Using the RE-AIM framework to evaluate the implementation of scaling-up the Friendship Bench in Zimbabwe – a quantitative observational study

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Study Justification:
– This study aimed to evaluate the real-world implementation of the Friendship Bench (FB) program in Zimbabwe, three years after its scale-up.
– It is one of the first evaluations of a scaled-up evidence-based psychological intervention in sub-Saharan Africa.
– The study used the RE-AIM framework to assess the program’s performance in terms of reach, adoption, and implementation.
– The findings can provide valuable insights into the effectiveness of task-shared psychological interventions in sub-Saharan Africa and inform future implementation strategies.
Study Highlights:
– Small clinics achieved higher reach (34%) compared to large (15%) and medium clinics (9%).
– Adoption of the FB program was high in all clinic types, ranging from 59% to 71%.
– Small clinics had the highest implementation score (53%), followed by medium-sized clinics (43%) and large clinics (40%).
– Differences in performance between small and large clinics were significant.
– Ongoing support for delivering agents and buy-in from health authorities were identified as important factors for program activity and data quality.
Study Recommendations:
– Future implementation improvements should focus on increasing reach in larger clinics, as they performed poorly compared to smaller clinics.
– Program data should be integrated into existing health information systems to improve data collection and prioritization.
– Future studies should optimize scale-up and sustainment strategies to maintain effective task-shared psychological interventions in sub-Saharan Africa.
Key Role Players:
– Community health workers (CHWs)
– Health authorities
– District health promoting officers (DHPOs)
– Clinic leads
– Nurses in charge
Cost Items for Planning Recommendations:
– Training and support for CHWs in data collection
– Ongoing support for delivering agents
– Integration of program data into health information systems
– Resources for program activities (benches, questionnaires, notebooks)
– Supervision meetings for CHWs
– Support group meetings for clients
Please note that the cost items provided are general categories and not actual cost estimates.

The strength of evidence for this abstract is 6 out of 10.
The evidence in the abstract is moderately strong. The study used the RE-AIM framework to evaluate the implementation of the Friendship Bench program in Zimbabwe. The authors collected data from 36 primary health care clinics and analyzed indicators related to reach, adoption, and implementation. However, there are limitations in the study, such as the lack of reliable data and the inability to cover all five domains of the RE-AIM framework. To improve the strength of the evidence, the authors should ensure reliable data collection and consider including all domains of the RE-AIM framework in future studies.

Background: This study aimed to evaluate the real-world implementation of the Friendship Bench (FB) – an evidence-based brief psychological intervention delivered by community health workers (CHWs) – three years after its implementation in three city health departments in Zimbabwe. Implementation sites were evaluated according to their current performance using the RE-AIM framework making this one of the first evaluations of a scaled-up evidence-based psychological intervention in sub-Saharan Africa (SSA). Methods: Using the RE-AIM guide (www.re-aim.org), the authors designed quantitative indicators based on existing FB implementation data. Thirty-six primary health care clinics (PHC) in Harare (n=28), Chitungwiza (n=4) and Gweru (n=4) were included. Among these clinics 20 were large comprehensive health care centers, 7 medium (mostly maternal and child healthcare) and 9 small clinics (basic medical care and acting as referral clinic). Existing data from these clinics, added to additionally collected data through interviews and field observations were used to investigate and compare the performance of the FB across clinics. The focus was on the RE-AIM domains of Reach, Adoption, and Implementation. Results: Small clinics achieved 34% reach, compared to large (15%) and medium clinics (9%). Adoption was high in all clinic types, ranging from 59% to 71%. Small clinics led the implementation domain with 53%, followed by medium sized clinics 43% and large clinics 40%. Small clinics performed better in all indicators and differences in performance between small and large clinics were significant. Program activity and data quality depends on ongoing support for delivering agents and buy-in from health authorities. Conclusion: The Friendship Bench program was implemented over three years transitioning from a research-based implementation program to one led locally. The Reach domain showed the largest gap across clinics where larger clinics performed poorly relative to smaller clinics and should be a target for future implementation improvements. Program data needs to be integrated into existing health information systems. Future studies should seek to optimize scale-up and sustainment strategies to maintain effective task-shared psychological interventions in SSA.

The aim of this study was to evaluate the implementation of the FB program three years post scale up using the RE-AIM framework. To gain an overview of the FB activities at the 36 PHCs, we carried out a review of the FB data that should have been routinely collected in a data collection book at each clinic since 2016. However, we found that FB related data since the scale-up exercise started was not reliably available. Upon investigating reasons for the lack of reliable data, several factors became obvious: a) CHWs had not been trained in data collection and responsibilities were unclear; b) data was collected only from those clinics whose CHW supervisors received continual guidance from FB research team members which was only happening in Harare; c) FB data was not integrated in the routine clinic data collection efforts and therefore not prioritized. Since reliable routine FB data was unavailable, we restructured our research approach which required a deviation from our protocol [22]. Instead of drawing from three years of data collection (2016-2019), we decided to collect fresh data in 2019, specifically focusing on the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) indicators described below. We based this decision on the assumption that we capture activity for the month prior to data collection, assuming this reflected the usual or at least minimum level of activity as no efforts had been made to increase the activity levels since the scale up in 2016. Using the RE-AIM guide (www.re-aim.org), we designed quantitative draft indicators based on availability of Friendship Bench implementation data such as PHC clinic user numbers, number of clinic staff, catchment area size, number of CHWs, FB program user number, data pertaining to program usage such as frequency of consultations, FB-related tools such as benches, questionnaires, notebooks, frequency of supervision meetings for CHWs and support group meetings for clients. The research team decided on the final indicator definitions in an iterative process based on our understanding of RE-AIM framework’s definition during a 2-day-long meeting. The team consisted of experienced international and local mental health researchers who have expertise in program development, implementation, and evaluation. Three members of the research team had successfully developed and scaled up evidence-based practices (RA, DC, RV). In total, we created 16 indicators (Table ​(Table1)1) covering three of the five domains (Reach, Adoption, Implementation) which are described below. It was not possible to cover all five domains of the RE-AIM framework due to the lack of reliable data as described above. List of indicators for three domains of RE-AIM model Based on the finalized indicators, a FB specific RE-AIM interview guide was designed with multiple versions for different interview partner groups (see Additional file Table ​Table2)2) to elicit the additional information needed. We planned to confirm all statements made by stakeholders by requesting to be shown notebooks, notes, registries, filled out questionnaires or any other applicable documents. Number and distribution of clinic types in the three cities The following table lists all indicators and descriptive details for the three domains of the RE-AIM model chosen (Table ​(Table11). This study was carried out in 36 PHC clinics in three cities Harare (n=28), Chitungwiza (n=4) and Gweru (n=4). All 36 PHC clinics were part of the FB scale-up process in 2016 in which CHWs were mandated to take the manualized FB training. CHWs are attached to PHC clinics which cater for the needs of communities in areas with high population density (“townships”) characterized by informal income generating activities. Depending on their size, PHC clinics serve between 20,000-80,000 people from the most socio-economically disadvantaged sectors of the population and are defined as large (poly clinics), medium (family health clinics) and small (satellite) clinics [23]. CHWs are present at all clinics and do health promotion at clinic level as well as outreach activities. CHWs are overseen by health managers (district health promoting officers – DHPOs). Clinic size defines how many CHWs (currently between 1-14 CHWs) are attached. The group of CHWs who had prior experience with the FB program through their participation in the FB RCT [6] were assigned a peer-supervisory role in the PHC clinics they were attached to. Not all clinics had such a peer supervisor. Peer supervisors support other CHWs with referral issues, regular debriefing, and data collection. Depending on the size of the clinic, different numbers of wooden benches (Friendship Benches) are placed on the clinic premises. CHWs see clients between Monday and Thursday mornings at the clinic and at other times during the week in the informal setting of the community. Patients waiting for services at the PHC clinic are being sensitized about mental health and the FB program by FB CHWs who are trained as “mobilizers”. These can refer to the CHW on the bench who will administer a locally validated screening tool, the Shona Symptom Questionnaire (SSQ-14) [24]. Clients who score above the cut-off score and/or wish to receive the FB program are given psychoeducation and problem-solving therapy (PST). The intended FB workflow and its steps is described in the patient flow chart (Fig ​(Fig1).1). Clients are encouraged to come back for follow-up sessions for up to 4-6 times. All clients are invited to join a peer-led support group which focuses on income generation activities such as crocheting bags out of recycled plastic or doing community gardening. Group meetings happen weekly on the clinic grounds and are facilitated by the CHWs. Friendship Bench patient flow in a PHC clinic. Authors RV, CC, SM, JT, DC are affiliated with Friendship Bench and therefore have permission to use the company logo We investigated FB activities in 20 large, 7 medium, and 9 small clinics, as shown in Table ​Table22. The study was authorized by the city health authorities who run the PHCs and had received ethics approval from the Medical Research Council Zimbabwe (MRCZ). All 36 clinic leads were informed about purpose and duration of the study and key informant groups [CHWs, CHW supervisors, nurses in charge, and District Health Promotion Officers (DHPO)]. Four trained research assistants collected data between October and November 2019. Two research teams visited first clinics in Harare, then Gweru and Chitungwiza. Two consecutive days were spent at each clinic to conduct all questionnaire-based interviews and each team covered two clinics per week. As each clinic had varying numbers of CHWs and we had time constraints, half of all FB counsellors were selected randomly in their presence and subsequently interviewed. All FB program activities for a period of one month prior to the data collection were investigated and data was entered into KOBOtool (http://support.kobotoolbox.org/) to allow for complete data collection. CHW notes and notes from the supervisor of the CHWs were read to verify the responses given in the interviews. Data was verified on site after collection and then uploaded daily onto a password protected cloud. Only the local research team had access to the data base. To estimate the performance achieved at each clinic, we used descriptive and inferential statistics to analyze the quantitative data. The indicators for each domain were weighted as equivalent. All indicators were rated using a binary scale (0=not present or 1=present), except for the two indicators for Reach that were assigned % values. Indicator scores represented the level of performance, mean results per clinic group are presented. Additionally, individual indicator scores were summed, and each clinic received a total summary score for each domain which was ranked according to a procedure suggested by Farris et al. [25]. The higher the score or % value per clinic, the further up on the ranking a clinic was, which means the better the performance in that domain. Within each indicator and domain, there were cases where several clinics had the same combined domain rank and, therefore, ended up with the same rank. The mean of all three domain ranks per clinic formed a composite ranking which represented the overall level of FB site performance (see Additional file Table ​Table1).1). We ranked all clinics again based on this total score with the assumption that a lower score means a higher rank. Inter-Item correlations of domains were calculated. Considering that the data was collected from all clinics participating in this study and that there was homogeneity of variance across the clinics, an analysis of variance (ANOVA) was used to determine any significant differences among the clinics’ scores and differences according to type of clinic. Additionally, a Tukey post hoc test was used to confirm the differences between clinics individually and when aggregated as type groups. To establish whether clinic types had an influence on the performance of a FB site, we aggregated the clinics according to their types (large, medium sized, small) and compared their performance using their overall composite ranking (mean of all 3 ranks).

Based on the information provided, it appears that the study is focused on evaluating the implementation of the Friendship Bench (FB) program in Zimbabwe, specifically in relation to maternal health. The study uses the RE-AIM framework to assess the program’s reach, adoption, and implementation in different primary health care clinics.

In terms of potential innovations to improve access to maternal health, based on the information provided, here are a few recommendations:

1. Integration of FB data into routine clinic data collection efforts: The study highlights that FB data was not integrated into the routine clinic data collection, which affected the availability and reliability of data. An innovation could be to develop a system or technology that seamlessly integrates FB data into existing health information systems. This would ensure that data on maternal health and the FB program is consistently collected and readily available for analysis and decision-making.

2. Training CHWs in data collection and responsibilities: The study identified that CHWs had not been trained in data collection and responsibilities were unclear. An innovation could be to develop training programs or tools specifically focused on data collection for CHWs. This would empower CHWs to effectively collect and manage data related to maternal health and the FB program, contributing to improved monitoring and evaluation.

3. Leveraging technology for data collection and monitoring: The study mentions the use of KOBOtool for data collection. Expanding on this, an innovation could be to explore the use of mobile health (mHealth) technologies or digital platforms for data collection and monitoring. This could involve developing mobile applications or web-based platforms that enable CHWs to easily collect and report data on maternal health indicators, FB program activities, and client outcomes. This would streamline data collection processes and provide real-time access to information for program management and decision-making.

4. Strengthening support for delivering agents and buy-in from health authorities: The study highlights the importance of ongoing support for delivering agents (CHWs) and buy-in from health authorities for program activity and data quality. An innovation could involve developing strategies to enhance support for CHWs, such as regular supervision and mentoring, training opportunities, and incentives. Additionally, efforts could be made to engage and collaborate with health authorities to ensure their active involvement and support for the FB program and maternal health initiatives.

These are just a few potential innovations that could be considered to improve access to maternal health based on the information provided. It’s important to note that further research and evaluation would be needed to assess the feasibility, effectiveness, and sustainability of these innovations in the specific context of Zimbabwe and the FB program.
AI Innovations Description
The study described aims to evaluate the implementation of the Friendship Bench (FB) program in Zimbabwe, specifically focusing on the RE-AIM framework. The RE-AIM framework is a tool used to assess the reach, effectiveness, adoption, implementation, and maintenance of an intervention.

The study found that there were challenges in collecting reliable data for the FB program, which impacted the evaluation. Factors contributing to the lack of reliable data included inadequate training of community health workers (CHWs) in data collection, limited guidance from the FB research team, and a lack of integration of FB data into routine clinic data collection efforts.

To overcome these challenges, the research team decided to collect fresh data in 2019, focusing on indicators related to reach, adoption, and implementation. These indicators included clinic user numbers, number of clinic staff, catchment area size, number of CHWs, FB program user numbers, frequency of consultations, and availability of FB-related tools.

The study evaluated 36 primary health care clinics in three cities in Zimbabwe. The findings showed that small clinics had higher reach, adoption, and implementation scores compared to large and medium-sized clinics. This suggests that smaller clinics performed better in implementing the FB program.

The study highlights the importance of ongoing support for CHWs and buy-in from health authorities to ensure program activity and data quality. It also emphasizes the need to integrate program data into existing health information systems.

Based on the findings, recommendations for improving access to maternal health through innovation could include:

1. Strengthening training and support for CHWs: Provide comprehensive training for CHWs on data collection and their responsibilities. Ensure ongoing support and guidance from the research team to improve data quality and program implementation.

2. Integration of program data: Develop mechanisms to integrate FB program data into routine clinic data collection efforts. This will help prioritize the collection and analysis of program data, leading to better monitoring and evaluation of maternal health outcomes.

3. Scaling up successful strategies: Learn from the performance of small clinics and identify strategies that have contributed to their success in implementing the FB program. These strategies can be scaled up and replicated in larger clinics to improve access to maternal health services.

4. Collaboration with health authorities: Foster collaboration and buy-in from health authorities to ensure the sustainability and scale-up of the FB program. Engage health authorities in decision-making processes and involve them in the implementation and evaluation of maternal health interventions.

By implementing these recommendations, it is possible to develop innovations that improve access to maternal health, based on the findings and lessons learned from the evaluation of the FB program using the RE-AIM framework.
AI Innovations Methodology
Based on the provided description, the study aims to evaluate the implementation of the Friendship Bench (FB) program in Zimbabwe using the RE-AIM framework. The FB program is an evidence-based brief psychological intervention delivered by community health workers (CHWs) to improve access to maternal health.

To simulate the impact of recommendations on improving access to maternal health, a methodology can be developed using the following steps:

1. Identify the recommendations: Based on the study findings and existing literature, identify potential recommendations that can improve access to maternal health. These recommendations can include strategies to enhance reach, adoption, and implementation of the FB program.

2. Define indicators: Develop quantitative indicators that can measure the impact of the recommendations on improving access to maternal health. These indicators should align with the RE-AIM framework and focus on the domains of Reach, Adoption, and Implementation.

3. Collect data: Collect data on the identified indicators from the primary health care clinics (PHCs) involved in the FB program. This data can include clinic user numbers, number of clinic staff, catchment area size, number of CHWs, program usage data, and other relevant information.

4. Analyze data: Analyze the collected data using descriptive and inferential statistics. Calculate indicator scores and composite rankings to assess the performance of the FB program in improving access to maternal health. Conduct an analysis of variance (ANOVA) to determine significant differences among clinic scores and types.

5. Compare performance: Compare the performance of different clinic types (large, medium, small) to evaluate the influence of clinic size on the FB program’s effectiveness. Use post hoc tests, such as the Tukey test, to confirm differences between clinics individually and when aggregated as type groups.

6. Assess impact: Based on the analysis of the data, assess the impact of the recommendations on improving access to maternal health. Identify areas of improvement and prioritize strategies to optimize the scale-up and sustainment of the FB program.

7. Make recommendations: Based on the findings, make recommendations for further implementation improvements. These recommendations should focus on addressing the identified gaps and challenges in reaching, adopting, and implementing the FB program to improve access to maternal health.

By following this methodology, researchers can simulate the impact of recommendations on improving access to maternal health and provide evidence-based strategies for scaling up and sustaining effective maternal health interventions like the FB program.

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