Northern Manhattan Caregiver Intervention Project (NOCIP)

Elderly Hispanics have a higher burden of dementia compared to Non-Hispanic Whites. Furthermore, Hispanic caregivers tend to have a higher burden of care for their relatives with dementia. The objective of this application is to conduct a randomized trial in 160 Hispanic relative caregivers of persons with dementia comparing the effectiveness of New York University Caregiver Intervention to a case management intervention lead by community health workers(CHW). This trial will last 6 months. The main outcomes in the trial will be changes in depressive symptoms measured with the Geriatric Depression Scale and caregiver burden measured with the Zarit Caregiver Burden Scale. This research project will be conducted by the Northern Manhattan Center of Excellence in Comparative Effectiveness Research for Eliminating Disparities (NOCERED) funded by the National Institute on Minority Health and Health Disparities.

1. SPECIFIC AIMS:

   The goal of this study is to compare the effectiveness of an existing evidence-based dementia family caregiver intervention, the New York University Caregiver Intervention (NYUCI), to community-based case management using community health workers (CHWs) in Hispanic caregivers in Northern Manhattan. The investigators will randomize 160 relative caregivers of persons with dementia to case management alone or NYUCI in addition to case management. The total duration of followup will be 6 months. We will call this project the Northern Manhattan Caregiver Intervention Project (NOCIP).

   Our primary aim is to compare changes from baseline to 6 months in caregiver depressive symptoms, measured with the geriatric depression scale (GDS), and in caregiver burden using the Zarit caregiver burden interview (ZBI), between the randomization arms using an Intent to treat approach.

   We hypothesize that depressive symptoms and caregiver burden will improve or deteriorate less in the NYUCI arm compared to the case management arm at 6 months.

2. BACKGROUND AND SIGNIFICANCE. This project addresses one of the priority areas for comparative effectiveness research (CER) from the Institute of Medicine, "interventions for caregivers of persons with dementia". It also addresses 2 priority conditions from the Agency for Health Care Research and Quality (AHRQ): Dementia and Depression. Dementia caregiver burden is a major source of disparities in Northern Manhattan. The prevalence of dementia in Hispanics is twice that of Non-Hispanic Whites. In addition, Hispanic families tend to be reluctant to delegate the care of their relatives with dementia and consider it a family affair. Thus, the burden of care-giving for persons with dementia is much higher in Hispanic families. NOCIP will be the first study to test the effectiveness of an existing caregiver intervention, the New York University Caregiver Intervention, in the Hispanic community of Northern Manhattan. In addition, the NYUCI has been tested in spouse caregivers, and NOCIP will be the first randomized clinical trial to include non-spouse caregivers.

3. METHODS:

   • Participants. Study subjects will be Hispanic relative caregivers of persons with dementia.

   • Recruitment. There are several recruitment strategies including:

     • Outreach in clinical practices in Northern Manhattan.
     • Dissemination and outreach at Senior centers and organizations that cater to the elderly and persons with dementia such as the Alzheimer's Association.
     • Advertisement in local and city wide newspapers.
     • Talks in the community.
   • Randomization and blinding: Following consent, determination of eligibility and completion of baseline measures, the coordinator will alert the Data Coordinating Center electronically either via encrypted email or data uploads to a secure server. Respondents will be randomized to treatment or active placebo groups. The randomization algorithm accommodates rolling enrollment, and the results are checked periodically for balance.
   • Power for primary analyses: Cohen's d ranged from 0.37 to 0.54 or between 4 and 5 points on the ZBI or GDS endpoint means -- roughly equivalent to a 0.5 SD endpoint difference in means -- or a moderate effect size. Conservatively, under the assumptions specified above, 80 subjects per group will provide power ≥ 0.80 to detect a 4 to 5 unit differential change in depression and burden, based on testing the Time X Group interaction in a MANOVA, allowing for heterogeneous variances and serial correlations. Even if the pooled variance is higher than assumed, medium effect sizes are still detectable. Thus, 80 subjects per arm will provide sufficient power to detect the hypothesized difference between the active control and the intervention arm of the study.

   • Analysis for Primary Aim 1: Those assigned to the intervention will, on average, exhibit greater 6-month decreases in ZBI and GDS than those assigned to the education active control condition. The primary proposed analyses will use mixed random effects models, and a FIML approach, with sensitivity analyses using GEE. The change from pre- to post-treatment values of continuous outcomes will be modeled as functions of baseline values, treatment and the interaction of baseline and treatment. A general longitudinal mixed effects model, using SAS PROC MIXED will be used to allow for the possible group heterogeneity in residual variances and serial correlations that may require modeling to satisfy model assumptions and improve model fit. There may be violations of the more rigid assumptions involved in ANCOVA, such as homoscedasticity, so that modeling the group heterogeneity in residual variances may be necessary. Based on prior analytic experience with the outcome variables, it is not expected that transformations will be necessary. Prior to analyses, baseline values of all variables from each arm will be examined; however, no p values will be provided, and covariates are not proposed for inclusion in the main analyses of treatment effects. Depending on the severity of missing data, other modeling techniques may be used. Examination of baseline differences on key variables between completers and those lost-to-follow-up will be conducted to inform about the nature of the missing data. The intent-to-treat analyses performed using SAS PROC MIXED will permit all individuals with at least one observation will be included. Other methods of examining missing data (e.g., propensity scores and multiple imputation) are discussed. Depending on the observed correlation between the dependent variables, MANOVA or MANCOVA will be performed in sensitivity analyses. A significant interaction term for one of the groups would indicate that the effect of one of the treatments is different for ZBI and GDS; in that case two treatment effects will be estimated for each outcome. If the interaction is not significant a model with only main effects for the outcomes and treatment will be fit and the treatment effect (common for ZBI and GDS will be estimated from this model. In addition to significance testing, we will estimate the treatment effects with 95% Confidence Intervals. The general hypothesis is that, controlling for covariates (if needed), the vector of means will differ over time between groups. In the simple case, we can test the hypothesis of no effect by calculating the vector of change scores for each group. Or we can adjust each vector of means for prescore level, and test the hypothesis of equality of means for the groups using Wilks' lambda or Hotelling's T2. More powerful methods such as a risk score test may be used, depending upon whether all endpoints are affected equally or not. Bartlett's test of sphericity will inform about the degree of intercorrelation among the outcome measures in order to determine suitability of the basic MANOVA model. Using collinearity diagnostics and examination of correlations, the final covariate set will be selected. It is anticipated that there will be: ky = 2 non-redundant outcomes (depression and burden) kc = 1 exogenous baseline covariate kx = 1 dummy variable (NYU intervention). Depending on the results of the analyses of bias due to attrition or selection, other covariates may be included. Randomization should obviate the need for covariates in the analysis. However, selection and attrition bias, and failures of randomization may occur. If one or more sources of potential bias are identified, the predicted values from those analyses will be included as covariates in secondary analyses.

     • Selection bias: Subject to informed consent, data (e.g., gender, age) participants will be compared with those who refuse. If non-trivial differences are observed, a probit model predicting non-participation will be performed using the combined sample of participants and non-participants. If the results from this model show that participation is non-trivially related to one or more background characteristics, the predicted values from this probit model will be incorporated as a covariate in the analyses.
     • Attrition bias: Information from the baseline assessment will allow for comparisons between completers and dropouts with regard to sociodemographics, baseline ZBI and GDS, and other covariates. A probit model of attrition will be developed. Should the results indicate that attrition is significantly related to one or more baseline characteristics, the predicted values from this model can be used as a covariate to adjust for differential attrition. Depending on the degree of bias, another approach is to perform propensity score analyses, in which the treatment groups are combined, and a logistic regression predicting original group membership from covariates performed. The resulting probabilities are then arrayed in quintiles, and the subjects within each quintile randomly assigned to new groups. The analyses will be re-run with the new group designations in order to determine if the effects were similar in the new analyses with groups equalized.
     • Treatment of Missing Data: Using the above-described maximum-likelihood approach to estimate treatment effects, we will include the baseline data for these subjects in the analysis. Under the assumption that the missing data are either Missing Completely at Random (MCAR) or Missing at Random (MAR), this method, in conjunction with the covariate to adjust for attrition bias (if necessary), yields intent-to-treat parameter estimates that are consistent with what would be expected if there were no missing data. Scales will be prorated for missing data, using individual imputation algorithms developed by the measurement statisticians at the DCC. Missing data are only replaced for those who are missing less than 50% of items.
     • Intervention Dose: Because the analysis and inference is based on intent-to-treat, an attempt will be made to obtain post-treatment data from all participants randomized, regardless of whether they attended any or all of the sessions. Non-completion will thus not necessarily result in the loss of 6-month follow-up data, and will minimize bias for group comparisons. Inclusion of all participants in between-group comparisons, regardless of the number of sessions attended may be overly conservative because not all participants will have received the full "dose". However, inclusion of participants who received only part of their targeted program is more reflective of the real-world impact because most programs do not retain all participants and not all make full use of most programs. Nonetheless, secondary analyses will be conducted so as to investigate the impact of differential participation, stratifying the participants in the treatment conditions based on their degree of participation and examining differences between strata on the outcome measures at follow-up.

• Behavioral: New York University Caregiver Intervention (NYUCI)
  The NYU Caregiver Intervention (NYUCI) has substantial evidence of efficacy. This intervention is unique in its emphasis on family support and in providing ongoing availability of the counselor. While the NYUCI is being implemented in several communities, its effectiveness in the Hispanic community of Northern Manhattan has not been tested. The first component of the intervention consists of two individual and four family counseling sessions that include relatives suggested by the caregiver. The second component of the intervention is participation in a support group to provide the caregiver with continuous emotional support and education. The third component of the treatment is "ad hoc" counseling the continuous availability of counselors to caregivers and families to help them deal with crises and with the changing nature and severity of their relatives' symptoms over the course of the disease.
  Other Name: NYU Caregiver Intervention
• Other: Community Health Worker Case Management
  The CHW intervention will consist of 2 visits in month 1, followed by monthly visits until month 6. The main role of the CHW will be to provide access to existing education and referral resources about dementia and caregiving. In addition, CHW will assess other health and social issues and provide information on existing resources on Northern Manhattan. The CHW will carry a blackberry or iPhone type device with real time access to email, text, the internet, and telephone. Thus, the CHW will be able to provide participants with real time information from pertinent websites such as CUMC, Alianza, and the NY chapter of the Alzheimer's Association. CHW will also provide participants with their phone number and email address for ad-hoc contacts.
  Other Name: CHW

• Experimental: NYUCI
  New York University Caregiver Intervention (NYUCI) in addition to community-based case management using community health workers.
  Intervention: Behavioral: New York University Caregiver Intervention (NYUCI)
• CHW
  Community-based case management using community health workers (CHWs).
  Intervention: Other: Community Health Worker Case Management

• Luchsinger J, Mittelman M, Mejia M, Silver S, Lucero RJ, Ramirez M, Kong J, Teresi JA. The Northern Manhattan Caregiver Intervention Project: a randomised trial testing the effectiveness of a dementia caregiver intervention in Hispanics in New York City. BMJ Open. 2012 Sep 14;2(5). doi:pii: e001941. 10.1136/bmjopen-2012-001941. Print 2012.
• Andrieu S, Aboderin I, Baeyens JP, Beard J, Benetos A, Berrut G, Brainin M, Cha HB, Chen LK, Du P, Forette B, Forette F, Franco A, Fratiglioni L, Gillette-Guyonnet S, Gold G, Gomez F, Guimaraes R, Gustafson D, Khachaturian A, Luchsinger J, Mangialasche F, Mathiex-Fortunet H, Michel JP, Richard E, Schneider LS, Solomon A, Vellas B. IAGG workshop: health promotion program on prevention of late onset dementia. J Nutr Health Aging. 2011 Aug;15(7):562-75.

Inclusion Criteria:

• Must be caring for a relative with a clinical diagnosis of dementia and have the primary responsibility for their care. All people with dementia must be living at home with their caregiver when they enroll in the study.
• In each family, the person with dementia or the caregiver has to have at least one relative living in the New York City metropolitan area.
• The caregiver must be emotionally and physically capable of participating. Caregivers with clinical depression or other serious mental illness will be referred.