Design
We employ a Stepped Wedge Cluster Randomized Controlled Trial (SW-CRCT), with a nested health economic evaluation to assess the impact on persons with Common Mental Disorders (CMD) and return on investment of the intervention in the Indian state of Gujarat.
The stepped wedge design is chosen for evaluating the scale-up of Atmiyata intervention as it allows for random allocation of the time at which clusters receive an intervention (15), and all clusters receive the intervention before the trial ends which is ethically appropriate. The design also allows for Atmiyata intervention to be delivered in a staggered manner to account for practical and logistic constraints. Logistically, it is not feasible to start delivering the intervention in all clusters (villages served under groups of PHCs) simultaneously. A stepwise implementation allows the implementation team enough preparation time and is an efficient use of implementation team resources. Additionally, the staggered implementation of the intervention over time periods allows for more in-depth statistical analysis than a simple pre-post, parallel arm cluster randomized controlled trial design.
There are 56 primary health centers (PHCs) in Mehsana district (where the study takes place), and each PHC serves discrete villages within a geographical area. Each village in the geographical area served by a PHC is a cluster in this study. We created 4 groups of clusters (A, B, C, D), each made up of villages covered by 14 PHCs. The groups are created according to geographical location to help reduce the probability of contamination between groups. Thus, villages in Group A are farther from Group B villages and villages in Group C are farther from Group D and so on. All groups (A, B, C, D) are allocated to intervention condition at different steps. A ’Step’ is the order in which a group of clusters switches from control to intervention condition. On the other hand, ’Period’ is defined as group of observations by time of measurement. The duration of each period is 5 months to accommodate for baseline and 3 months follow-up data collection [Figure 1].
This study uses a repeated cross-sectional design with outcome data derived from different participants in each period. All four groups start at baseline in the control condition and are exposed to the intervention at regular time period of five months [Figure 1].
Setting
Mehsana district, the study site, located in Western India in the state of Gujarat is primarily a rural district (75% rural), with a rural population of 1.52 million people, of which approximately one million are above 18 years of age. The district is divided into 10 blocks/ sub districts with a total of 645 villages and 316,536 rural households (16). Almost half (45.4%) of Mehsana’s rural population has a low standard of living as per the Standard of Living Index. Most residents (53%) are employed in the agricultural sector. The rural population of Mehsana district is economically disadvantaged as agriculture is not always a viable occupation given uncertain climatic events (16). In terms of health services, Mehsana has 56 PHCs, 11 Community Health Centers and 1 District Hospital staffed by 2 psychiatrists, along with District Mental Health Program (DMHP) which provides additional human resources (such as a psychologist and social worker) for mental health at the community level. Mental health care is primarily delivered by psychiatrists at the District Hospital and the psychiatrists also visit Community Health Centers on a fortnightly basis in rotation, as part of DMHP. The district hospital has in-patient and out-patient services for persons with mental illness, and limited psychosocial support services.
Participants
The study sample consists of adult community members with common mental disorders (i.e. anxiety and depression) residing in rural villages in Mehsana district.
Inclusion Criteria:
- Persons aged 18 years or more and less than 65 years of age
- A score of 3 or above on the General Health Questionnaire (GHQ-12), indicating a case with common mental disorder
Exclusion criteria:
- Persons who cannot give informed consent or decline participation in the study
- Persons with a terminal medical condition
- Persons who have suicidal ideation or plans for suicide at baseline interview
Primary outcome
The primary outcome is symptomatic improvement of depression and anxiety as measured using a validated Gujarati version of the General Health Questionnaire- 12 (GHQ-12) (17) from baseline to 3-month follow-up with an 8-month follow-up to evaluate sustained effects of the intervention. The GHQ is a widely used screening tool with reliable sensitivity for assessing CMD (18). GHQ-12 is a dichotomous 12-item questionnaire with each item rated on a 4-point scale, with possible responses being "less than usual," "no more than usual," "rather more than usual," or "much more than usual." We used a bimodal scoring method, whereby "less than usual" and "no more than usual" is scored as 0 point, and "rather more than usual" and "much more than usual” is scored as1 (17).GHQ-12 scores will be analyzed as both continuous (ranging from 0 to 12) and categorical outcomes (case defined as 3 and above score on GHQ scale; non-case as less than 3 score on GHQ scale).
Secondary outcomes
Secondary outcome measures are assessed at 3 months, and 8 months after the start of the intervention [Table 1].
Quality of life (QOL): Improvement in quality of life of persons with CMDs is assessed using the validated Gujarati version of EURO Quality of life 5D (EQ-5D) (19).The EQ-5D’s descriptive system is a preference-based Health Related Quality of Life measure with one question for each of the five dimensions that include mobility, self-care, usual activities, pain/discomfort, and anxiety/depression measured at 5 levels: no problems, slight problems, moderate problems, severe problems, and extreme problems. Lower score indicates better quality of life (19).
Psychiatric symptoms: Improvement in psychiatric symptoms is assessed using a validated Gujarati version of Self Reporting Questionnaire (SRQ). SRQ is a scale developed by the World Health Organization to screen for psychiatric disturbances for low- and middle-income countries consisting of 20 questions which are scored 1= yes and 0=no indicating presence or absence of a particular symptom over the past month. SRQ is a continuous scale; responses are calculated as total score ranging from 0 to 20 with lower scores indicating recovery of symptoms (20).
Disability: Reduction of disability and reduction in number of days unable to work and improvement in productivity is assessed using validated Gujarati version of WHO-DAS-12. WHODAS-12 is useful for brief assessment of overall functioning as it assesses difficulties due to health conditions. The scale uses12 items, 5-point rating scale ranging from none, mild, moderate to severe and extreme. Responses are calculated as a total score ranging from to 12 to 60 (21).
Depression and anxiety symptoms: Improvements in depression symptoms is assessed using a validated Gujarati version of Patient Health Questionnaire (PHQ-9). PHQ-9 total scores range from 0 to 27greater score indicating greater symptoms (22). Improvements in anxiety scores is assessed by using a validated Gujarati version of Generalized Anxiety Disorder (GAD-7) with total scores ranging from 0 -21 (23).
Social Participation: Increased social participation is assessed using the Social Participation Scale (SPS). The SPS is an 18-item interview-based instrument which measures perceived problems in major domains of life such as learning, communication, mobility, self-care, domestic life, interpersonal interactions, major life areas and community etc. The scale allows quantification of participation restrictions experienced by people affected by disability or other stigmatized conditions. The 18 items are rated on a 5-point scale ranging from 0 (no problem) to 5 (large problem). Responses are calculated as total score ranging from 0 to 90 (24).
Service User Satisfaction: User-satisfaction with the intervention is assessed using a validated Gujarati version of the Client Satisfaction Questionnaire (CSQ) (25) at 8-month follow-up. The CSQ is an 8-item scale assessing client satisfaction with care/treatment received. The scoring uses a 4-point rating scale and is scored by summing the individual scores to produce a range of 8 to 32, with higher scores indicating greater satisfaction with care (25).
Table 1: Follow-up assessment of tools with time points
|
ASSESSMENTS TOOLS
|
At Baseline
|
At 3months
|
At 8months
|
|
Demographic details
|
✓
|
✓
|
✓
|
|
General Health questionnaire
|
✓
|
✓
|
✓
|
|
Self-Reporting Questionnaire
|
✓
|
✓
|
✓
|
|
Social Participation Scale
|
✓
|
✓
|
✓
|
|
EURO-5D Quality of Life
|
✓
|
✓
|
✓
|
|
WHO-Disability scale
|
✓
|
✓
|
✓
|
|
General Anxiety Disorder Scale
|
✓
|
✓
|
✓
|
|
Patient Health Questionnaire
|
✓
|
✓
|
✓
|
|
Client Satisfaction Questionnaire
(only in intervention condition)
|
-
|
-
|
✓
|
|
Economic Questionnaire
|
✓
|
✓
|
✓
|
Economic Evaluation
The most common measure of efficiency in the health sector is cost-effectiveness analysis (CEA) which measures only health related benefits and expresses these in natural unit such as lives saved, or symptoms reduced. However, return of investment (ROI) analysis expresses all the benefits in monetary terms. Expressing both the costs and the full range of benefits of an intervention in the same units (money) has the distinct advantage of making investment decisions very straightforward (26). If the money value of benefits of an intervention is larger than the cost of the intervention, it may be regarded as a sound investment. Hence, we have chosen to do a Return of Investment (ROI) analysis for the Atmiyata intervention. We will follow the reporting guideline of the ROI in global mental health innovation. (26).
Costs are calculated using both government and societal perspective (26). Perspective determines the cost components to be included in any cost analysis and societal perspective is the broadest viewpoint which covers all costs irrespective of who incurs these costs. On the other hand, a government perspective only includes costs incurred by the government for a particular health intervention. Costs are accounted under two categories: 1. total cost of the intervention and; 2. treatment cost of CMDs. Treatment costs are further accounted under three sub-headings: direct medical cost, direct non-medical cost and indirect costs. Direct medical cost includes out of pocket expenses on seeking treatment, diagnostic tests, fees for consultation in clinics, traditional healers, hospitals, bed day charges at a health facility (private and/or public) etc. Direct non-medical cost includes amount spent for travelling to the health facility for the patient and accompanied persons for treatment, amount spent on meal / food taken while waiting for treatment, expenses for overnight accommodation for seeking care etc. Indirect cost is the opportunity cost for the patient and their household members’ time related to CMD. Cost data is collected at baseline, 3 months and 8 months from all study participants. Time spent by the champion will be obtained from the programme implementation data. Minimum wage rate of Gujarat will be used to value their time. Total hours spent for the programme will be multiplied by hourly wage (obtained from minimum wage rate) to get the time cost of the Champions. Benefits are considered in terms of improved health, functioning, participation, productivity, increased saving and investment, reduced informal care giving and health and welfare services.
Intervention condition
The Atmiyata intervention has been described extensively elsewhere (13). Briefly, Atmiyata is a complex psychosocial intervention involving two-tiers of community volunteers for identification and support to people in distress and with symptoms of common mental disorders. The first tier consists of community volunteers called Atmiyata Mitras who are from different caste and religion-based sections of the village, trained to identify persons with mental distress. The second tier is Atmiyata Champions (CH), who are important community members (e.g. former teachers, community leaders) with leadership and communication skills and are well-known and approachable in their village. Champions are trained to identify and provide structured counseling to persons with significant mental distress, including the ones referred by Mitras. Given the social barriers based on caste, gender, religion, the identification and support by Champions and Mitras ensure equitable reach and improves coverage of the intervention across the entire village.
In the Atmiyata pilot intervention in the state of Maharashtra in 2013-2015, Champions and Mitras were trained by the project team. In this study, the Atmiyata Gujarat program, where the target population is substantially larger, Champions are identified and trained by Community Facilitators (CF) who typically have a master’s degree in social work or related fields, are locally based and aware of community dynamics. Facilitators first map their allotted villages, then identify and recruit the Champions, train them and provide ongoing mentoring support to Champions. The CFs are recruited, trained and mentored by Project Managers (PM). Each Project Manager supports 7-8 Community Facilitators. Each CF supports 40-50 Champions (1 per 1000 population), and each Champion has 4-5 Mitras. Principal Investigator (PI) monitors and supports the project managers. [Figure 2]
Mitras receive 4 hours of training from the Champions at the village. Champions receive 40 hours of training over 3 weeks, at a central location in the block or village area. Project Managers and Community Facilitators receive 55 hours of training over 5 weeks, with additional 8-hour sessions on how to be a master-trainer. The methodology of the training is interactive, reflective and participatory.
The Champions are trained : (i) to identify persons with CMD and provide evidence-based 4-6 counselling sessions ; (ii) to raise community awareness on social issues by ‘narrow-casting’ four films; 10-minute films dubbed in Gujarati on commonly experienced social issues in the community such as unemployment, family conflict, domestic violence, and alcoholism. Films are developed to build community mental health awareness and are not for training or intervention delivery. (28); (iii) make referrals of persons with severe mental disorders (SMD) to mental health services offered within the public health system when required, and (iv) enable access to social benefits for persons with mental health problems.
Counselling sessions by Champions are based on three evidence-based techniques: active listening, activity scheduling and problem-solving techniques which have been used in other similar task sharing programs (29,30). The training includes basic skills of empathy, non-judgemental behaviour, rapport building, verbal and non-verbal communication and creating a safe environment to build skills for ‘active listening’. Activity scheduling techniques enable individuals to explore reasons why they have been avoiding activities, and schedule pleasurable and valuable activities to resume day to day routine (31, 32). Problem solving techniques are used for a positive orientation towards the problem which enables viewing problems as solvable, and as opportunities to learn and change. Champions are trained to deliver 4-6 sessions of counseling over a period of 6 to 12 weeks, with no set time between sessions. Each session lasts 20 to 40 minutes based on mutual agreement between the Champion and the participant. The number of sessions delivered to the participant is also left to mutual agreement between the Champion and the participant. As this is an implementation research study, we aim to assess what happens when the intervention is implemented in ‘real-life’ settings where the number, duration and frequency of sessions will vary between different provider (Champion) and-participant dyad. We therefore, provide broad guidelines and recommendations on the number, duration and frequency of sessions to Champions (e.g. a range of sessions from 4-6 sessions, duration from 20-40 min, and period of 6-12 weeks) which both mimics what is likely to happen in real-life clinical settings and allows us to explore the possibility of dose-response effects in the study. Champions deliver the intervention at the participant’s home or immediate surroundings at a location preferred by the participant (e.g. champion’s home, a community place such as village hall, temple etc.). Thus, participants do not have to travel to receive the intervention. The delivery of intervention is in Gujarati language.
Adverse events
We considered adverse events as attempted suicide, self-harm or death by suicide. A protocol for reporting and recording of adverse events is provided in supplementary material. All the team members are trained by the data manager and PI on proper identification, recording and reporting of adverse events. All adverse events are tracked as per the protocol and reported to institutional Ethics Committee within 15 days of occurrence.
Comparison condition
Participants in the control condition receive Enhanced Usual Care (EUC). EUC is offered to all participants in the comparison condition who scored 3 and above on GHQ-12. EUC provides information on the impact of distress on their physical and mental health and relevant information of accessible and available public mental health care services, including services by District Mental Health Program (DMHP), and help lines for mental health support and for domestic violence in and around Mehsana district.
The EUC also has provision for providing active support to participants in crisis. A crisis is defined as the participant revealing a recent self-harm attempt or expressing thoughts of self- harm during data collection. Such participants are encouraged to seek help immediately and the data collectors seek participant consent to inform their family member or a friend about the crisis and thus, mobilize social support to deal with the crisis.
Sample size and power calculations
A trained lay health worker led intervention study conducted in India reported a risk difference of 12% at follow up between intervention and control condition for recovery of CMD patients (33,34). The sample size for this SW-CRCT is calculated to detect a 13% difference in CMD cases at 3-month follow-up using GHQ-12 as a categorical measure between intervention (58% improved) and control condition (45% improved). Assuming an intra-cluster correlation coefficient (ICC=0.1), number of steps (t=4), number of clusters randomized in each step (k=14), average cluster size (m=4), power (80%) and alpha of 0.05, translates to 1120 participants, i.e., approximately 56 individuals per cluster per period. [Figure 1, 3] The sample size was calculated using “stepped wedge” function of STATA version 14 (35).
Randomization and treatment allocation
The unit of randomization in stepped wedge trials is a cluster or group of clusters, allocated to different steps. In India, PHCs serve discrete villages and hence we have used the PHC as a unit to identify discrete geographical areas consisting of all villages under a PHC. This geographical area is taken as a cluster for our study. Typically, a PHC in Gujarat covers a population of 25000-30000 across 12-13 villages. There are 56 PHCs in Mehsana district, so we created 4 groups (A, B, C, D), each group consisting of all villages under 14 PHCs. These groups of clusters (A, B, C, D) are sequentially allocated to different steps at given time periods. Randomization takes place at the level of participants, all the participants are randomly selected for each period from each of these groups of clusters (A, B, C, D) as described in the recruitment section below. The administrative organization of primary health care in Gujarat ensures that inter-PHC movement of people for health care is minimal and avoids contamination of the intervention.Since double-blinding is not possible in such psychosocial intervention trials, several other procedures are used to minimize contamination and bias. To minimize contamination due to the intervention and control village members meeting and potentially discussing the intervention, clusters are geographically dispersed. Second, the data collection team is separate from intervention team and blind to the treatment status. Third, the data collection staff receives initial training and re-training at repeated intervals to ensure quality of data collected.
Recruitment
For control condition, a screening list is generated from district electoral roll using systematic random sampling method with pre-decided random start and random interval, with every nth number from the pool being selected. We used electoral roll as it is the most complete, comprehensive and accessible national frame of residential addresses in India and are extensively used for drawing random sample for general population (36). For each groups of clusters (A, B, C, D) electoral rolls from all the villages under 14 PHCs are included. Since the prevalence of CMD is 4-8%, according to the National Mental Health Survey, India (1), a screening list using a minimum prevalence of 4% and assuming 25% missing persons is prepared. For each group (A, B, C and D) in each period of the control condition, a screening list of 1800 participants is created and screened (GHQ-12 score of 3 and above) to achieve the target sample of 56 participants.
A different recruitment procedure is used in the intervention condition as using structured questionnaires for identification (e.g. GHQ, PHQ) was perceived as impractical when implementing the intervention at scale and seen as stigmatizing in a community setting. Champions are trained to identify a person in their catchment area (i.e. villages) with CMD based on symptoms described by the participant during an unstructured interview. As described earlier champions received detailed training in identifying symptoms of distress as well as depression and anxiety.When a Champion identifies a person, who in their opinion has CMD and who they intend to provide 4-6 counselling sessions, they are asked to inform their CF who in turn informs the project manager who creates a caseload list for each Champion. All these caseload lists are then merged to create a master list. The sample for the intervention condition is drawn from this master caseload list using computer generated random method. The drawn sample is screened by data collection staff using GHQ-12 (score of 3 and above) for recruiting intervention participants. This screening and subsequent baseline data collection for participants meeting the inclusion criteria is done prior to the Champion starting psychosocial counselling sessions with the participant. This process is continued till the target sample size of 56 cases is reached for each cluster and period. Different recruitment procedure for control and intervention condition was chosen as one of the secondary outcomes of the study is to check the specificity of identification of CMD cases by champions. The recruitment procedure in the intervention group allows us to answer this question of specificity of identification by Champions. Using similar recruitment procedure in both control and intervention condition (using electoral rolls) would have answered the sensitivity question (how many people with common mental disorders were identified by the Champion) but not allow us to address the specificity question. The sensitivity question relates to coverage (how many persons in the population with CMD are identified and receive the intervention), but given that we are using volunteers, we first want to establish whether these Champions are accurately able to identify persons with CMD, before addressing the coverage question. Furthermore, we have other data to estimate the population coverage of the intervention. To account for recruitment as a potential confounder, the statistical analysis plan includes adjusting for baseline covariates (baseline data for all the scales), assuming baseline differences between control and intervention participants.
Data collection
Written Informed consent is sought from all participants. A thumb impression and signature of a witness is taken for illiterate participants (37). Data is collected by trained researchers in two stages using paper pencil method. In the first stage, demographic data along with GHQ-12 is collected. The data collectors score the GHQ using a scoring sheet and if the participant has a score of 3 or more, secondary outcome data is collected at same time. The questionnaire for secondary outcome data takes 40-45 minutes to complete. Participants are not compensated for their time, as this is a volunteer-led intervention. Data collection staff travel to participant’s home for data collection to avoid any travel costs for participants. Data collectors are recruited from the intervention district but recruited from different villages. Data collectors are not paired with participants and they are not assigned participants from their own villages for data collection, thus reducing the likelihood of study staff having prior acquaintance with the participants. Furthermore, if any study staff had any prior personal acquaintance with a participant, they were replaced with another data collector who was not acquainted with the participant.
Data management
Atmiyata uses a comprehensive data management system that aids in collecting high quality data by maintaining on-going- on-site and off-site quality assurance and quality control checks. Research staff (data collectors) handling data are thoroughly trained in interview techniques and procedures for sensitive data handling. Several measures to control for quality of data collected are implemented, including weekly checks, field monitoring visits twice a month by project managers and spot checks (once a month). Additionally, refresher training sessions are provided once in 4 months for quality assurance purposes. The project manager ensures completeness and legibility of the data prior to data entry and is responsible for storing all the data. Designated data entry person is trained for specific entry guidelines to avoid erroneous data entry. The de-identified data is entered in password protected Excel sheets. Personally identifiable information is not entered in the database. Raw data is not uploaded on internet; instead all entered data is shared with statistician through offline electronic data transfer from the site by the project manager on monthly basis. Statistician collates the data, maintains the database and reviews data quality in terms of numbers, consistency and completeness. Measurement of percentage agreement among the data collectors is obtained once a year, to ensure reliability of the data collected. Several strategies are adopted to achieveadequate participant enrolmentincluding three telephonic follow-up calls to participants not available during in-person visits, two reminders for follow-up visits and rescheduling visits as per participant convenience. Recruitment, follow-up rates and missing data are discussed at monthly team review meetings between project manager and data collectors.
Data storage, security and confidentiality
Study data is anonymized using unique study identification (ID) codes for participants, which is matched to the physical consent form and then entered in the study database. Only the consent form includes personally identifiable details. A code sheet linking participant’s personal identifiable information is linked to the unique study ID code. Data is stored on a password-protected external hard drive periodically as a back-up. All consent forms and data forms are stored in a locked cabinet at the site office in Mehsana, accessible only to the principal investigator (PI) and project manager. After the study is over, the data will be stored in the sealed cabinet as required by Indian regulations.
Data monitoring
An advisory committee consisting of 4 experts in medical ethics, public health administration and public health and social science research was formed to monitor the implementation and research. The Committee meets every 6 months with the research team and also makes periodic site visits to personally interact with a few participants. All adverse events will be reported to the committee.
Statistical analysis
Baseline characteristics will be summarized using counts (percentages) for categorical variables and means (SD) for continuous variables. Analysis will be based on intention to treat and participants will be analyzed in the group that the cluster was assigned to at each time point.
The analysis plan is based on the Hussey and Hughes model for analysis of cross-sectional SW-CRCT designs (15). Generalized Linear Mixed Model (GLMM) will be used to determine the size and direction of the difference between the control and intervention conditions for primary and secondary outcomes. The estimated intervention effect will be reported as the mean outcome difference for continuous variables and Odds Ratio for categorical variables between intervention and control condition assuming a constant treatment effect over time. Estimates of the difference and 95% CIs will be calculated. To take time effect into account, all analysis will be adjusted for time (periods) of the intervention and for clusters. Period (time) and intervention (counseling sessions) will be specified as fixed effects and clusters as random effect. Analysis will be adjusted for baseline covariates to account for potential imbalance arising due to different recruitment procedures and regional differences across control and intervention condition. The analytical plan does not include any interim analyses.
Two broad model extensions (38), random cluster by period effect and random cluster by treatment effect will be used for secondary analysis. The secondary analysis will investigate an interaction effect between intervention and time and interaction effect between cluster and time. Additional analyses of the primary outcome will be conducted controlling for demographic variables if required. Statistical analyses will be carried out using STATA version 14 (35).
Economic evaluation analysis
All data will be analysed in Microsoft excel. The ratio of costs and benefits will be calculated and will be presented as ROI. This will inform whether Atmiyata intervention is a sound investment. Apart from this, the study will also provide information on economic burden of CMD in Mehsana district, which is of value to funders, policy makers and can be used for advocacy purposes.