 1 are reported in Table 3 for each mediator-depressive symptom measure combination. These findings indicate highly sig nificant mediation effects for behavioral activation, depression knowl edge, and anxiety (all ps < .01) for both depression measures. The mediation effects were similar in magnitude, with the proportion mediated effect ranging from .35 to .42.
Multiple Mediator Models The single mediator models indicated that changes in three medi ators (behavioral activation, depression knowledge, and anxiety) ex
plained a portion of the intervention-induced changes on depressive symptoms. Figure 2 displays the standardized estimates of the effects from the model that examined intervention-induced changes on three of these mediators simultaneously and for both depressive symptom measures. Because the “a” paths did not change across the two models for different depressive symptom measures, only one estimate is provided for each “a” path in Figure 2. In both models, the unmedi ated or direct effect of the intervention was no longer statistically significant (-0.08 for PHQ-9 and -0 .0 8 for CES-D) whereas the joint mediated effects explained more than 60% of the interventions’ total impact on depressive symptoms. A comparison of the standard ized b paths indicated that changes in anxiety had somewhat stronger independent mediation effects than the other two mediators examined, although differences were not statistically significant.
Discussion To our knowledge, this is the first study to identify mediators of a multicomponent, home-based intervention that reduces depres sive symptoms in a resource strapped population, urban older African Americans. This group had significant health, pain and financial concerns and moderate to moderately severe levels of depressive symptoms. We examined whether the effects of four
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due in large part to the lack of an appropriate measure reflective of these components. We were able to examine one indicator, formal care service use which reflects only one aspect of care manage ment. Future research should consider whether fulfilling unmet needs mediates intervention effects; unmet needs may be a better indicator of these two treatment components (care management and referral/linkage). Furthermore, as the care management and referral/linkage components identified unmet needs, provided re source ideas and areas for developing behavioral activation goals, it may be difficult to disentangle the specific effects of one intervention component from the other. For example, it may be that by addressing unmet needs, we also reduced anxiety. In this way, the indicators we used of mediational processes do not necessarily singularly align with each treatment component. Taken as a whole, our results lend strong support for multicom ponent, nondrug approaches that help low-income older African Americans address the contextual factors impinging on their mood. It appears that all treatment components are important and should be considered when replicating these findings with other minority
Figure 2. Multiple-mediator model of intervention effect on change in depressive symptoms. BL = baseline observation. A = 4-month score minus baseline score. PHQ-9 = Patient Health Questionnaire; CES-D = Center for Epidemiologic Studies-Depression scale. Numbers on top refer to PHQ-9 whereas numbers in bracket refer to CES-D.
populations or in different geographic regions. The results are consistent with behavioral theories suggesting that reducing situ ational stressors, educating about symptom recognition, and pro viding actionable plans leading to engagement in pleasant and/or meaningful activities can address mood disturbances and should be integrated in depression treatments for this population (Arean et al„ 2010). Noteworthy is that similar mediational results were obtained for each indicator of depressive symptoms, PHQ-9 and CES-D, lend ing support for the robustness of the findings. The two measures were moderately correlated suggesting over lap in symptoms but also differences in the aspects of depressed mood that were measured. Regardless, similar mediation relation ships and effects were achieved suggesting that BTB impacts the breadth of depressive symptoms expressed by these measures. However, as noted above, although behavioral activation was significant in the independent model it was not a significant mediator in the joint model for PHQ-9. This may signify that behavioral activation impacts affective depressive symptoms more as emphasized by the CES-D items versus the more somatic aspects reflected by the PHQ-9 items. Given the dearth of mediation analyses for home-based treat ments, it is unclear how these findings compare to others. Scogin et al. (2007) cognitive-behavioral intervention for rural older adults, most of whom were African American, could not account for treatment effects by cognitive or behavioral mediational pro cesses. In contrast, for a dementia caregiver intervention involving individual and family counseling, change in satisfaction with so cial support mediated intervention effects for depressive symptoms (Roth et al., 2005). Thus, interventions may impact depressive symptoms through different processes depending upon the target population and properties of the intervention. No studies to our knowledge have attempted to identify indicators of components of complex interventions as we do here. Mediation analyses are an important analytic approach for understanding the relative contri butions of treatment components and should be pursued in future depression trials. Several study limitations should be noted. Our sample size was relatively small compared with large primary-care physician-based depression clinical trials. Nevertheless, this study compares favor ably with intervention studies conducted in single community sites with sample sizes
© 2014 American Psychological Association 0882-7974/14/$ 12.00 http://dx.doi.org/10.1037/a0036784
Mediators of the Impact of a Home-Based Intervention (Beat the Blues) on Depressive Symptoms Among Older African Americans Laura N. Gitlin, David L. Roth, and Jin Huang Johns Hopkins University Older African Americans (N = 208) with depressive symptoms were randomly assigned to a home-based nonpharmacologic intervention (Beat the Blues, or BTB) or wait-list control group. BTB was delivered by licensed social workers and involved up to 10 home visits focused on care management, referral and linkage, depression knowledge and efficacy in symptom recognition, instruction in stress reduction techniques, and behavioral activation through identification of personal goals and action plans for achieving them. Structured interviews by assessors masked to study assignment were used to assess changes in depressive symptoms (main trial endpoint), behavioral activation, depression knowledge, formal care service utilization, and anxiety (mediators) at baseline and 4 months. At 4 months, the intervention had a positive effect on depressive symptoms and all mediators except formal care service utilization. Structural equation models indicated that increased activation, enhanced depression knowl edge, and decreased anxiety each independently mediated a significant proportion of the intervention’s impact on depressive symptoms as assessed with 2 different measures (PHQ-9 and CES-D). These 3 factors also jointly explained over 60% of the intervention’s total effect on both indicators of depressive symptoms. Our findings suggest that most of the impact of BTB on depressive symptoms is driven by enhancing activation or becoming active, reducing anxiety, and improving depression knowledge/ efficacy. The intervention components appear to work in concert and may be mutually necessary for maximal benefits from treatment to occur. Implications for designing tailored interventions to address depressive symptoms among older African Americans are discussed. Keywords: depression, mediation models, mental health disparities
Depression in older adults is well recognized as a debilitating condition that heightens the risk for functional decline, comorbid ity, poor quality of life, dementia, and mortality (Ciechanowski et al., 2004; Cuijpers, Beekman, & Reynolds, 2012; Glaser, Robles, Sheridan, Malarkey, & Kiecolt-Glaser, 2003; Lenze et al., 2001). Even mild to moderate symptoms, if not successfully treated, may lead to poor health outcomes and increased health care utilization and costs (Arean, 2006; Glaser et al., 2003; Grabovich, Lu, Tang, Tu, & Lyness, 2010; Lee et al., 2012; Lyness, Chapman, McGriff, Drayer, & Duberstein, 2009). Older African Americans, one of the fastest growing minority segments of the aging population (Institute of Medicine [IOM], 2012), are at risk for depressive symptoms due to their high rates of chronic illnesses (e.g., heart disease, high blood pressure, dia betes) and exposure to other jeopardies and chronic adversities including poor access to needed resources, low income, poor
housing, and unsafe neighborhoods, as well as a history of dis crimination, all factors that increase burdens and risk for depres sion (Arean et al„ 2010; Pickett, Bazelais, & Bruce, 2013). Recent estimates of prevalence rates for this group are higher than the 7% to 15% previously reported (National Institute of Mental Health, 2010; Woodward, Taylor, Abelson, & Matusko, 2013; Zivin, Pirraglia, McCammon, Langa, & Vijan, 2013). In the African American Health Study of 998 community-dwelling Af rican Americans, 21.1% had clinically relevant depressive symp toms (Miller et al., 2004). A survey of 150 older poor African Americans attending outpatient rehabilitation found that 30% scored positively for depression (Kurlowicz, Outlaw, Ratcliffe, & Evans, 2005). Similarly, in a survey of 153 urban African Amer ican senior center members, 24.2% reported mild to moderate depressive symptoms (Gitlin, Harris, McCoy, Chemet, Jutkowizt, Pizzi, 2012). Of 440 temporarily homebound older African Amer icans evaluated for depressive symptoms, 31% (n = 137) screened positively for mild to severe symptoms (Gitlin, Harris, et al., 2012 ). Nevertheless, older African Americans with depressive symp toms continue to be underdiagnosed and undertreated in primary care and mental health clinics (Arean & Uniitzer, 2003; Tai-Seale, McGuire, Colenda, Rosen, & Cook, 2007). Contributing to their underrepresentation in depression care are system- (lack of access to treatment and trained health providers) and person- (stigma, lack of knowledge about symptoms, lack of trust of providers) level factors (Conner et al., 2010; Ell, 2006; Gum et al., 2009). Studies also show that older African Americans may prefer nondrug ap-
Laura N. Gitlin, School of Nursing Center for Innovative Care in Aging, Johns Hopkins University; David L. Roth and Jin Huang, Center on Aging and Health, Division of Geriatric Medicine and Gerontology, Johns Hop kins University. Clinicaltrials.gov: NCT00511680; National Institutes of Mental Health #R01 MH 079814. Correspondence concerning this article should be addressed to Laura N. Gitlin, Johns Hopkins University School of Nursing Center for Innovative Care in Aging, Johns Hopkins University, 525 Wolfe Street, Suite 316, Baltimore, MD, 21205. E-mail: [email protected] 601
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proaches and have poorer compliance to drug therapies than their White counterparts (Kales et al., 2012). Moreover, drug therapies may not be as effective for those with mild to moderate symptoms and of short duration (Nelson, Delucchi, & Schneider, 2013). Although a growing evidence base supports the use of nonpharmacologic approaches including collaborative and integrated care models (Uniitzer et al., 2002) and psychotherapies (Lee et al., 2012; Peng, Huang, Chen, & Lu, 2009; Scogin, 2005; Wilson, Mottram, & Vassilas, 2008), their efficacy for minority popula tions has not been extensively examined (Fuentes & Aranda, 2012). Thus, a limited evidence base and persistent mental health disparities have prompted a national call for new models of care that address access and treatment preferences for nondrug ap proaches and which evaluate mechanisms by which approaches are effective for minority populations (Alexopoulos & Bruce, 2009; Bartels & Naslund, 2013; Callahan & Hendrie, 2010). Over the past decade, novel promising nonpharmacologic com munity and home-based care models have been tested. A system atic review of 23 effective models revealed that most were multicomponent and included care management and a behavioral approach such as problem solving, cognitive-behavioral or behav ioral activation therapies, addressed unmet needs and provided participants specific skills to cognitively reframe and manage situational stressors such as poor health, housing, or social needs (Gitlin, 2014). These models are unified in their attempts to identify and tackle the multiple contextual factors that may con tribute to or reinforce poor mood and which drug treatments cannot address (Frederick et al., 2007; Fuentes & Aranda, 2012; Gitlin, 2014). These models are also unified in their adoption of a social ecological framework for understanding the etiology of depres sion. This framework favors a behavioral explanation that links mood to daily life stressors and seeks to address contextual triggers of depressive symptoms such as unmet health and care manage ment needs as well as helping participants become behaviorally activated and also reengage in meaningful or pleasant activities (Kanter et al., 2010; Meeks, Looney, van Haitsma, & Teri, 2008; Scogin, Morthland, Kaufman, Chaplin, & Kong, 2011). To address depressive symptoms in urban, low-income older African Americans, we developed and tested the Beat the Blues (BTB) program. This multicomponent home-based intervention was informed by previously effective interventions and findings from focus group and in-depth interviews conducted for the pur poses of this trial to identify preferred treatment approaches. Treatment components included: care management (identifying unmet needs and deriving a plan of action), referral and linkage (making referrals to formal care and social service resources based on the care management assessment), education about depression and symptom recognition (instruction in early detection of symp toms, discussing feelings with physicians and those of a different race, therapeutic modalities including medication use and psycho therapy), stress reduction techniques (instruction in different ap proaches including deep breathing or counting, to reduce situationalinduced anxiety), and behavioral activation (identifying daily routines, a behavioral goal, an action plan, introducing pleasant events in routines). As keeping busy and being engaged in activity was identified in focus groups and in-depth interviews as preferred coping mechanisms, we included behavioral activation as a treat ment component versus more cognitive-based therapies such as
structured problem solving (Agarwal, Hamilton, Crandell, & Moore, 2010). Each component was designed to address situa tional conditions that may be reinforcing depressed mood for this low resource population. Addressing unmet health management and daily living needs through care management and a behavioral activation plan may be particularly salient for this group (Arean et al., 2010). For example, this might include setting a goal for disease self-management and an action plan for how to achieve that goal which specifies the necessary behavioral steps. Tested in a randomized trial involving 208 older African Amer icans, we found that study participants receiving the BTB program reported reduced severity in depressive symptoms with 43.8% in BTB versus 26.9% in the control group (p = .020) in remission by 4 months. Following treatment, control group participants demon strated benefits (4 to 8 months) similar in magnitude to the ad justed treatment effects for BTB participants in the first 4 months; and the initial BTB group maintained 4-month benefits at 8 months (Gitlin et al., 2013). Although mounting evidence supports multicomponent, non drug, behavioral treatment approaches, the active ingredient(s) by which these approaches have their desired effects is unclear. Also unclear is whether all treatment components are necessary for benefits to be realized. Mediation analysis provides an analytic framework for evaluating underlying mechanisms or how inter ventions may work, whether intervention components are neces sary, which components may need to be strengthened, and how to enhance intervention efficiency and design more effective and replicable treatments (Gitlin et al., 2000; Kraemer, Kieman, Essex, & Kupfer, 2008; Roth & MacKinnon, 2012). With few exceptions, mediational processes have not been ex amined in depression trials. Only a few caregiver studies address ing depression have examined mediators. These studies suggest different mediational processes may be operative depending upon treatment properties. A problem solving therapy for stroke care givers found that perceived health, threat appraisals and use of rational problem solving significantly mediated the intervention effect on caregiver depressive symptoms (King et al., 2012). A counseling and support intervention for spouse caregivers of per sons with dementia found that positive change in satisfaction with one’s social support network mediated a significant proportion of the impact of the intervention on caregiver depression; and this was further mediated by changes in caregiver stress appraisals (Roth, Mittelman, Clay, Madan, & Haley, 2005). Only one trial to our knowledge that tested a home-delivered cognitive-behavioral therapy with 134 participants, most of whom were African American, has examined mediational processes. Scogin et al. (2007) found that although their intervention im proved quality of life, cognitive and behavioral variables were not impacted and hence they did not mediate the positive benefits of the intervention. Thus, it remains unclear as to the underlying mechanisms re sponsible for the effectiveness of home-based nonpharmacologic treatment approaches to reduce depressive symptoms in older adults, and specifically for African Americans. In this study, we applied a mediational framework to understand the active ingre dients) of BTB. We examined four possible mediators of BTB’s impact on depressive symptoms: a measure of the change in levels of behavioral activation, or the extent to which participants be come actively engaged; a measure of the change in depression
MEDIATORS OF INTERVENTION ON DEPRESSIVE SYMPTOMS
knowledge and confidence in recognizing and managing symp toms; a measure of the change in anxiety levels; and a measure of formal care service utilization. These measures served as indica tors of or broadly corresponded to each of the five intervention components; behavioral activation, depression knowledge/efficacy, stress reduction, and care management/ referral/ linkage respectively. As we did not have a direct measure of engagement in stress reduction techniques, we used state anxiety as an indica tor. Also, as we did not have a direct measure of care management and referral/linkage components, we examined formal care service utilization as one indicator of these intervention processes. The treatment components of BTB were conceptualized to com plement and work in concert with each other. Thus, we expected each indicator of mediation to independently and significantly contribute to reducing depressive symptoms. We further expected that their joint effect would be even greater than their individual contributions.
Method Participants As described in depth elsewhere (Gitlin, Harris, et al., 2012; Gitlin et al., 2013), a total of 208 African Americans were enrolled in the trial. Participants were >: 55 years of age, English speaking, cognitively intact (Mini Mental Status Examination > 24), and scored > 5 on the Patient Health Questionnaire (PHQ-9), a mea sure of depressive symptoms, on two sequential testing occasions. Other enrollment criteria to enhance study retention included hav ing a home telephone and planning to live in the area for 8 months. Individuals were not eligible with a history of serious mental illness, life-limiting illnesses, involvement in another clinical de pression trial, or who lived in assisted living or nursing home facilities. Antidepressant or other medication use did not exclude participation. The trial reflected a partnership between a senior center and an academic research center who shared recruitment, interviewing, and intervention responsibilities. Recruitment targeted individuals enrolled in a short-term in-home support program for medically compromised individuals through ongoing systematic screening, and the community at-large through media announcements and presentations at local events and social agencies. Analyses for this present study were based on 179 participants (86.1%) who were retained through the 4-month assessment and provided complete data for all variables of interest in the mediation analyses. Of the 29 with incomplete data, 26 did not complete the 4-month follow-up (missing PHQ-9, CES-D and all mediators), one participant had missing data on the depression knowledge scale, one participant had missing data for both the behavioral activation and anxiety scales, and one had missing data for the CES-D and mediators. A comparison of the 179 participants in cluded in the analyses to the 29 participants who were not, re vealed no large or statistically significant differences at baseline on basic characteristics, indicators of mediation, and the two mea sures of depressive symptoms which were the outcome variables (all ps > .05). Participants recruited from the two venues (in-home support group and community at-large) differed at baseline along certain characteristics as anticipated. The in-home group (n = 51) partic
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ipants were older, had more pain and more health conditions (ps < .05) compared to the community at-large group (n = 128). For baseline depression measures, the two groups had similar PHQ-9 scores but did differ on CES-D scores (p = .04). The in-home group reported on average less symptomatology (M = 13.06, SD = 6.08) than the community at-large group (M = 15.09, SD = 5.73) on the CES-D, although both groups scored in a high range of symptomatology indicative of clinical depression. The groups did not statistically differ on the four measures of mediation. As we used a stratified randomization scheme based on recruitment source (in home support group vs. community at-large), all groups were comparable at baseline; that is, no large or statistically significant differences were found at baseline between the in-home participants assigned to experimental and control groups nor be tween the community at-large participants assigned to experimen tal and control groups.
Procedure Enrollment procedures included two sequential depression screenings of individuals by trained senior center staff over 2 weeks using the Patient Health Questionnaire (PHQ-9). Those eligible (PHQ-9 a 5) and willing to participate in the trial pro vided written consent using an approved Institutional Review Board (IRB) form, completed a baseline home interview, and were then randomized to receive BTB immediately or 4 months later (wait-list control). All participants were reassessed at 4 and 8 months in their homes using the same interview battery conducted by assessors masked to participant group allocation. Participants did not incur any study-related expenses and were provided $15 for completion of each interview (baseline, 4 and 8 months) to recognize their time and participation in the study. This article used data from the baseline and 4-month assess ments.
Intervention Beat the Blues. The Beat the Blues intervention involved up to 10, 1-hr sessions that occurred at home over 4 months and was conducted by licensed social workers who were trained in the protocol. The first few sessions focused on building rapport and assessing for unmet care management needs from which to derive a plan of action including referral and linkage to formal care, community and social services. Interventionists also educated par ticipants about depressive symptoms and specifically, the link between behavior and mood, how to identify the onset of depres sive symptoms and use specific strategies to manage symptoms early on including having discussions about symptoms with phy sicians and when physicians are of a different race. Participants also learned about the effects of stress and how to use a basic deep breathing technique before or during stressful points in the day. In the next few sessions, interventionists helped participants resolve identified unmet care management needs (medical, housing re pairs, relocation needs, social, financial, benefits/entitlements), and worked on care management plans involving coordination, and referral and linkages to services if necessary. Additional stress reduction techniques (e.g., counting, music) were also introduced to provide other easy-to-use stress-reduction tools to address sit uational anxiety. In Sessions 4 and 5, interventionists continued
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addressing care management needs and began behavioral activa tion exercises. First, interventionists reviewed daily routines and helped participants select a behavioral goal and a specific activity to add pleasure and personal satisfaction to daily or weekly rou tines. Active problem solving and motivational interviewing tech niques helped participants achieve identified activity goals. Poten tial barriers to carrying out selected activities were identified and solutions derived that might also have required care management (arranging transportation) to engage in desired activities. Sessions 6 - 8 involved reinforcement of activity engagement, identification of new activity goals and specific steps to achieve them. In Sessions 9 and 10, interventionists reviewed and reinforced all techniques, continued to help participants identify activity goals, break them down to achievable steps, and learn this process for future independent use. All participants received all five treatment components. The content of each component reflected or was tailored to the partic ipants’ specific care management and referral/linkage needs, level of depression knowledge and ability to recognize symptoms, pre ferred stress reduction techniques, and self-identified goals and behavioral activation plans. For example, although all participants were exposed to stress reduction techniques, if a participant ex pressed a preference, that particular technique was reinforced. Similarly, all participants were exposed to the same behavioral activation steps but the specific goals and action steps identified were individualized. Further, the treatment components were in tegrated such that a care management need could be the basis of a behavioral activation goal (e.g., preparing and eating the right foods to manage diabetes), and depression knowledge/efficacy was linked to self-management and becoming actively engaged in one’s own health care. Interventionists presented each of their assigned cases in weekly one-on-one supervisor meetings and biweekly group debriefing sessions to assure protocol adherence and to review care management, referral/linkage and behavioral activation plans. Approximately seven sessions involved care management and behavioral activation, five sessions involved teaching and practic ing a stress reduction technique, and about four sessions involved referral and linkage and depression knowledge/efficacy (Gitlin et al., 2013). Wait-list control group. The wait-list control group did not receive any study-related intervention or contact following the baseline interview. Participants in this group, as those in the BTB group, were free to engage in any nonstudy services, depression treatments or programs they chose. After completing the 4-month assessment, participants received BTB in its entirety and as deliv ered to the initial group. This study examined mediational pro cesses at 4 months only given that by 8 months, all participants received the intervention.
Measures Measures included the following background characteristics: marital status (not married/married, living as married), living ar rangement (alone/with others), sex, education (< high school, high school or > high school level of education), age, financial diffi culty (0 = not very difficult to 3 = very difficult paying fo r basics), self-reported health conditions, and use of depression, anxiety, or pain medications (yes/no).
Outcome Variable The primary dependent variable was depressive symptoms (main trial endpoint). We used two different scales with psycho metric adequacy for African Americans in order to examine the robustness of our effects across two measures that tapped into slightly different types of depressive symptoms (Huang, Chung, Kroenke, Delucchi, & Spitzer, 2006; Nguyen, Kitner-Triolo, Ev ans, & Zonderman, 2004). The PHQ-9 provided a brief, psychometrically sound 9-item self-report severity measure (Kroenke & Spitzer, 2002). As the scale was administered on two subsequent occasions 2 weeks apart to determine eligibility, the second screen was used as the participants’ baseline value for the present anal yses. A total severity score was calculated by summing responses across the nine items which were rated as occurring not at all (0), several days (1), more than half the days (2), or nearly every day (3). Possible scores ranged from 0-27 (Cronbach’s alpha = .78 for this sample). We also used the 10-item Center for Epidemiology Studies Depression Scale (CES-D; Santor & Coyne, 1997). Participants indicated symptomatology in the past week (0 = rarely/never, 3 = most or all o f time). Scores were summed across items (range = 0-30) with a score > 8 indicative of clinical symptoms. Higher scores indicated greater symptomatology (a = .77 for this sample). There is some overlap of items for the CES-D and PHQ-9 (e.g., sleep quality, felt sad). However, CES-D items tend to emphasize affective components (e.g., felt lonely, enjoyed life), whereas PHQ-9 items tend to emphasize somatic aspects (e.g., poor appe tite, trouble concentrating or moving, or speaking slowly) of depressed mood.
Indicators of Mediation The measures used as mediating variables included depression knowledge/efficacy, state anxiety, behavioral activation, and for mal care service utilization. We assessed depression knowledge/efficacy using 10-items re flecting symptom awareness (“can identify depression symptoms”) and efficacy (“know how to explain feelings”) rated from 1 = not at all confident to 4 = absolutely confident. A total mean score was derived by summing across items and dividing by the number of items (range = 1-4). Higher scores represented greater knowl edge/efficacy (a = .72 for this sample; Cretin, Shortell, & Keeler, 2004). To measure anxiety, we used the 10-item State Anxiety Scale. Participants rated feelings (“I felt calm,” “tense”) from 1 = very much to 4 = not at all. A total anxiety score was computed as the mean across all items (a = .85 for this sample). Higher scores indicated greater anxiety (Speilberger, Gorsuch, Lushene, Vagg, & Jacobs, 1983). Activation was assessed using a modification of the Behavioral Activation Scale which included eliminating 14 items (“My work/ schoolwork suffered . . . ”) that were not relevant to this sample and rewording three items to heighten their relevance. Participants rated the resulting 17-items from 0 = not at all to 6 = completely. Items reflect broad content including positive engagement (“ac complished goal,” “engaged in activities,” “did things even though hard because fit with goals”), avoidance of difficult situations (“there were certain things that I needed to do that I didn’t do”), or
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dwelling on negative feelings (“. . . spent time thinking about my past, people who have hurt me, mistakes I’ve made”). A total activation score was computed as the mean across items (a = .83 for this sample). Higher scores indicated greater activation (Kanter, Mulick, Busch, & Berlin, 2007). The use/nonuse of formal care services in the past month was measured by 14 items reflecting four service types: psychosocial (e.g., talking to clergy, social worker, counselor, psychologist, psychiatrist, attending support groups), home health (e.g., assis tance with daily chores, self-care), social (e.g., transportation), and health care (e.g., physician visits, outpatient clinics) services. A total utilization index was computed by summing the number of services used.
group (in-home support group and community at-large) separately. As consistent results across mediators and outcomes were found, we only report analyses for the entire sample. After the mediators were examined individually, those that were identified as statistically significant mediators were examined si multaneously to test for independent versus overlapping mediation effects. The c’ from those models represented any intervention effect on depressive symptoms that was independent of the other mediating mechanisms and was used to calculate a jointly medi ated proportion. All statistical analyses were conducted using Mplus Version 7 (Muthen & Muthen, 2012).
Statistical Analysis
Table 1 provides descriptive data on the background character istics and the baseline measures of behavioral activation, depres sive symptoms, anxiety, and formal care service utilization for the 179 participants included in this study for both the total sample and by treatment assignment. For this sample, participants had a mean age of 69.44 (SD = 8.57). Most were female (N = 142, 79.33%), not employed (N = 164, 91.62%), not married (N = 157, 87.71%), had > high school education (N = 86, 48.04%), lived alone (TV = 106, 59.22%), and reported financial difficulties (N = 121, 67.60%). Participants reported an average of 6.56 (SD = 3.05) health conditions such as high blood pressure (n = 141, 78.77%), high cholesterol (n = 106, 59.22%), arthritis (n = 136, 75.98%), and diabetes (n = 79, 44.13%). Most were not taking medications for mood: 38 (21.35%) reported antidepressant and 29 (16.29%) antianxiety medication use. However, most were on a pain man agement drug (N = 92, 51.69%) suggesting this sample had significant health concerns. Participants reported a moderate level of depressive symptoms on the PHQ-9 (M = 12.87, SD = 4.96) with close to one third expressing mild symptoms, more than one third expressing mod erate symptoms, close to one quarter indicating moderately severe symptoms and about 11% having severe symptoms. Similarly, for the CES-D, participants scored above the clinical cutoff for de pressive symptoms and in the moderate symptom range (M = 14.51, SD = 5.89). As to mediators, participants reported some to moderate anxiety (M = 2.52, SD = 0.65), some confidence recognizing symptoms (M = 3.11, SD — 0.43), low activation (M = 2.89, SD = 1.00), and using an average of four formal services (M = 4.04, SD = 4.90; see Table 1). The correlations among the variables analyzed in the mediation models are displayed in Table 2. As expected, there were signif icant correlations across the different mediating variables, both at baseline and for the 4-month change scores. The two measures of depression were moderately correlated, both at baseline (r = .49) and in terms of changes over time (r = .50). This indicates some overlap, but also differences in the way depressive symptoms were measured in the two instruments (see Table 2).
The general analytic approach to examine the proposed media tors individually is illustrated in Figure 1. The primary aim of the analyses was to determine whether improvements in four mediat ing variables (depression knowledge, anxiety, behavioral activa tion, formal care use) independently and jointly, mediated the beneficial impact of the intervention on depressive symptoms at 4 months. There are multiple ways to statistically test for mediation effects even with relatively straightforward, two-wave (prepost) data from a randomized trial. In particular, the b path illustrated in Figure 1 can fluctuate substantially depending on whether covariated-adjusted change scores or 4-month scores are analyzed as the effects (Roth & MacKinnon, 2012). In our analyses, simple change scores (4 month minus baseline) were calculated for the mediators (behavioral activation, depression knowledge, anxiety, formal care service use) and the depressive symptoms measures (PHQ-9, CES-D). These change scores were then analyzed as a function of their baseline values and the interven tion effect as illustrated in Figure 1. The mediated or indirect effect represents the joint impact of the a and b paths on the outcome, and is estimated as a*b. The c’ path represents unmediated or direct effect, and the sum of a*b and c’ comprises the total (baseline-adjusted) effect of BTB on depressive symptoms. These estimates were tested for statistical significance and used to estimate the proportion of the total effect that could be attributed to that mediator, (a’b)/((a*b)+c’). We also conducted stratified analyses for each recruitment source
Results
Effects of BTB on Depressive Symptoms and Mediators Figure 1. Two-wave mediation model used to examine mediators indi vidually. BL = baseline observation. A = 4-month score minus baseline score.
Using standard analyses of covariance, with the baseline score as the covariate, the BTB intervention was found to have significant effects on both measures of depressive symptoms and on three (all
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Table 1 Baseline Characteristics o f Analytical Sample (N = 179) Characteristic Age Sex, n (%) Male Female Education, n (%) CHS HS/GED >H S Employment status, n (%) Employed Unemployed Paying for basics, n (%) Not difficult at all Not very difficult Somewhat difficult Very difficult Marital status, n (%) Not married Married Number of health conditions Antidepressant medication, n (%) Anxiety medication, n (%) Pain medication, n (%) PHQ-9 Score (second screen) PHQ-9 Score (second screen), n (%) Minimal/no depression (0-4) Mild depression (5-9) Moderate depression (10-14) Moderate/severe depression (15-19) Severe depression (&20) CES-D score Behavioral activation Depression knowledge Anxiety Formal care service use Note.
Total sample (.N = 179)
Treatment group (.N = 86)
Control group (V = 93)
69.44 (8.57)
69.00 (8.70)
69.84 (8.48)
37 (20.67) 142 (79.33)
17(19.77) 69 (80.23)
20 (21.51) 73 (78.49)
40 (22.35) 53 (29.61) 86 (48.04)
18(20.93) 22 (25.58) 46 (53.49)
22 (23.66) 31 (33.33) 40 (43.01)
15 (8.38) 164(91.62)
11 (12.79) 75 (87.21)
4 (4.30) 89 (95.70)
(20.11) (12.29) (38.55) (29.05)
12(13.95) 13(15.12) 33 (38.37) 28 (32.56)
24(25.81) 9 (9.68) 36 (38.71) 24(25.81)
157 (87.71) 22 (12.29) 6.56 (3.05) 38 (21.35) 29(16.29) 92 (51.69) 12.87 (4.96)
72 (83.72) 14(16.28) 6.73 (2.75) 22 (25.58) 12(13.95) 44(51.16) 12.99 (5.27)
85 (91.40) 8 (8.60) 6.40(3.31) 16(17.39) 17(18.48) 48 (52.17) 12.75 (4.67)
0 (0.00) 54 (30.17) 63 (35.20) 41 (22.91) 21 (11.73) 14.51 (5.89) 2.89(1.00) 3.11 (0.43) 2.52 (0.65) 4.04 (4.90)
0 (0.00) 27 (31.40) 30 (34.88) 16(18.60) 13(15.12) 14.53 (5.88) 2.94(1.01) 3.09 (0.46) 2.51 (0.66) 4.36(6.19)
0 (0.00) 27 (29.03) 33 (35.48) 25 (26.88) 8 (8.60) 14.48 (5.93) 2.85(1.00) 3.13 (0.40) 2.53 (0.64) 3.75 (3.31)
p value .51 .77
.35
.04
.18 36 22 69 52
.12
.47 .18 .41 .89 .75 .39
.95 .57 .51 .83 .41
PHQ-9 = Patient Health Questionnaire; CES-D = Center for Epidemiologic Studies-Depression scale.
ps < .0001) of four proposed mediating variables. In each case, the findings indicated that improvements were observed in the BTB group that exceeded any changes observed in the wait-list control group for behavioral activation, depression knowledge/efficacy, and anxiety. There was no intervention effect for formal care service utilization. The significant intervention effects were previously pub lished for the entire sample (Gidin et al., 2013). The estimates for these effects on the mediators comprise the “a” paths in the mediation models and are provided in that column of Table 3.
Single Mediator Models The unstandardized estimates that correspond to the paths illus trated in Figure 1 are reported in Table 3 for each mediator-depressive symptom measure combination. These findings indicate highly sig nificant mediation effects for behavioral activation, depression knowl edge, and anxiety (all ps < .01) for both depression measures. The mediation effects were similar in magnitude, with the proportion mediated effect ranging from .35 to .42.
Multiple Mediator Models The single mediator models indicated that changes in three medi ators (behavioral activation, depression knowledge, and anxiety) ex
plained a portion of the intervention-induced changes on depressive symptoms. Figure 2 displays the standardized estimates of the effects from the model that examined intervention-induced changes on three of these mediators simultaneously and for both depressive symptom measures. Because the “a” paths did not change across the two models for different depressive symptom measures, only one estimate is provided for each “a” path in Figure 2. In both models, the unmedi ated or direct effect of the intervention was no longer statistically significant (-0.08 for PHQ-9 and -0 .0 8 for CES-D) whereas the joint mediated effects explained more than 60% of the interventions’ total impact on depressive symptoms. A comparison of the standard ized b paths indicated that changes in anxiety had somewhat stronger independent mediation effects than the other two mediators examined, although differences were not statistically significant.
Discussion To our knowledge, this is the first study to identify mediators of a multicomponent, home-based intervention that reduces depres sive symptoms in a resource strapped population, urban older African Americans. This group had significant health, pain and financial concerns and moderate to moderately severe levels of depressive symptoms. We examined whether the effects of four
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due in large part to the lack of an appropriate measure reflective of these components. We were able to examine one indicator, formal care service use which reflects only one aspect of care manage ment. Future research should consider whether fulfilling unmet needs mediates intervention effects; unmet needs may be a better indicator of these two treatment components (care management and referral/linkage). Furthermore, as the care management and referral/linkage components identified unmet needs, provided re source ideas and areas for developing behavioral activation goals, it may be difficult to disentangle the specific effects of one intervention component from the other. For example, it may be that by addressing unmet needs, we also reduced anxiety. In this way, the indicators we used of mediational processes do not necessarily singularly align with each treatment component. Taken as a whole, our results lend strong support for multicom ponent, nondrug approaches that help low-income older African Americans address the contextual factors impinging on their mood. It appears that all treatment components are important and should be considered when replicating these findings with other minority
Figure 2. Multiple-mediator model of intervention effect on change in depressive symptoms. BL = baseline observation. A = 4-month score minus baseline score. PHQ-9 = Patient Health Questionnaire; CES-D = Center for Epidemiologic Studies-Depression scale. Numbers on top refer to PHQ-9 whereas numbers in bracket refer to CES-D.
populations or in different geographic regions. The results are consistent with behavioral theories suggesting that reducing situ ational stressors, educating about symptom recognition, and pro viding actionable plans leading to engagement in pleasant and/or meaningful activities can address mood disturbances and should be integrated in depression treatments for this population (Arean et al„ 2010). Noteworthy is that similar mediational results were obtained for each indicator of depressive symptoms, PHQ-9 and CES-D, lend ing support for the robustness of the findings. The two measures were moderately correlated suggesting over lap in symptoms but also differences in the aspects of depressed mood that were measured. Regardless, similar mediation relation ships and effects were achieved suggesting that BTB impacts the breadth of depressive symptoms expressed by these measures. However, as noted above, although behavioral activation was significant in the independent model it was not a significant mediator in the joint model for PHQ-9. This may signify that behavioral activation impacts affective depressive symptoms more as emphasized by the CES-D items versus the more somatic aspects reflected by the PHQ-9 items. Given the dearth of mediation analyses for home-based treat ments, it is unclear how these findings compare to others. Scogin et al. (2007) cognitive-behavioral intervention for rural older adults, most of whom were African American, could not account for treatment effects by cognitive or behavioral mediational pro cesses. In contrast, for a dementia caregiver intervention involving individual and family counseling, change in satisfaction with so cial support mediated intervention effects for depressive symptoms (Roth et al., 2005). Thus, interventions may impact depressive symptoms through different processes depending upon the target population and properties of the intervention. No studies to our knowledge have attempted to identify indicators of components of complex interventions as we do here. Mediation analyses are an important analytic approach for understanding the relative contri butions of treatment components and should be pursued in future depression trials. Several study limitations should be noted. Our sample size was relatively small compared with large primary-care physician-based depression clinical trials. Nevertheless, this study compares favor ably with intervention studies conducted in single community sites with sample sizes
