Community-based Mental Health Interventions for Elderly Women in Tamil Nadu, India

Last registered on January 17, 2025

Pre-Trial

Trial Information

General Information

Title
Community-based Mental Health Interventions for Elderly Women in Tamil Nadu, India
RCT ID
AEARCTR-0015018
Initial registration date
December 12, 2024

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
December 17, 2024, 8:23 AM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
January 17, 2025, 4:44 PM EST

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Region

Primary Investigator

Affiliation
MIT

Other Primary Investigator(s)

PI Affiliation
MIT
PI Affiliation
MIT
PI Affiliation
Tamil Nadu Indian Administrate Service (Retired)
PI Affiliation
Dartmouth
PI Affiliation
MIT
PI Affiliation
MIT

Additional Trial Information

Status
On going
Start date
2024-11-18
End date
2026-10-01
Secondary IDs
NCT05856552
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Mental illnesses often go undiagnosed or untreated in low-income settings. Mental health care may be especially important for the elderly - events in the lives of the elderly, like illnesses or deaths of peers, may put these individuals at high risk of mental illness. The study will constitute a randomized controlled trial aimed at reducing depression among elderly women over a 12-week period. Through two interventions, the investigators will aim to improve women elder's outlook on life and relationships through cognitive behavioral therapy (CBT) and facilitated group activities. There will be a total of four treatment arms: one for CBT during home visits, one for facilitated group activities, one for both, and a control group receiving neither the CBT nor facilitated group activities. All activities will be delivered by lay government community volunteers. Randomization for group activities will be at the village-level, and randomization for CBT will be at the individual-level within each village. Investigators will track outcomes of the elderly at two points in time: immediately after the 12-week intervention and 6 months after the intervention.
External Link(s)

Registration Citation

Citation
Banerjee, Abhijit et al. 2025. "Community-based Mental Health Interventions for Elderly Women in Tamil Nadu, India." AEA RCT Registry. January 17. https://doi.org/10.1257/rct.15018-1.2
Experimental Details

Interventions

Intervention(s)
The intervention will deliver cognitive behavioral therapy and group activities to elderly women in rural areas of Tamil Nadu in two cross-randomized arms.
Intervention Start Date
2024-11-18
Intervention End Date
2025-09-01

Primary Outcomes

Primary Outcomes (end points)
Mental health (depression), Functional impairment
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Loneliness/Social connectedness, Sleep quality and quantity, Demand for interventions, Perceived health status, Physical mobility, Cognition, Agency, Health management behavior
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The experiment sample will comprise approximately 5,370 elderly women from 358 villages from 3 districts in Tamil Nadu, India (Tiruchirappalli, Tiruvannamalai, Dharmapuri). We will cross-randomize two interventions aimed at improving mental health: group activities will be randomized across villages, and cognitive behavioral therapy will be randomized across individuals. Outcomes will be measured immediately after the intervention, as well as at 6 months after the intervention. The interventions will be delivered by a trained group of government volunteers present at the village-level (Community Resource Persons).
Experimental Design Details
Not available
Randomization Method
Randomization will be done in Stata.
Randomization Unit
Individual-level for CBT arm. Clustered by villages for Group Activities arm.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
5,370 individuals
358 clusters (villages)
Sample size: planned number of observations
5,370 individuals
Sample size (or number of clusters) by treatment arms
50% of villages will be assigned to Group Activities and 50% of villages will not have Group Activities.
Within each village, 5 elders will be assigned to therapy and the remaining will not have therapy
The effective approximate sample size per treatment arm is:
1. Group activities only, No therapy: 179 villages * 10 elders = 1,790 elders, approximately 33% of sample
2. Therapy only, no group activities: 179 villages * 5 elders = 895 elders, approximately 17% of sample
3. Group activities and therapy: 179 villages * 5 elders = 895 elders, approximately 17% of sample
4. No group activities, No therapy: 179 villages * 10 elders = 1,790 elders, approximately 33% of sample
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
MDEs for main treatment effects: Our MDEs are conservative in that they assume a sample size of N=3,580, which assumes we are only able to recruit 67% of the intended sample size of N=5,370. We assume an intra-class correlation (ICC) of 0.33 for mental health (as measured by depression score on Geriatric Depression Scale) and 0.21 for functional impairment (as measured by disability score on World Health Organization Disability Assessment Scale). The ICC estimates are based on baseline data from the Tamil Nadu Elderly Panel Survey (2019) when subsetting the sample to elderly women in rural areas. We assume that including baseline covariates and strata fixed effects reduces the residual variance in the outcome measure by 20%, thus decreasing standard errors accordingly. Given our two cross-randomizations occur at different levels (CBT is randomized across individuals; Group activities are randomized across villages), we include MDEs for both clustered and unclustered regressions. Specifically, we will estimate three different regressions. The first will regress the outcome on an indicator for CBT treatment (along with other covariates), without clustered standard errors. The second will regress the outcome on an indicator for GA treatment (along with other covariates), with clustered standard errors. The third will regress the outcome on indicators for assignment to CBT treatment only, GA treatment only, and both (along with other covariates), with clustered standard errors. The other covariates will be strata fixed effects, surveyor fixed effects, and the value of the outcome measured at baseline. Additionally, in the first regression we will control for GA treatment, and in the second we will control for CBT treatment. Regression 1. MDE for treatment effect of therapy without clustered standard errors, if running a regression pooling across Group Activities arms is 0.09 SD for both primary outcomes (mental health and functional impairment). Regression 2. MDE for treatment effect of Group Activities with village-clustered standard errors, if running a regression pooling across CBT arms is 0.18 SD for mental health and 0.16 SD for functional impairment. Regression 3. MDE for treatment effects of (1) CBT only, (2) Group Activites only, and (3) CBT + Group activities (relative to a control group of elders who do not receive CBT and are in villages without Group Activities) with village-clustered standard errors, if running a regression with the third specification is 0.2 SD for mental health and 0.18 SD for functional impairment. MDEs for Actigraph-based measurements (sleep and mobility): Some of our outcomes rely on device-based measurements using Actigraph wearable devices. First, we use Actigraphs to measure sleep (time asleep and efficiency, which is time asleep divided by time in bed). Second, we use Actigraphs to measure step count, which is a measure of mobility. For these outcomes, we only intend to collect data from N=1000 elders from N=358 villages, constituting approximately 20% of our sample. For both sleep and step count, we assume an ICC of 0.26, which is the ICC observed in self-reported sleep hours in wave 1 of the Tamil Nadu Elderly Panel Survey (2022). We will estimate the same specifications for these outcomes as described above, except we will not have baseline measures of these outcomes to include as controls. Regression 1. MDE for treatment effect of therapy without clustered standard errors, pooling across Group Activities arms is 0.18 SD for both the sleep time and step count outcomes. Regression 2. MDE for treatment effect of Group Activities with village-clustered standard errors, if running a regression pooling across CBT arms is 0.22 SD for both the sleep time and step count outcomes. Regression 3. MDE for treatment effects of (1) CBT, (2) Group Activites, and (3) CBT + Group activities (relative to a control group of elders who do not receive CBT and are in villages without Group Activities) with village-clustered standard errors, if running a regression with the third specification is 0.29 SD for both the sleep time and step count outcomes.
IRB

Institutional Review Boards (IRBs)

IRB Name
Massachusetts Institute of Technology Institutional Review Board
IRB Approval Date
2023-11-16
IRB Approval Number
2309001107