Draft Outline of Psy and Aging Within-Site Analysis

Running Head: Effect of Multi-component Interventions 1

Effect of Multi-component Interventions on Caregiver Burden and Depression:

The REACH Multi-site Initiative at Six Months Follow-up

Laura N. Gitlin, Ph.D. Thomas Jefferson University

Louis Burgio, Ph.D. University of Alabama, Tuscaloosa

Sara Czaja, Ph.D. University of Miami School of Medicine

Diane Mahoney, Ph.D. Hebrew Rehabilitation Center for Aged

Dolores Gallagher-Thompson, Ph.D. Stanford University School of Medicine VA Palo Alto Health Care System

Robert Burns, M.D VA Medical Center, Memphis

Walter W. Hauck, Ph.D. Thomas Jefferson University

Steven H. Belle, Ph.D. University of Pittsburgh

Richard Schulz, Ph.D. University of Pittsburgh

Marcia G. Ory, Ph.D.* Behavioral and Social Science Program, National Institute on Aging Running Head: Effect of Multi-component Interventions 2

*Addendum of Co-authors:

Data Management and Statistical Work Group:

David Coon, Ph.D. Goldman Institute on Aging, San Francisco, CA

Rich Jones, ScD. Hebrew Rehabilitation Center for Aged, Boston MA

Helena Kraemer, Ph.D. Stanford University School of Medicine

David Loewenstein, Ph.D. University of Miami School of Medicine

Allan Lummus, M.A. University of Tennessee

David Roth, Ph.D. University of Alabama, Birmingham

Stephen Wisniewski, Ph.D. University of Pittsburgh

Site Collaborators/Co-investigators:

Mary Corcoran, Ph.D. George Washington University

Marie P. Dennis, Ph.D. Thomas Jefferson University

Linda Nichols, Ph.D. Memphis VA Medical Center and University of Tennessee

Alan Stevens, Ph.D. University of Alabama, Birmingham

Laraine Winter, Ph.D. Thomas Jefferson University Running Head: Effect of Multi-component Interventions 3

ABSTRACT

This paper reports the effects of 15 REACH (Resources for Enhancing Alzheimer’s

Caregiver Health) interventions (9 active and 6 control group conditions) at six-month follow-

up on reduction of burden and depressive symptoms in family members providing care to

individuals with dementia. Caregivers at each REACH site were randomly assigned to a

treatment condition. Interventions varied across participating sites and included information

provision, individual, group and family support, psycho-educational and skill-based training,

environmental redesign, and enhanced technology systems. Data from both within site and

cross-site analyses are presented. In addition, the effects of racial and ethnic identity on

treatment outcomes are reported. At the site level, ANCOVA’s revealed no main effects for

group assignment on caregiver burden. A statistically significant group by race interaction

effect was found at the Birmingham site (p = .02). Across REACH, the pooled parameter

estimate of the meta-analysis indicated that active interventions were superior to control

conditions (p = .05). For depressive symptoms (CES-D), a statistically significant effect for

group assignment was only found at the site level for Miami’s combined family therapy and computer technology intervention (p = .01). The results suggest that interventions may need to

be tailored to match specific characteristics of caregivers including cultural background and

relationship to the care recipient. Running Head: Effect of Multi-component Interventions 4

INTRODUCTION

Providing care to individuals with Alzheimer’s disease or a related disorder

(ADRD) poses significant challenges to families that may result in emotional distress such as depression and feelings of burden (Schulz, O’Brien, Bookwala, & Fleissner, 1995). Reducing the negative consequences of caregiving can have important benefits such as sustaining the health and well-being of family caregivers and postponing nursing home placement

(Mittleman, Ferris, Steinberg, Shulman, Mackell, Aminder, & Cohen, 1995). Although numerous interventions have been developed, few have shown significant positive outcomes for family caregivers. Given the expected increase in the number of persons with dementia, identifying innovative approaches to reducing the stress of caregiving is an important public health issue.

The Resources for Enhancing Alzheimer’s Caregiver Health (REACH) was funded

(1995-2000) by the National Institute on Aging and the National Institute for Nursing Research at the National Institutes of Health, to characterize and test the feasibility of the most promising behavioral, social, technological or environmental interventions for family caregivers of persons with ADRD. Six sites developed and implemented unique interventions

(Birmingham, Boston, Memphis, Miami, Palo Alto, and Philadelphia) and a seventh site

(Pittsburgh) served as the coordinating center to assure standardization and quality oversight of study protocols, data management, and analysis. This article examines the effects of the

REACH interventions on two outcomes commonly used in caregiver intervention research, caregiver burden and caregiver depression. Running Head: Effect of Multi-component Interventions 5

Impact of Dementia Caregiving

Caring for individuals suffering from dementia has profound consequences for family caregivers. Potential stressors associated with family caregiving are numerous and can include managing behavioral disturbances, attending to physical needs, and providing seemingly constant vigilance (Gold, et al., 1995; Vitaliano, Russo, Young, Teri, & Maiuro,

1991; Wright, Clipp, & George, 1993). The effects of these stressors on family caregivers can be catastrophic. Family caregiving has been associated with increased levels of depression and anxiety as well as higher use of psychoactive medications, poorer self-reported physical health, compromised immune function and increased mortality (Kiecolt-Glaser & Glaser, 2001; Light,

Niederehe, & Lebowitz, 1994; Schulz & Beach, 1999; Schulz et al., 1995).

Increases in behavioral disturbances among care recipients are particularly stressful to caregivers and are reported to be more distressing than cognitive problems

(Gaugler, Davey, Pearlin, & Zarit, 2000; Ford, Goode, Barrett, Harrell, & Haley, 1997; Kaufer, et al., 1998). A review by Schulz and colleagues (1995) that examined the association between behavioral disturbances and caregiver depression, found that nine out of 10 studies reported a significant relationship between these variables.

Previous Research on Caregiver Interventions

The past 15 years have yielded numerous studies testing interventions to alleviate burden and depression in families caring for persons with dementia. Early studies tested interventions that were primarily psychosocial, typically involving support groups, individual counseling, and education. Reviews of these studies concluded that such interventions had only modest therapeutic benefits as measured by global ratings of well-being, mood, stress, psychological status, and caregiving burden (Knight, Lutzky, & Macofsky-Urban, 1993; Running Head: Effect of Multi-component Interventions 6

Toseland & Rossiter, 1989). Furthermore, programs designed for individual caregivers appeared to be more effective than group programs (Knight et al., 1993). As Zarit and Teri

(1992) noted, interpretations of these early efforts should be tempered by the fact that expectations for particular intervention outcomes and the malleability of caregivers were initially overly optimistic. Also some intervention effects may have been underestimated because of methodological limitations.

More recent studies have evaluated a broader scope of interventions that can be categorized as individual or family counseling, case management, skills training, and combinations thereof. In a comprehensive review of this second generation of intervention studies by Bourgeois, Schulz, and Burgio (1996), several important conclusions are derived.

First, the complexity and rigor of intervention studies continue to improve with an increasing emphasis on randomized designs. Second, the literature on the whole supports the conclusion that more is better in that multi-component interventions that provide caregivers with diverse services and supports and that target specific caregiver needs tend to generate larger effects than narrowly-focused interventions. Similarly, single component interventions with higher intensity (frequency and duration) have a greater positive impact on the caregiver than similar interventions with lower intensity. However, a persistent limitation of caregiver intervention research is that individual studies offer relatively small sample sizes or explore a limited range of intervention strategies. As a result, it is difficult to identify the optimal mix of program elements for a given caregiver-care-recipient dyad. This review was recently updated and expanded by Kennet, Burgio and Schulz (2000), and their conclusions remained unchanged. Running Head: Effect of Multi-component Interventions 7

Racial and Ethnic Differences in Caregiver Intervention Research

Another limitation of intervention studies is the lack of attention to the potential impact or role of racial/ethnic identity on caregiving and how that may affect responses to intervention (Aranda & Knight, 1997; Connell & Gibson, 1997). Recent evidence shows important differences in perceived burden and depression among African-American, White and

Hispanic family caregivers (Calderon & Tennstedt, 1998; Haley, et al., 1996; Stueve, Vine, &

Struening, 1997). Most studies show that African-American caregivers report less depressive symptoms and lower burden than White or Hispanic caregivers (Connell & Gibson, 1997).

Furthermore, it has long been understood that culture influences the construction of illness perceptions (Kleinman, Eisenberg, & Good, 1978; Lockery, 1991). The failure to address multicultural issues has led to significant gaps in knowledge about psychosocial problems such as depression (Sue, Bingham, Porsche-Burke, & Vasquez, 1999). It seems reasonable to expect that racial and ethnic identity may shape cultural beliefs about dementia and the family's responsibility for care and will therefore affect how families respond to the challenges of long- term caregiving and interventions designed to support these efforts (Haley, Han, & Henderson,

1998).

Present Research

The REACH initiative addresses some of the major limitations in previous intervention research and offers several important advantages to examining treatment effects on caregiver burden and depression. Foremost among these is the large (N=1,222) ethnically diverse sample of caregivers recruited by REACH. The REACH sample included large numbers of White/Caucasian, Black/African-American and Hispanic/Latino caregivers. This latter group included subsamples of Cuban-Americans, primarily recruited at the Miami site, Running Head: Effect of Multi-component Interventions 8 and Mexican-Americans, primarily recruited at the Palo Alto site. In the analyses presented here these subgroups were combined and are referred to as Hispanic/Latino (Torrres-Gil &

Kuo, 1998). Additionally, sites tested different theory-driven interventions and used randomized clinical trial procedures to test hypotheses about the effects of intervention. A common set of measures and procedures was implemented to facilitate cross-site comparisons.

The procedures and analytic approach used by the REACH study group to evaluate treatment effectiveness followed clinical trial methodology. Finally a unifying theoretical framework was developed that allows pooling data across sites for the purpose of identifying specific intervention components that are particularly effective (see article #3 and 4 in series).

The REACH interventions included individual information and support strategies, group support and family systems efforts, psycho-educational and skill-based training approaches, home-based environmental strategies and enhanced technology systems. Although each site intervention was based in a specific theory-driven care model, the REACH initiative used a basic stress process model developed by Cohen, Kessler & Gordon (1995) and adapted by the REACH investigators (Schulz, Gallagher-Thompson, Haley, Coon, & Czaja, 2000) to conceptualize the experience of ADRD caregivers. This model and its adaptation are described in more detail in Czaja et al (paper # 3 in this series) and provides a broad conceptual framework for linking REACH interventions to specific elements of stress processes and explains how interventions impact appraisals.

This paper examines the relative effects on caregiver burden and depressive symptoms of 15 different site-specific REACH interventions and through meta-analysis, the combined effect of interventions across sites following six months of active treatment.

Secondary analyses were also conducted to examine differences in treatment effects by Running Head: Effect of Multi-component Interventions 9 race/ethnic identity for each site’s intervention. REACH collected follow-up data on all caregivers at 6 months, 12 months and 18 months to determine treatment effects at each testing occasion. This paper focuses on outcomes of the first phase of REACH interventions at six- months.

METHOD

Recruitment and Sample

REACH recruited family caregivers of individuals with dementia from multiple community sites, health, and social agency settings, with special attention to enrolling diverse participants. Outreach efforts such as radio, television, targeted newsletters, public service announcements, and community presentations were common across sites. Participants were also recruited from referrals from memory disorder clinics, primary care clinics, social service agencies and physician offices. Recruitment goals were based on power analyses for detecting different effect sizes for the different intervention strategies. Thus enrollment numbers differed across the sites. Details about the extensive recruitment efforts, as well as their related costs and outcomes, are reported in the literature (Nichols, Malone, Tarlow, & Lowenstein,

2000; Tarlow & Mahoney, 2000).

REACH enrolled and randomized 1,222 family caregivers over the age of 21 who lived with and provided care for a relative with ADRD for a minimum of fours hours of supervision or direct care per day for at least the past six months. They were excluded if they were involved in another caregiver intervention study or had an acute illness that would prevent them from participating for at least six months. Running Head: Effect of Multi-component Interventions 10

Caregivers were also excluded if their care recipients had a terminal or severe illness or disability that would prohibit them from participating in the interventions. Care recipients had to have a medical diagnosis of probable ADRD or exhibit a Mini-Mental State Exam

(MMSE; Folstein, Folstein, & McHugh, 1975) score less than 24. Additionally they had to have at least one limitation in basic activities of daily living (ADL; Katz, Ford, Moskowitz,

Jackson, & Jaffe, 1963) or two dependencies in their instrumental activities of daily living

(IADLs; Lawton & Brody, 1969). Both sexes were recruited except at one site, Palo Alto, where only female caregivers were enrolled.

These participation criteria were designed to ensure that caregivers were involved in daily tasks and responsibilities that could be burdensome. Other requirements were logistical and included having a telephone, planning to remain in the geographic area for at least six months, and competency in languages specified by each study site.

Procedures

Interventions at each site were tailored to the specific racial or ethnic group being served (e.g., Blacks/African-Americans were a key focus at Birmingham, Boston, Memphis and Philadelphia; Hispanic/Latinos at Miami and Palo Alto). All intervention materials and assessment instruments were translated into Spanish for the Hispanic participants using established techniques for forward and back translation and allowing for regional variation in language expression. Also, the Miami and Palo Alto sites included bi-lingual staff. Special techniques for recruitment and retention of these ethnic minority groups were also used, such as obtaining endorsement from community gatekeepers and providing financial assistance for transportation and respite costs when needed (Gallagher-Thompson, et al., 2000; Nichols, et al., under review). Running Head: Effect of Multi-component Interventions 11

Potential participants were initially interviewed at each site via telephone using a common set of screening questions. After obtaining informed consent from those who were eligible, caregivers were administered the core battery of measures in person and then were randomly assigned to intervention or control group conditions at each site. Caregivers were subsequently interviewed using the REACH core battery of measures at six, 12 and 18 months.

The core battery was modified, however, if the care recipient’s status changed prior to their next scheduled interview. If the care recipient died, a bereavement battery was substituted; if the care recipient was institutionalized, a placement battery was used. Both of these batteries eliminated measures that were not relevant to current caregiving concerns, such as care recipients’ bothersome behaviors and caregiver upset with such behaviors, but maintained the relevant domains such as caregiver depression. If at the time of a scheduled interview the care recipient did not remain institutionalized and returned home, the full battery was administered.

Consequently, the analytic sample size reported in this paper varies for the two outcome measures according to the disposition status of the caregiver (active caregiving at home, long- term care placement or bereaved). The core battery of measures used at each testing occasion is described in more detail in Wisniewski et al. (paper #1 in this series).

Each site obtained local Institutional Review Board (IRB) approval for their specific interventions and maintained ongoing approval during the five-year study period. The coordinating center conducted site visits to ensure adherence to study protocols and confirm the exclusive use of REACH trained and certified interviewers. They also conducted monthly monitoring of enrollment and data processing for quality control purposes. Running Head: Effect of Multi-component Interventions 12

Measures

Basic sample background characteristics and their coding are discussed in the companion paper

(Wisniewski et al., paper #1 in this series) and shown in Tables 2 and 3 here.

Outcome Measures

A specific protocol governed the selection of REACH measures and a committee conducted extensive investigations over the course of a one year period applying the psychometrically based selection guidelines (Switzer, Wisniewski, Belle, Dew, & Schulz,

1999). Preference was given to established measures with appropriate psychometric properties that had been used with ADRD family caregivers and had acceptable measurement properties for ethnically diverse samples. Two measures that met our criteria were used to assess caregiver burden and caregiver depression: The Revised Memory and Behavior Problem

Checklist (RMBPC; Teri, et al., 1992) and the 20-item Center for Epidemiological Studies

Depression Scale (CES-D; Radloff, 1977). The RMBPC was used to measure upset with the presence of memory and behavior problems. Caregivers were asked at baseline and six months whether their care recipients manifested any one of 24 problem behaviors (7 memory, 8 depressive, and 9 disruptive behaviors) during the past week. If caregivers responded yes, they were asked how bothered or upset they were for each reported behavior using a 5-point scale ranging from 0 (Not at all) to 4 (Extremely). Average upset scores were calculated among all behaviors assigning no upset to behaviors that were not manifested. The summary calculation reports an average upset rating with scores ranging from 0 to 96. For this study sample (N =

903), Cronbach’s alpha was .88. We used a change score (6 month - baseline) as the outcome variable (RMBPC burden score). High scores indicate increases in upset or burden, and a negative score indicates a decrease in caregiver upset or burden with behaviors. Running Head: Effect of Multi-component Interventions 13

To assess for the presence of depressive symptoms, we used a more global measure of well-being. The CES-D was initially designed as a screen for community dwellers at risk of developing major depressive symptomatology. It has been used widely in intervention studies with family caregivers. For each of the 20 items, participants rate its frequency of occurrence during the past week along four points (0 = rarely to 3 = most of the time). Scores range from

0-60 with a higher score indicating the presence of a greater number and frequency of depressive symptoms. A score of 16 or above has been identified as discriminatory between groups with clinically relevant and non-relevant depressive symptoms (Radloff & Teri, 1986).

For this study sample (N = 1076), Cronbach’s alpha was .73. The change score (6 months- baseline) for the CES-D was used as the outcome variable. A negative score indicates a decrease in depressive symptoms.

Randomization

Each site developed a stratified randomization scheme by which caregivers were assigned equally to treatment and control group conditions except for the Boston site, which did not use stratification and the Palo Alto site, which did not equally distribute participants across conditions. At the Palo Alto site, a 2-2-1 randomization scheme was used such that for every two caregivers randomized to the two treatment conditions, one caregiver was randomized to the minimal support condition. The stratification variables used in randomization are shown in Tables 4 and 5.

Interventions

A total of 15 interventions (9 active and 6 control group conditions) were tested across the six REACH sites. These interventions are described in detail in Wisniewski et al.

(paper #1 of this series). Three sites, Birmingham, Boston and Philadelphia, tested a single Running Head: Effect of Multi-component Interventions 14 active intervention (Skills Training Condition [STC], Telephone Linked Computer {TLC],

Environmental Skill Building [ESP], respectively). Three sites implemented two active interventions: Memphis (Behavior and Enhanced care), Miami (Family-based Multisystem In- home [FSMII], and FSMII combined with computer technology information system [CTIS] and Palo Alto (Coping class and Enhanced Support Group). Three sites used modified usual care control groups (Boston and Philadelphia) in which caregivers received information packets only. One site (Memphis) provided information and referral while three other sites

(Birmingham, Miami, Palo Alto utilized a minimal support control (information and empathetic listening [MSC]). An important feature of REACH was the use of rigorous treatment implementation procedures in which each site developed checks and balances to assure minimal deviation from intervention protocols as more fully explained in Burgio, et al.

(under review).

The background of individuals who delivered the interventions (e.g., occupational therapists, social workers, psychologists, and counselors) varied at each site and across interventions, as did the delivery characteristics including dose and intensity of contact, and location of intervention, e.g., home, community, and medical office (see Czaja et al., paper #3 in this series for more details). Overall, the active phase of the REACH interventions ranged in length from 6 months (Birmingham, Boston, Philadelphia, Miami, Palo Alto) to 24 months

(Memphis), with each intervention requiring a different frequency of contact. There was wide variation in the average number of contacts for each intervention in the first six months ranging from 5.2 (Philadelphia ESP) to 59 (Miami FSMII + CTIS). Overall, during the first six months, actual contact was more frequent in active than control conditions within each site Running Head: Effect of Multi-component Interventions 15 except for Birmingham and Palo Alto. In these sites, researchers attempted to equalize the number of contacts such that control and intervention groups received equivalent contacts.

Analytic Strategy

In accordance with clinical trial research principles, we examined intervention effects for the entire sample for which data were available. This intention-to-treat strategy is designed to preserve randomization by not deleting subjects from the analyses. Although we did not delete subjects based on post-randomization information, not all subjects provided six- month data on the RMBPC burden measure. Subjects who were bereaved or who placed their family member in a long-term care facility received a battery different from the core assessment. These placement and bereavement batteries did not include the RMBPC burden measure because it was not an appropriate measure for these caregivers. This yielded slightly different sample sizes for the two outcome measures; RMBPC burden and CES-D.

To reduce the number of subjects with missing data on both dependent variables, we interpolated six-month values using linear interpolation when the subject had twelve-month but not six-month data on the outcome variable. Thus, the analyses with RMBPC burden change score as the outcome variable include caregivers who were actively caring for a person with dementia at home at either six or 12 months (N = 903). Twenty-five caregivers had interpolated scores for 6-month RMPBC burden. The analyses involving CES-D change score as the outcome variable include this same set of active caregivers, as well as caregivers who were bereaved and those who placed their family member in a long term care facility (N =

1076), of whom 39 had interpolated scores for six-month CES-D.

Each site used the same analytic procedures for the within-site analyses. First a series of independent t-tests and chi-square tests for association were performed to examine Running Head: Effect of Multi-component Interventions 16 differences in caregiver characteristics between caregivers for whom we obtained six-month data and those who were not included in the six-month analyses due to loss to follow-up

(inactivation or status unknown).

Second, each site calculated adjusted mean differences in treatment effects on the outcome measures using analysis of covariance. The outcome measures were the change scores

(six-month score – baseline score) for RMBPC burden and CES-D. We used change scores because it was viewed as more interpretable than the six-month value alone. In these analyses, each site included as covariates the baseline value of the outcome measure and any stratifying or design variables applicable to that site. Baseline score of the dependent variable was included as a covariate to allow that the possible change in a measure may depend on the starting value. Since larger values of these measures indicate greater burden and depressive symptomatology, respectively, a negative change corresponds to improvement. Tables 4 and 5 present these analyses and list the covariates used by each site. The normality assumption for each dependent measure was tested by examining the distribution of the residuals from Tables

4 and 5 analyses. In some cases (Birmingham, Boston, Miami, Philadelphia), the residual distribution was skewed and normality would have been improved with a transformation of the data. However, in all cases, use of the transformation did not change the results. Therefore, we report untransformed results for all sites and measures.

Third, each site added race/ethnicity-by-treatment interaction to the analyses of

Tables 4 and 5, using the categories shown in the tables (two categories per site). We report interactions that are large or statistically significant.

Finally, we used meta-analysis to estimate treatment effects within each site and for

REACH overall. For each outcome, linear regression models were used to estimate treatment Running Head: Effect of Multi-component Interventions 17 effects (each active treatment versus control condition) within site. In addition, in the Palo Alto site White/Caucasians and Hispanic/Latinas were randomized separately to treatment conditions. Also interventions were conducted separately for each ethnic group. Therefore, these models were fit separately for White/Caucasians and Hispanic/Latinas. This resulted in

11 separate regression models for each of the two outcome measures. The independent variables were the baseline value of the scale for which the outcome was the six-month change, variables used in the design of the study at each site (as shown in Tables 4 and 5), and an indicator variable for active treatment. If there was no difference between the treatments, the parameter estimate was zero. A negative parameter estimate implied that the active treatment was more efficacious than the control treatment whereas a positive parameter estimate implied the opposite. The homogeneity of effects was tested (Pettiti, 2000) and a random-effects procedure (DerSimonian & Laird, 1986) was used to obtain a summary measure across the interventions.

RESULTS

Recruitment and Attrition

Table 1 shows the number of caregivers randomized at baseline and their participation status at six months by site and intervention assignment. The REACH sites overall were successful in retaining 88% of the participants through the first follow-up time point of six months. All sites retained at least 85% of randomized caregivers. As shown, of

1,222 caregivers randomized at baseline, at the six-month follow-up, 77 caregivers (6%) had placed their care recipients in a long-term care facility, 79 caregivers (6%) were bereaved, the status of 83 caregivers (7%) was unknown (e.g., caregiver missed six-month follow-up and status in study is unknown), and 63 caregivers (5%) withdrew from study participation Running Head: Effect of Multi-component Interventions 18

(inactivated). Table 1 also shows the number of subjects by site and intervention assignment for the RMBPC burden sample and the CES-D sample (Table 1).

Completers vs. Non-completers

Each site conducted a series of analyses to identify large or statistically significant differences in caregiver and care recipient characteristics listed on Tables 2 and 3 between those in the six month analyses (completers) and those for whom we did not have six month data (non-completers; status unknown or inactivated). These comparisons showed statistically significant differences on different variables at each site.

Birmingham. Birmingham randomized 140 caregivers, of whom 120 caregivers had six-month data (15% attrition rate). When the 120 caregivers with six-month data were compared to the 20 caregivers without six-month data on the variables listed in Tables 2 and 3, two statistically significant differences were found, p < .05. Non-completers were less likely to be married, 2 (5) = 23.43, p = .001, and had less education, 2 (2) = 14.26, p = .001, than those who completed the six-month assessment.

Boston. Boston randomized 100 caregivers, of whom 93 had six-month data (7% attrition

rate). A comparison of 93 completers to 7 non-completers revealed no differences at six

months with regard to the variables shown in Table 2. However, there were apparently large

differences in the age and MMSE of care recipients. Those with missing data at six months

were younger (M = 74.7, SD = 8.4 vs. M = 78.3, SD = 8.4), p = .28, respectively and more

cognitively impaired as measured by the Mini-Mental State Examination, (M = 6.3, SD = 4.5

vs. M = 11.7, SD = 8.4), p = .21.

Memphis. Memphis randomized 245 caregivers, of whom 215 had six-month data (12%

attrition rate). A comparison of the 215 completers to 30 non-completers revealed two Running Head: Effect of Multi-component Interventions 19

statistically significant differences. More non-completers were low-income (less than $20,000

per year) than completers (40,000+ per year); 2 (4) = 13.51, p = .01. In addition the baseline

CES-D scores for non-completers were significantly higher than completers (M = 16.26, SD =

13.47 versus M = 12.07, SD = 9.19), p = .05.

Miami. Miami randomized 225 caregivers, of whom 185 had six-month data (18% attrition).

A comparison of the 185 completers to 40 non-completers showed that non-completers had higher CES-D scores at baseline (M = 22.18, SD = 12.2) than completers (M = 17.24, SD =

11.5), F (1,123) = 5.89, p = .05.

Palo Alto. Palo Alto randomized 257 caregivers, of whom 231 had six-month data

(10% attrition). The results of the comparison of 231 completers to 26 non-completers

showed that for non-completers, the care recipient was more likely to be divorced, p=.02.

Philadelphia. Philadelphia randomized 255 caregivers, of whom 232 had six-month

data (9% attrition rate). A comparison of these completers to 23 non-completers showed that

caregivers differed significantly by race, 2 (2) = .03, p = .05, such that more African-

American caregivers were completers than White caregivers.

Sample Characteristics

Demographic data for caregivers at each of the six sites are presented in Table 2 for all those included in the six-month analyses. The sample included a total of 1,076 caregivers

(197 males and 879 females) whose mean age was 62.07 years (SD = 13.56 yrs.). Over half of these individuals were White/Caucasian (56.3%), approximately one quarter of caregivers were

Blacks/African-Americans (24.1%) and almost one-fifth of the caregivers (18.9%) were

Hispanic/Latino. The Hispanic/Latino category included subgroups of Mexican-Americans, and Cuban-Americans as well as a small subgroup of caregivers from Central America. There Running Head: Effect of Multi-component Interventions 20 were equivalent numbers of spouses (48.3%) vs. children (44.1%). The majority of caregivers

(57.5%) was fairly well educated, had greater than a high school education and had an income level of $20,000 or greater (64.1%). Finally, on average, caregivers had spent 4.33 years as a caregiver. The mean RMBPC burden score at baseline for caregivers (N = 903) was 16.11 (SD

= 13.65) indicating low burden and the mean CES-D score at baseline for the CES-D sample was 15.05 (SD = 11.23) indicating that most caregivers did not show a clinical level of depressive symptoms (Table 2).

As depicted in Table 3, the mean age of care recipients was 79 yrs. (SD = 8.22 yrs.) and 45% were males. Over half (56%) of the care recipients were White/Caucasian, almost one quarter (24.4 %) were Black/African-American; and slightly less than one-fifth (18%) was

Hispanic. Almost one-half (45%) of these individuals had less than a high school education and almost a quarter (23.4%) were high school educated. The average Mini Mental State

Examination score for the care recipients was 12.64 (SD = 7.58) of a possible 30 points. The average number of activities of daily living for which the care recipient required help was 3.31

(SD = 2.07) out of six possible activities. The number of instrumental activities of daily living for which the care recipient required help was 7.31 (SD = 1.21) out of eight possible activities

(Table 3).

Effect of Interventions on RMBPC Burden Score

The results of the site-specific analyses on the change observed in RMBPC Burden scores from baseline to six months are displayed in Table 4. The results in Table 4 indicate that the baseline caregiver burden score was statistically significant at each site, ps = .01. This effect indicates that participants with higher baseline RMBPC burden scores tended to report greater decreases on this measure at six months. Running Head: Effect of Multi-component Interventions 21

The effect of group assignment was not statistically significant at any of the sites.

Most active interventions resulted in non-significant improvements in comparison to their respective control conditions. This advantage for the active treatment condition over the control condition approached statistical significance at the Boston site, p = .09. The only other effect that approached statistical significance at the site level for RMBPC burden was that of caregiver relationship to the care recipient at the Philadelphia site. At this site it was found that non-spouses had marginally better improvements than spouses, p = .08 (Table 4).

Not shown on the table are additional models that examined whether group assignment interacted with race/ethnicity in affecting change on RMBPC burden. Adding this interaction term to the models resulted in a statistically significant group by race/ethnicity interaction effect at the Birmingham site only, F (1,90) = 5.73, p = .02. The covariate-adjusted means at this site indicated that the skill-training intervention was better than the minimal support condition for the African-American participants (Ms = -8.53 and – 1.39, respectively), whereas skill training was less effective than the minimal support condition for the White participants (Ms = -4.12 and -6.99, respectively). However, post-hoc comparisons using

Fisher’s LSD procedure showed that reductions in RMBPC burden experienced by African

Americans in skill training condition was significantly greater than the reductions reported by

African-Americans in MSC, p < .05; whereas there were no statistically significant difference between skill training and minimal support for Whites. The Boston site also showed a trend such that White caregivers in the TLC active treatment showed marginally better improvements compared to controls than did Black/African-American caregivers, p = .08. Running Head: Effect of Multi-component Interventions 22

Meta- analysis with RMBPC Change Score

Figure 1 shows the results of the meta-analysis for the six-month change in RMBPC burden. For this outcome, the nine active treatments were better than their comparison control condition, with point estimates ranging from –3.11 at Boston to 1.39 for the Miami FSMII therapy. This implies that, on average, the six-month RMBPC change in caregivers receiving the Boston TLC intervention was 3.11 points better than the change in caregivers at Boston receiving Usual Care. However, none of the parameter estimates differed significantly from 0

(p>.05). The test for homogeneity had an associated p-value of .94, indicating no evidence of departure from homogeneity. The pooled parameter estimate (-1.41; 95% confidence interval of –2.61 to –0.21) indicated that across REACH, the active interventions were superior to the control conditions with respect to six-month change in RMBPC burden. Presented in Figure 1 are unstandardized parameter estimates. In standardized terms, these effect sizes were small and ranged from -.152 (Boston) to .058 (Miami, FSMII).

Effect of Interventions on CES-D Scores

The same analytic strategy as above was used for the CES-D. The site-specific results are displayed in Table 5. The baseline CES-D score was a significant predictor of CES-

D change at all sites with higher baseline scores again being associated with greater decreases, ps < .01. A statistically significant effect for group assignment was found at the Miami site only p = .024. Here, the combination of FSMII and CTIS was more effective than FSMII alone or MSC (control group) for reducing depression. A statistically significant effect for race/ethnicity was found at the Philadelphia site, with minority caregivers reporting greater decreases than White caregivers at six months, p < .01. Conversely, a trend for race/ethnicity was found at the Miami site, with the White caregivers reporting greater decreases than Cuban Running Head: Effect of Multi-component Interventions 23 caregivers, p = .08. Not shown on the table are additional models that were conducted to examine possible group assignment by race/ethnicity interaction effects on change in CES-D.

None of these interaction effects was statistically significant (Table 5).

Meta-analysis with CES-D Change Score

Figure 2 shows the results of the meta-analysis for the six-month change in CES-D that was the primary goal of the interventions at the Miami, Memphis, and Palo Alto sites. For this outcome, the Miami combined intervention with caregivers receiving the CTIS in addition to FSMII was significantly (p<.05) more efficacious than the Miami MSC. The average six- month change was 2.56 points better in the active treatment than the control condition (95% confidence interval of –4.95, -0.17). For the six other active interventions for which the point estimate indicated that they were more efficacious than their control conditions, the difference was not statistically significant, p>.05. The test for homogeneity indicated adequate homogeneity in effect, p=.52. The pooled parameter estimate (-0.59, 95% confidence interval of –1.42 to 0.24) did not differ significantly from zero, p=.17. Presented in Figure 2 are unstandardized parameter estimates. In standardized terms, these effect sizes were small and ranged from -.160 (Miami FSMII + CTIS) to .006 (Philadelphia).

Treatment by Disposition Status for CES-D Change Score

Finally, we also conducted analyses at the site level to test the hypothesis of a differential treatment effect on CES-D score by the disposition status of caregivers (active caregiving at home, placement of care recipient, or bereaved). Some interventions were designed specifically for active caregivers (Birmingham, Boston, Memphis, and Philadelphia) whereas other interventions (Miami and Palo Alto) involved caregivers who were bereaved or who had placed their family member in long-term care. Adding a treatment by disposition Running Head: Effect of Multi-component Interventions 24 interaction term to the models however, did not result in statistically significant differences by the status of the caregiver. Findings may be limited by the small sample sizes in the placement and bereavement groups. It is possible that the null finding is due to inadequate statistical power.

DISCUSSION

REACH was designed to examine the feasibility and effectiveness of multiple intervention approaches for family caregivers of individuals with dementia. This paper reports the results of the within site analyses and the across site meta-analyses for measures of caregiver burden and depressive symptoms six months post intervention. Across the six sites there were nine active intervention conditions and six control group conditions. Each site was conducted as a randomized trial with high levels of quality control including formal treatment implementation procedures (Lichstein, Riedel, & Grieve, 1994) and the use of the intention-to- treat analytic strategy. The basic assumption was that active interventions would result in a reduction of caregiver burden and caregiver depressive symptoms at the first six-month interval of the REACH initiative.

Caregivers enrolled across the REACH sites had been providing care for an average of four years to individuals at the moderate to severe stage of dementia. Most caregivers reported minimal burden with behavior problems and were below the clinical cut-off for evidence of depressive symptoms. A comparison of caregivers who did not complete the six- month assessment to completers revealed no consistent pattern across sites. For two sites

(Memphis and Miami), non-completers reported higher depressive scores than completers. For one site (Boston), non-completers were caring for individuals with lower MMSE scores than completers. For these sites, caregivers most likely to benefit from intervention may have been Running Head: Effect of Multi-component Interventions 25 lost to follow-up. Other sites found differences in basic characteristics between completers and non-completers suggesting regional variation in recruitment and retention. Completers in active intervention groups had close to the intended treatment exposure (see Czaja et al. Paper

#3 in this series) for the first six-months at all sites, although length of active intervention varied across sites from six to 24 months.

There were not significant effects for any one intervention for the measure of burden, although for each site’s active intervention, change in burden score was in the hypothesized direction. However, the pooled estimate from the meta-analysis for burden was statistically significant (p = .05), albeit small. Overall, caregivers across the REACH sites in active intervention conditions showed greater reduction in burden with behavior problems than caregivers enrolled in the control conditions. This modest overall effect compares favorably to recent caregiver intervention studies. Shikiar et al., (2000) report a 1.34 to 1.36 reduction in caregiver burden for caregivers of patients receiving two different dosages of Metrifonate compared to caregivers in a placebo control group. The change in burden for active interventions in REACH ranged from 3.11 (Boston) to 1.39 (Miami) in comparison to each site’s control group condition. The findings are similar to those of Newcomer and colleagues

(1999), who also found very small reductions in caregiver burden following a case management intervention for only some of their participating intervention sites.

In contrast to the RMBPC burden results, the pooled estimate across sites for the meta- analysis for CES-D, was not statistically significant, p > .05. Only one site’s intervention,

Miami’s combined family therapy and technology intervention, resulted in a significant reduction in depressive symptoms, p< .05. The family therapy intervention by itself did not have a significant effect on depressive symptoms. The unique feature of the combined therapy Running Head: Effect of Multi-component Interventions 26 and technology intervention was that in addition to receiving in-home family therapy, caregivers were able to access local resources and participate in family conferences and on-line support groups using a simple computer/telephone technology. The technology may have facilitated the ability of caregivers to receive additional needed individualized support without having to leave their homes. Also, caregivers were able to control the type of resource information they received, and when and how frequently they wished to participate in on-line support groups. This finding is consistent with the caregiver intervention study by Mittleman and colleagues (1995). They report significant reductions in depressive symptoms following an intervention that combined individual and family counseling and that focused on conflict resolution concerning care plans for the patient. Their study however was confined to spouses.

Also, they had a significant treatment effect at 12 months but not at four and eight month follow-ups.

The finding of no treatment effect for the other REACH active interventions is consistent with previous studies (Knight et al., 1993). Also, as in the Mittleman et al., study, disposition of caregiver (bereaved or placement of care recipient) did not influence treatment effects.

There are several possible explanations for these mixed results and small reductions in caregiver burden and depression. First, caregivers in the REACH study sites were not selected for participation on the basis of a predetermined clinical level of reported burden or depressive symptoms. Also, in accordance with the intention-to-treat methodology, we did not exclude caregivers with minimal levels of burden and depressive symptoms from the analyses.

Consequently, 15% of the caregivers in the RMBP burden sample reported no or minimal burden with behavior problems. Similarly, a large proportion of caregivers (60%) in the CES- Running Head: Effect of Multi-component Interventions 27

D sample scored less than 16, the clinical cut-off for depressive symptoms on that measure.

Thus, for both of these outcomes, there may have been a floor effect such that many caregivers had little room for improvement or reduction of scores. Second, the control groups at each of the sites did receive some form of intervention that may have decreased our power to detect change in the active interventions. Active comparison conditions were chosen due to ethical concerns and to discourage differential dropout among groups. The usual care control groups at Boston, Memphis and Philadelphia received information packets on dementia and the stress of caregiving. Birmingham, Miami and Palo Alto utilized a minimal support control condition in which caregivers received periodic telephone contact that involved empathic listening and useful information. Birmingham’s control group, by design, received the same number of contacts as its intervention group, and involved a greater number of contacts than active interventions at other sites. Also, the sample as a whole reported a high rate of formal service use at baseline (Harrow, 2000) such that caregivers in both intervention and control group conditions were exposed to supports over and above that provided by REACH. Third, some interventions did not have as their primary goal reducing caregiver depression (Birmingham,

Boston, and Philadelphia). There may be other outcomes not measured in the REACH core batteries that are more proximal to the goals of these interventions, such as enhancement of self-efficacy beliefs. Moreover, depression may serve as a moderator of treatment effect on self-efficacy improvement, particularly for interventions that provide skills training and that are behaviorally demanding (Birmingham and Philadelphia; Gitlin, Corcoran, Winter, Boyce,

& Marcus, 1999).

Another explanation for the absence of a main effect for RMBPC burden at the site level is suggested by the complex pattern of significant findings involving various subgroups at Running Head: Effect of Multi-component Interventions 28 several of the sites. At the Birmingham site, a significant race by treatment interaction effect was found (p = .02) such that African-American caregivers in the skill training intervention had greater improvement with respect to burden compared to African-American caregivers in the minimal support group. For White caregivers, there were no statistically significant differences between skill training and minimal support. At the Boston site there was a trend such that

White caregivers in active treatment (a computer-telephone intervention) compared to controls had marginally better improvements relative to African-American caregivers, p = .08. African-

American caregivers were more likely not to use the telephone intervention (Mahoney, Tarlow,

Jones, Tennstedt, & Kasten, 2001). These findings suggest that particular caregiver characteristics may interact with specific interventions to produce positive outcomes. At the

Philadelphia site there was a trend such that non-spouses reported a greater decrease in burden in comparison to spouses (p= .08) at six months regardless of group assignment; for CES-D a main effect for race was found such that minority caregivers reported more improvement than

White caregivers at six months (p = .01) regardless of group assignment. These findings suggest that particular caregiver characteristics interact with specific outcomes independent of intervention. The challenge for future research will be to match intervention approaches with specific target populations, while recognizing that the optimal match may vary as a function of the outcome measure, regional context (e.g., Northeast vs. deep South), and characteristics of caregivers including cultural background and relationship.

In summary, using clinical trial methodology and the intention-to-treat approach, REACH was unable to identify one optimal solution to alleviating caregiver burden, although collectively, caregivers in active treatments showed more improvements. These findings suggest that a combination of treatment elements may be effective (Belle et al., paper #4 in Running Head: Effect of Multi-component Interventions 29 series). With regard to depressive symptoms, one approach, the Miami family therapy intervention combined with computer technology information systems did significantly reduce depressive symptoms following six-months of active treatment. Despite the overall lack of significant treatment effects for the two outcome measures, the results from the first follow-up at six months of the REACH initiative provide important insights for developing and testing interventions for family caregivers. The results show that there is no single, easily implemented, and consistently effective method for eliminating the multiple stresses of caregiving. For example, although the Miami FSMII + CTIS intervention reduced depressive symptoms, it did not have a significant effect in reducing burden associated with behavior problems. It is our belief that a multi-component intervention that includes elements that target different aspects of the caregiving experience (e.g., affective responses, behavioral burden, unsafe physical environments) might be most beneficial. Moreover, interventions may need to be tailored to match specific characteristics of caregivers including cultural background and relationship to the care recipient. Future research is necessary to systematically test this approach.

Finally, the findings here should be tempered by the interval of data collection, possible insensitivity of the measures to the components of caregiver distress that may have been positively affected and that these interventions may be beneficial for some subgroups but not others. A limitation of the analytic approach presented here is that it does not fully take advantage of the power of REACH and its potential to yield information about optimal intervention strategies. To address this goal, REACH developed a comprehensive classification system for characterizing and measuring caregiver interventions that captures the content, process, and goals of an intervention in a theoretically relevant manner. This Running Head: Effect of Multi-component Interventions 30 classification system is presented in Czaja et al. (under review), and Belle et al. (under review), in this series. The analyses based on the classification system that are presented in these papers extend the traditional analyses presented here.

Running Head: Effect of Multi-component Interventions 31

References

Aranda, M. & Knight, B. (1997). The influence of ethnicity and culture on the caregiver stress and coping process: A sociocultural review and analysis. The Gerontologist,

37, 342-354.

Belle, S. H., Czaja, S. J., Schulz, R., Burgio, L., Gitlin, L. N., Jones, R.,

Mendelsohn, A. B., & Ory, M. (2001). Using a new taxonomy to combine the uncombinable:

Integrating results across diverse caregiving interventions. Manuscript submitted for review.

Bourgeois, M. S., Schulz, R., & Burgio, L. (1996). Interventions for caregivers of patients with Alzheimer's disease: A review and analysis of content, process and outcomes.

International Journal of Aging and Human Development, 43, 35-92.

Burgio, L., Corcoran, M., Lichstein, K. L., Nichols, L., Czaja, S., Gallagher-

Thompson, D., Bourgeois, M., Stevens, A., Schulz, R., & Ory, M. (2001). Judging outcomes in psychosocial interventions for dementia caregivers: The problem of treatment implementation. Manuscript submitted for publication.

Calderon, V., & Tennstedt, S. (1998). Ethnic differences in the expression of caregiver burden: Results of a qualitative study. Journal of Gerontological Social Work 30,

159-178.

Cohen, S., Kessler, R. C., & Gordon, L. U. (1995). Measuring stress. New York:

Oxford University Press.

Connell, C. M. & Gibson, G. D. (1997). Racial, ethnic, and cultural differences in dementia caregiving: Review and analysis. The Gerontologist 37, 355-364. Running Head: Effect of Multi-component Interventions 32

Czaja, S. J., Schulz, R., Lee, C. C., & Belle, S. H. (2001). A methodology for describing and decomposing complex psychosocial and behavioral interventions. Manuscript submitted for review.

DerSimonian R. & Laird N. (1986). Meta-analysis in clinical trials. Controlled

Clinical Trials, 7, 177-188.

Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). Mini-mental state: A practical method for grading the cognitive state of patients for the clinician. Journal of

Psychiatric Research, 12, 189-198.

Ford, G. R., Goode, K. T., Barrett, J. J., Harrell, L. E., & Haley, W. E. (1997).

Gender roles in caregiving stress: An examination of subjective appraisals of specific primary stressors in Alzheimer's caregivers. Aging and Mental Health, 1, 158-165.

Gallagher-Thompson, D., Arean, P., Coon, D., Menendez, A., Takagi, K., Haley,

W., Arguelles, T., Rubert, M., Loewenstein, D., & Szapocznik, J. (2000). Development and implementation of intervention strategies for culturally diverse caregiving populations. In R.

Schulz (Ed.), Handbook on dementia caregiving: Evidence-based interventions for family caregivers (pp.151-185). New York: Springer.

Gaugler, J. E., Davey, A., Pearlin, L. & Zarit, S. H. (2000). Modeling caregiver adaptation over time: The longitudinal impact of behavior problems. Psychology and Aging,

15 (3), 437-450.

Gitlin, L. N., Corcoran, M., Winter, L., Boyce, A., & Marcus, S. (1999). Predicting participation and adherence to a home environmental intervention among family caregivers of persons with dementia. Family Relations, 48, 363-372.

Gold, D. P., Cohen, C., Shulman, K., Zucchero, C., Andres, D., & Etezad, J. (1995). Running Head: Effect of Multi-component Interventions 33

Caregiving and dementia: Predicting negative and positive outcomes for caregivers.

International Journal of Aging and Human Development, 41, 183-201.

Haley, W. E., Han, B. & Henderson, J. N. (1998). Aging and ethnicity: Issues for clinical practice. Journal of Clinical Psychology in Medical Settings, 5, 393-409.

Haley, W. E., Roth, D. L., Coleton, M. I., Ford, G. R., West, Constance A. C.,

Collins, R. P., & Isobe, T. L. (1996). Appraisal, coping, and social support as mediators of well-being in black and white family caregivers of patients with alzheimer’s disease. Journal of Consulting and Clinical Psychology, 64, 121-129.

Harrow, B. (Nov. 2000). Measuring the cost of community based care for

Alzheimer’s family caregivers. (Paper presented at the annual meeting of the Gerontological

Society of America, Washington, DC.)

Katz, S., Ford, A. B., Moskowitz, R. W., Jackson, B. A. & Jaffe, M. W. (1963). Studies of illness in the aged, the index of ADL: A standardized measure of biological and psychosocial function.

Journal of the American Medical Association, 185, 914-919.

Kaufer, D. I., Cummings, J. L., Christine, D., Bray, T., Castellon, S., Masterman,

D., MacMillan, A., Ketchel, P., & DeKosky, S. T. (1998). Assessing the impact of neuropsychiatric symptoms in Alzheimer's disease: The Neuropsychiatric Inventory Caregiver

Distress Scale. Journal of the American Geriatrics Society, 46 (2), 210-215.

Kennet, J., Burgio, L., & Schulz, R. (2000). Interventions for in-home caregivers:

A review of research 1990 to present. In R. Schulz, et al. (Eds.), Handbook on dementia caregiving: Evidence-based interventions for family caregivers (pp. 61-125). New York:

Springer Publishing Company. Running Head: Effect of Multi-component Interventions 34

Kiecolt-Glaser, J. K. & Glaser, R. (2001). Stress and immunity: Age enhances the risks. Current Directions in Psychological Science, 10, 18-21.

Kleinman, A., Eisenberg, L., & Good, B. (1978). Clinical lessons from anthropologic and cross-cultural research. Annals of Internal Medicine, 88, 251-258.

Knight, B. G., Lutzky, S. M., & Macofsky-Urban, F. (1993). A meta-analytic review of interventions for caregiver distress: Recommendations for future research. The

Gerontologist, 33, 240-248.

Lawton, M. P. & Brody E. (1969). Assessment of older people: Self-maintaining and instrumental activities of daily living. The Gerontologist, 9, 179-186.

Lichstein, K. L., Riedel, B. W., & Grieve, R. (1994). Fair tests of clinical trials: A treatment implementation model. Advances in Behaviour Research and Therapy, 16, 1-29.

Light, E., Niederhe, G., & Lebowitze, B. (Eds.). (1994). Stress effects on family caregivers of Alzheimer’s patients: Research and interventions. New York: Springer Publishing Co.

Lockery, S. (1991). Caregiving among racial and ethnic minority elders. Generations, 15, 58-62.

Mahoney, D. M., Tarlow, B., Jones, R. N., Tennstedt, S., & Kasten, L. (in press). Factors affecting the use of a telephone-based intervention for Alzheimer’s caregivers. Journal of

Telemedicine and Telecare.

Mittelman, M. S., Ferris, S. H., Steinberg, G., Shulman, E., Mackell, J., Aminder, A., &

Cohen, J. (1995). A comprehensive support program: Effect on depression in spouse-caregivers of

AD patients. The Gerontoloist, 35, 792-802.

Newcomer, R., Yordi, C., DuNah, R., Fox, P., & Wilkinson, A. (1999). Effects of the medicare Alzheimer’s disease demonstration on caregiver burden and depression: Health Services

Research 34:3, 669-689. Running Head: Effect of Multi-component Interventions 35

Nichols, L, Malone, C., Tarlow, B., & Lowenstein D. (2000). The pragmatics of implementing intervention studies in the community. In R. Schulz (Ed.) Handbook on dementia caregiving: Evidence-based intervention for family caregivers (pp.127-150). New

York: Springer.

Nichols, L., Martindale-Adams, J., Burns, R., Coon, D., Ory, M., Mahoney, D.,

Tarlow, B., Burgio, L., Gallagher-Thompson, D., Guy, D., Argüelles, T., & Winter L. (2001).

A social marketing approach to recruitment: The Resources for Enhancing Alzheimer’s

Caregiver Health (REACH) study. Manuscript submitted for review.

Pettiti, D. B. (2000). Meta-analysis, decision analysis, and cost-effectiveness analysis: Methods for quantitative synthesis in medicine (2nd ed., p. 115). Oxford University

Press. Radloff, L. S. (1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385-401.

Radloff, L. S. & Teri, L. (1986). Use of the center for epidemiological studies depression scale with older adults. Clinical Gerontologist, 5, 119-136.

Schulz, R., & Beach, S. (1999). Caregiving as a risk factor for mortality: The caregiver health effects study. Journal of the American Medical Association, 282 (23), 2215-

Schulz, R., Gallagher-Thompson, D., Haley, W., Coon, D. & Czaja, S. (2000).

Understanding the intervention process: A theoretical/conceptual framework for intervention approaches to caregiving. In R. Schulz (Ed.) Handbook on dementia caregiving: Evidence-based interventions for family caregivers (pp. 33-56). New York:

Springer.

Schulz, R., O'Brien, A. T., Bookwala, J., & Fleissner, K. (1995). Psychiatric and Running Head: Effect of Multi-component Interventions 36 physical morbidity effects of dementia caregiving: Prevalence, correlates, and causes. The

Gerontologist, 35, 771-791.

Shikiar, R., Shakespeare, A., Sagnier, P., Wilkinson, D., McKeith, I., Dartiques, J,

& Dubois, B. (2000). The impact of Metrifonate therapy on caregivers of patients with

Alzheimer’s disease: Results form the MALT clinical trial. Journal of the American Geriatrics

Society, 48, 268-274.

Stueve, A., Vine, P., & Struening, E. L. (1997). Perceived burden among caregivers of adults with serious mental illness: Comparison of black, Hispanic, and white families. American Journal of Orthopsychiatry, 6 (2), 199-207.

Sue, D. W., Bingham, P., Porsche-Burke, L. & Vasquez, M. (1999). The diversification of psychology: A multicultural revolution. American Psychologist,

54, 1061-1069.

Tarlow, B. & Mahoney, D. (2000). The cost of recruiting Alzheimer’s disease caregivers for research. Journal of Aging and Health, 12 (4), 519-539.

Teri, L., Truax, P., Logsdon, R., Uomoto, J., Zarit, S., & Vitaliano, P. P. (1992).

Assessment of behavioral problems in dementia: The Revised Memory and Behavior Problems

Checklist (RMBPC). Psychology and Aging, 7, 622-631.

Torres-Gil, F. & Kuo, T. (1998). Social policy and politics of Hispanic aging.

Journal of Gerontologial Social Work, 30 (1&2), 143-158.

Toseland, R. W. & Rossiter, C. M. (1989). Group interventions to support family

Caregivers: A review and analysis. The Gerontologist, 29, 438-448.

Vitaliano, P. P., Russo, J., Young, H. M., Teri, L., & Maiuro, R. D. (1991).

Predictors of burden in spouse caregivers of individuals with Alzheimer's disease. Psychology Running Head: Effect of Multi-component Interventions 37 and Aging, 6, 392-402.

Wright, L., Clipp, E., & George, L. (1993). Health consequences of caregiver stress. Medicine, Exercise, Nutrition, and Health, 2, 181-195.

Wisniewski, S, Belle, S., Coon, D., Marcus, S., Ory, M., Burgio, L., Burns, R., &

Schulz, R. (2001). The Resources for Enhancing Alzheimer’s Caregiver Health (REACH) project design and baseline characteristics. Manuscript submitted for review.

Zarit, S. H. & Teri, L. (1992). Interventions and services for family caregivers. In

K.W. Schaie & M. Powell Lawton (Eds.), Annual review of gerontology and geriatrics (Vol.

11, pp. 287-310). New York: Springer Publishing Company. Running Head: Effect of Multi-component Interventions 38

Author Note

This research was supported through the Resources for Enhancing Alzheimer’s

Caregiver Health (REACH) project, which is supported by the National Institute on Aging

and the National Institute of Nursing Research (Grants: Burgio U01-NR13269, Burns U01-

AG13313, Eisdorfer U01-AG13297, Gallagher-Thompson U01-AG13289, Gitlin U01-

AG13265, Mahoney U01-AG13255, Schulz U01- AG13305).

Address correspondence to L. N.Gitlin, Ph.D. Director, Community and Homecare

Research Division, Thomas Jefferson University, 130 S. 9th Street, Philadelphia, PA 19107,

Voice: 215-503-2896 Fax: 215-923-2475 e-mail: [email protected]