Twelve-month Outcomes of a Mental Illness Destigmatizing Theatrical Intervention in Rural Uganda

Twelve-month Outcomes of a Mental Illness Destigmatizing Theatrical Intervention in Rural Uganda | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Twelve-month Outcomes of a Mental Illness Destigmatizing Theatrical Intervention in Rural Uganda Yang Jae Lee, Ryan Christ, Scott Blackwell, Kazungu Rauben, Alyssa Krause, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2743636/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose Evaluate the long-term effectiveness of a community-led theatrical intervention in reducing mental health stigma in a low-income setting in Uganda. Methods A follow-up survey of study participants was conducted 12 months after the initial community-led theatrical intervention measuring the primary outcomes of mental illness stigma using the Broad Acceptance Scale (BAS) and the Personal Acceptance Scale (PAS). Results Of the initial 57 participants, 46 (80%) completed the follow-up survey. The average improvement in Broad Acceptance Scale and Personal Acceptance Score observed from baseline to twelve months after the intervention was 1.435 (95% CI: 0.826–2.044, p < 0.0001, SD: 1.64) and 2.152 (95% CI: 1.444–2.860, p < 0.0001, SD: 1.93), respectively. Both effect sizes were within the confidence intervals of the average improvement observed one week after the intervention. Conclusion Exposure to the community-led theatrical intervention continued to confer a significant and substantial reduction in mental illness stigma. Global mental health stigma psychosis mental illness art-based interventions Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Mental illnesses are the leading cause of disability in the world [ 3 ]. The burden of mental illness is especially high in low- and middle-income countries (LMICs), where there is a limited supply of providers [ 4 ] and multiple barriers to care. Prominent among these barriers is stigma, a complex of negative cultural attitudes towards and beliefs about people who experience mental illness, which can lead to impaired self-esteem, social ostracism, shame, and reluctance to seek treatment [ 5 ]. Uganda, like many nations within East Africa, has seen a significant increase in population over the last few decades, from 36 million to 45 million people since 2014 [ 6 ]. It is estimated that up to 35 percent of the Ugandan population suffers from at least one mental illness, resulting in a critical need for increased use of effective psychiatric services throughout the country [ 7 ]. This issue is exacerbated by the country’s lack of trained healthcare professionals as there are only 0.78 psychiatric nurses per 100,000 individuals, primarily concentrated in the country’s one psychiatric hospital, Butabika National Referral Mental Hospital located in the capital, Kampala [ 7 ]. As a result, rural areas of Uganda are disproportionately affected by this treatment gap, due to long travel distances, high levels of poverty, and stigma around mental illness [ 7 ]. The strongest predictor of an individual’s ability to recover from a mental illness is the presence of a robust support system [ 8 ]. In LMICs, like Uganda, most individuals derive this support from their local community [ 9 ]. However, misunderstandings about mental illness and prejudice against afflicted individuals result in personal, public, and structural stigma, all of which can erode community supports [ 10 ]. A lack of health education, which is especially common in lower-income and rural populations, further exacerbates the stigmatization of people with mental illnesses [ 10 ]. Thus, mental illness destigmatization education is vital to reduce the burden of stigma towards those with mental illness and increasing access to care. Educational interventions have been shown to successfully reduce mental health stigma [ 11 ]. While a variety of educational approaches have been designed and tested, approaches to educational interventions using creative arts have been less studied than more didactic approaches [ 12 ]. Lee et al. in 2022 developed and evaluated the effectiveness of a community-led theatrical performance in the rural Busoga region of eastern Uganda, depicting an individual’s progression from intense, debilitating mental illness to establishing care opportunities at a health center, receiving individualized treatment, attaining gainful employment, and achieving reintegration into society [ 13 ]. Participants exposed to this intervention showed a significant and sizable reduction in mental health stigma from baseline to a one-week follow-up assessment. This is the first study, to our knowledge, to demonstrate the effectiveness of an arts intervention in reducing mental health stigma among the general population of a rural region of a low-income country. This study aims to extend the findings of Lee et al., in an evaluation of the long-term effectiveness of this community-led theatrical intervention in reducing mental health stigma by reporting the results of a one-year follow-up survey of the initial study participants. A detailed description of the community-led theater intervention, participant selection, and immediate post-intervention results have been reported previously by Lee et al. (2022) [ 13 ]. Methods The study was conducted in the Busoga region of rural Eastern Uganda, specifically in Buyende District (Fig. 1), which consists of sixty-eight parishes and is home to an estimated 450,100 people [ 14 ]. Participants were chosen after all villages in five parishes (Bukutula, Kabukye, Kagulu, Kirimwa, and Igalaza) were assigned a number, and residents of ten villages were randomly selected through a random number generator. At each involved village, ten households were identified through assigning each household in the village with a number and selecting subjects through a random number generator. At each selected household, researchers obtained a list of every household member aged 18 years or older, and each individual was assigned a number and one was randomly selected. If no household members were home or met the inclusion criteria, a different household was randomly selected. This process was iterated until ten participants were recruited from each village. Through this process, 101 participants were enrolled in the study. Figure 1 Regions of Uganda, with Buyende District within the Eastern Region (Map from World Atlas [ 2 ]) Figure 2 Buyende District Parishes which held theater interventions (Map data ©2022 GoogleMaps [ 1 ] ) INTERVENTION: THEATER PLAY DESIGN AND PERFORMANCE Message design theory underpinned by an audience-channel-message-evaluation (ACME) framework was used to design the original theater intervention [ 15 ]. The ACME framework organizes the principles of an effective health education campaign into four major categories: audience, channel, message, and evaluation. In translating this theory into practice, the target audience’s attitudes and stigma towards mental illness was measured, and that information was utilized to develop and implement a community-led theater performance in collaboration with community health workers. Theater was used because it is a common channel of media in the region [ 16 ]. The message depicted a protagonist and a storyline that are relatable to the audience, and was grounded in translating social cognitive theory into practice [ 17 ]. Qualitative data was collected through four focus groups to identify common misconceptions and specific points of stigma related to mental health. Based on the responses from the focus groups, local community health workers developed a culturally appropriate theatrical performance that addressed these points of stigma and encouraged seeking care. This play was then performed in July 2021 in the villages where the 101 participants who completed the structured questionnaire resided, and the participants were encouraged to attend the performance although no financial compensation was offered. QUESTIONNAIRE DESIGN AND ADMINISTRATION Outcomes were assessed with a 61-item questionnaire that gathered demographic data and included two stigma-focused batteries, the Personal Acceptance Scale (PAS) and the Broad Acceptance Scale (BAS), described in Lee et al [ 13 ]. The PAS targets population stigma, and consists of community-influenced negative attitudes, beliefs, and behaviors towards people with mentally illness. The BAS targets structural and institutional stigma, such as the cultural norms and institutional practices likely to limit the resources, opportunities, and well-being of individuals with mental illness. The questionnaire was administered to all 101 participants within two weeks before the play performances (baseline). All participants were contacted for a follow-up interview, and 57 of the original participants were re-surveyed one week after the intervention with the BAS and PAS in August 2021 to measure changes in stigma towards mental illness. Those that were unable to be resurveyed either could either not be located or did not participate in the intervention. During the summer of 2022, 46 of the 57 participants that were re-surveyed after the intervention were re-interviewed to measure the permanence of attitude changes towards mental illness stigma. INCLUSION CRITERIA All individuals who participated in the 2022 theater intervention who are over 18 years old and able to provide informed consent were eligible for the study. EXCLUSION CRITERIA Individuals who did not participate in the 2022 theater intervention or who are under the age of 18 or could not give informed consent to participate in this study were excluded. Individuals who could not be reached or who did not consent to participate were excluded. PARTICIPANT INFORMATION The follow-up cohort consisted of nine males and thirty-seven females (Total N = 46); the mean age of the cohort was 40.0 years. Thirty-nine participants were of Christian denominations (Catholic, Anglican, Pentecostal, Seventh Day Adventist, and Born-Again Churches) with the remaining seven individuals being Muslim. Thirty-one participants did not complete primary school or never attended primary school, fourteen completed primary school, and one individual completed some years of secondary school. STATISTICAL METHOD For both the BAS and PAS, the average difference between each pair of time points was tested using a paired t-test. Results The marginal distribution of BAS scores observed at each time point is shown in Fig. 3 ; the marginal distribution of PAS scores, Fig. 4 . The average improvement in BAS at baseline observed at time point two (one-year follow-up) was 1.435 (95% CI: 0.826–2.044, p < 0.0001, SD: 1.64). This estimated effect was almost as strong as and within the confidence interval of the average improvement estimated at time point one, one week after the intervention, 1.609 (95% CI: .994–2.224, p < 0.0001). The average improvement in PAS at baseline observed at time point two was 2.152 (95% CI: 1.444–2.860, p < 0.0001, SD: 1.93). This estimated effect is higher than but within the confidence interval of the average improvement estimated at time point one, 1.804 (95% CI: 1.134–2.475, p < 0.0001). Discussion Statement of Principal Findings: This study aimed to assess the persistence of stigma reduction among rural Ugandans one year after viewing the initial theater intervention. The results suggest that the effects on participants’ attitudes towards individuals with mental illness were sustained significantly over one year with magnitude of the reduction of stigma at around one standard deviation. Both the initial post-intervention and one-year follow-up surveys showed substantially greater effect sizes when compared to similar studies that have attempted to quantify and reduce mental health-related stigma at the community level in LMICs [ 18 , 19 ]. These results suggest that community-led, theatrical interventions may be an effective tool for inducing long-term, persistent reductions in mental illness-associated stigma among rural populations of low-income countries. Strengths and Weaknesses of the Study: The effectiveness of the intervention likely derives from its theoretical audience-channel-message-evaluation (ACME) framework[ 15 ] and its community-based approach, in which community health volunteers devised and performed a play that harmonized existing cultural ideas around the topic with new beliefs and knowledge about mental illness [ 13 ]. The intervention was therefore created by individuals with similar cultural perspectives as the target audience. The actors also utilized a variety of strategies to effectively engage their audience that included traditional music, props, and humor. The message depicted a protagonist and a storyline that are relatable to the audience[ 17 ]. Additionally, theater is a common channel of media in the region[ 16 ] likely contributing to its acceptance and success. This community-centered approach also likely contributed to the relatively low attrition rate (19.2%) from 57 participants in the one-week follow-up to this study’s twelve-month follow-up cohort (n = 46). Community health volunteers are well-respected community members with substantial knowledge about other individuals in their respective villages and are a key component of the health infrastructure in Uganda as well as other countries in Sub-Saharan Africa [ 20 ]. A limitation of the study was its small sample size, which could limit the generalizability of the results. Additionally, a control group was not used in the initial study, so it is possible that various confounds such as selection biases could have contributed to the changes in mental health stigma in this particular group. Although the drop-out rate was relatively low between one week and twelve months after the intervention, it is possible that some participants could not be located or refused to consent for a non-random reason. However, demographic data comparing the entire intervention cohort and the follow-up cohort did not reveal statistically significant differences (Table 2 ), suggesting that the two cohorts were comparable and representative of the target population. The drop-out rate could potentially have been improved if the initial post-intervention cohort was informed that a follow-up study would be conducted after one year. Additionally, cash compensation for participating in the interviews could have helped with the retention. Another limitation was the use of self-reported measures of stigma, which may be subject to social desirability bias. Such bias has been shown to play a role in stigma around drug use [ 21 ], but to the authors’ knowledge the role of this bias on mental health attitudes in particular and stigma in general have not been substantially studied. Finally, the study was limited to rural areas in the Busoga Region of Uganda, and although there are significant similarities between our study population and other rural populations in Sub-Saharan Africa, it is unclear whether similar effects of similar interventions would be found in other contexts or populations that may have different cultural practices, beliefs, and stigmas around mental illness. Table 2 Differences between cohorts interviewed at twelve months and the remaining Reinterviewed at twelve months (N = 46) not reinterviewed at twelve months (N = 55) Overall (N = 101) P-value Sex 0.0856 Female 37 (80.4%) 33 (60.0%) 70 (69.3%) Male 9 (19.6%) 22 (40.0%) 31 (30.7%) Age 0.973 Mean (SD) 40.5 (16.2) 40.0 (17.0) 40.2 (16.6) Median [Min, Max] 36.0 [18.0, 80.0] 35.0 [18.0, 86.0] 35.0 [18.0, 86.0] Marital Status 0.833 Married or Cohabiting 35 (76.1%) 44 (80.0%) 79 (78.2%) Separated (married but not cohabiting) 1 (2.2%) 3 (5.5%) 4 (4.0%) Single & Never Married 5 (10.9%) 3 (5.5%) 8 (7.9%) Widowed 5 (10.9%) 3 (5.5%) 8 (7.9%) Single 0 (0%) 2 (3.6%) 2 (2.0%) Religion 0.388 Anglican 17 (37.0%) 13 (23.6%) 30 (29.7%) Born Again 1 (2.2%) 1 (1.8%) 2 (2.0%) Catholic 5 (10.9%) 16 (29.1%) 21 (20.8%) Muslim 7 (15.2%) 15 (27.3%) 22 (21.8%) Pentecostal 15 (32.6%) 7 (12.7%) 22 (21.8%) Seventh Day Adventist 1 (2.2%) 2 (3.6%) 3 (3.0%) Isa Masia 0 (0%) 1 (1.8%) 1 (1.0%) Occupation 0.998 Brewer 1 (2.2%) 0 (0%) 1 (1.0%) Hairdresser 1 (2.2%) 0 (0%) 1 (1.0%) Peasant Farmer 39 (84.8%) 47 (85.5%) 86 (85.1%) Produce Seller 1 (2.2%) 0 (0%) 1 (1.0%) Shop Owner 1 (2.2%) 1 (1.8%) 2 (2.0%) Student 1 (2.2%) 1 (1.8%) 2 (2.0%) Tailor 1 (2.2%) 1 (1.8%) 2 (2.0%) Un-employed 1 (2.2%) 2 (3.6%) 3 (3.0%) Mechanic 0 (0%) 1 (1.8%) 1 (1.0%) Pancake Seller 0 (0%) 1 (1.8%) 1 (1.0%) Retired Peasant Farmer 0 (0%) 1 (1.8%) 1 (1.0%) Education 0.905 Complete Primary 13 (28.3%) 16 (29.1%) 29 (28.7%) Incomplete Primary 21 (45.7%) 25 (45.5%) 46 (45.5%) Incomplete Secondary 1 (2.2%) 0 (0%) 1 (1.0%) Never Attended 10 (21.7%) 8 (14.5%) 18 (17.8%) O-Level 1 (2.2%) 5 (9.1%) 6 (5.9%) Nursery School 0 (0%) 1 (1.8%) 1 (1.0%) Village 0.56 Bulayi 5 (10.9%) 5 (9.1%) 10 (9.9%) Bulondo 8 (17.4%) 2 (3.6%) 10 (9.9%) Bunangwe 6 (13.0%) 4 (7.3%) 10 (9.9%) Busuyi 5 (10.9%) 5 (9.1%) 10 (9.9%) Gabano 3 (6.5%) 2 (3.6%) 5 (5.0%) Gabona 3 (6.5%) 2 (3.6%) 5 (5.0%) Kinamagira 3 (6.5%) 8 (14.5%) 11 (10.9%) Kinatebe 2 (4.3%) 8 (14.5%) 10 (9.9%) Masaba 2 (4.3%) 8 (14.5%) 10 (9.9%) Nadiyope 2 (4.3%) 8 (14.5%) 10 (9.9%) Ngereka 7 (15.2%) 3 (5.5%) 10 (9.9%) Household Size 0.381 Mean (SD) 3.48 (2.23) 2.87 (1.58) 3.15 (1.92) Median [Min, Max] 3.00 [1.00, 12.0] 2.00 [1.00, 9.00] 2.00 [1.00, 12.00] Broad Acceptance Scale 0.847 Mean (SD) 4.37 (1.64) 4.49 (1.44) 4.44 (1.53) Median [Min, Max] 4.00 [1.00, 8.00] 4.00 [2.00, 9.00] 4.00 [1.00, 9.00] Personal Acceptance Scale 0.746 Mean (SD) 2.80 (1.73) 2.64 (2.01) 2.71 (1.88) Median [Min, Max] 3.00 [0, 7.00] 2.00 [0, 8.00] 3.00 [0, 8.00] Strengths and Weaknesses in Relation to Other Studies: To our knowledge, this was the first long-term follow-up study attempting to quantify the persistence of mental illness stigma after a community-led theater intervention among rural populations in a low-income country. De-stigmatization interventions remain an understudied topic in low-income countries. A meta-analysis investigating interventional stigma reduction studies in LMICs identified notable literature gaps in research on this topic, such as generally poor quality of outcome reporting and a small number of studies overall that have collected empirical data and reported at least one outcome [ 22 , 23 ]. Of the studies that seek to counter stigma and discrimination, most research has focused on short-term outcomes and has been conducted in high-income settings [ 18 ]. In low-income countries, it has been suggested that targeted community interventions are more effective than top-down educational campaigns [ 10 ], a claim that is further supported by our study. As reported previously, most interventions have targeted healthcare workers, rather than community members [ 24 , 25 ]. Further, a systematic review of mental health stigma reduction interventions in low- and middle-income countries found that only a small minority were developed by local residents or culturally adapted [ 26 ]. This study did not evaluate the relative effectiveness of different intervention types; therefore, it is possible that an intervention that was structured differently could have been more effective at reducing long-term stigma. Additionally, this study did not investigate the attitudes of community health workers towards mental illness after one year, although in the original study there was some qualitative evidence suggesting that community health workers may harbor their own stigmas towards individuals with mental illness. If this were the case, community-wide stigma would likely be significantly affected since community health workers are typically influential and sources of health-related information in their local communities. This study also focused on an intervention addressing mental health conditions that are most outwardly apparent to the community and most debilitating for the individual, i.e. schizophrenia and bipolar mania. It is unclear whether the same conclusions could be extrapolated to less apparent forms of mental illness, such as depression, anxiety, or substance abuse. More research into different types of community interventions addressing a variety of stigmatized conditions could help identify the optimal approach to address mental health stigma, as this remains a major barrier for afflicted individuals to seek treatment [ 27 ]. Meaning of the Study: Evidence-based interventions are of critical importance to governments and non-governmental organizations as they seek to allocate funds to address these health problems. This study suggests that locally adapted, community-based, creative media interventions can be an effective, affordable, and scalable strategy to create meaningful, long-term reductions in mental illness stigma among rural populations in Sub-Saharan Africa. Reduction of stigma at around one standard deviation is greater than any other interventions that we have found reported to decrease mental illness stigma [ 18 ] [ 19 ]. There are a variety of factors that could account for the success of this intervention. The performance script was both created and acted out by community health workers, which could have increased its credibility and acceptance among the villagers. Their involvement was also meant to ensure that the message was culturally sensitive, locally relevant, and engaging to the audience. Our results could also be attributed to the relatively limited access to mass media in the village communities we studied, thus the novelty of free theatrical performance may have attracted a larger audience and increased engagement with the educational content it conveyed. Furthermore, such limited access to media may have made the performance more memorable, potentially accounting for the lasting impact data we found. As a medium, theater allows for the depiction of real-life scenarios and challenges that an individual with mental illness faces in society, which can increase empathy and understanding among audience members. Encountering and grappling with the topic in this way could have been perceived by participants as more accessible and relatable than other interventional approaches. The report on the original study suggested that the intervention cohort demonstrated a greater willingness to live, work, interact, and understand those with mental illness [ 13 ]. This follow-up study demonstrated that these attitude shifts persist for at least one year and may even become more pronounced after a substantial period of time, suggesting that this model could be used to enact significant, long-term change in attitudes amongst rural Ugandans. Current literature suggests that interventional stigma reduction approaches can often fail to demonstrate lasting effects, so it is especially notable that these effects persisted in this one-year follow-up [ 28 ]. It is also worth noting that, while not statistically significant, the PAS effect size was larger in the year follow-up study (2.152, CI = 1.444–2.860) than it was among the initial post-intervention cohort (1.804, CI = 1.134–2.475). While this result could be due to random chance, it is also possible that a greater sample size would have demonstrated statistical significance. If this were the case, one potential explanation could be that the theater intervention acted as an impetus for critical reflection and attitude shifting on an individual level. It could also be the result of an increase in the number of conversations occurring among community members around this topic, as suggested qualitatively from focus group responses in the original Lee et al. study [ 13 ]. The broader implications of this study are significant, as reducing personal and community-wide stigma is a critical step in improving access to care and overall health outcomes for the mentally ill. Given the high burden of mental illness in many low- and middle-income countries, the use of community-led arts interventions to reduce stigma may be an important strategy for improving mental health outcomes in these settings [ 27 ]. Future Directions: Future directions for this study should include an exploration of the efficacy of similar mental illness de-stigmatization interventions on a larger scale, such as through radio broadcasts or other forms of mass media that have high engagement in low-income, rural settings. This would allow the intervention to reach a wider audience and potentially have a greater impact on reducing stigma at the community level. Additionally, it would be valuable to assess the sustainability of the effects of the intervention over a longer period, such as three or five years. This would provide further insight into the persistence of changes in attitudes and beliefs towards mental illness. Another area for future research could be to evaluate the feasibility and impact of incorporating the intervention into routine healthcare services, such as mental health clinics and outreach campaigns. This would ensure that the intervention reaches those who may be most in need of support and can be delivered in a sustainable and cost-effective manner. Furthermore, it would be prudent to explore the generalizability of this intervention model in regard to other aspects of mental health, such as stigma towards more insidious forms of mental illness, care-seeking behavior, knowledge of mental health maintenance and self-care, and the reduction of harmful coping mechanisms such as substance abuse. Given the significant effect size demonstrated both in the original study and this follow-up, it would be valuable to explore the efficacy of this model in other cultural and linguistic contexts. Mental illness stigma is a complex and multifaceted issue, and it is plausible that the effect sizes of similar interventions could vary depending on cultural perspectives and linguistic idiosyncrasies of the unique population being studied. By examining the impact of the intervention in different contexts, we could gain a better understanding of how to adapt the intervention to maximize its effectiveness. In conclusion, this study provides promising evidence for the effectiveness of a community-led mental illness de-stigmatization theater intervention in reducing stigma towards mental illness in rural Uganda. It is our hope that the model presented in this manuscript can be further refined, tested, and implemented at scale to improve mental health outcomes among vulnerable global populations. Declarations Competing Interests Co-authors Yang Jae Lee, Scott Blackwell, Kazungu Rauben, Scott Blackwell, and Emery Monnig are either Directors or Affiliates in the 501©3 organization Empower Through Health, which funded and supported this study. There are no other competing interests for any other authors. Ethics Approval: Before all surveys, a research assistant read a consent form describing the aim and potential risks of the study, and all participants gave verbal and written informed consent. All methods were carried out in accordance with relevant guidelines and regulations. This project was approved by the Institutional Review Board of The AIDS Support Organization, Uganda and Uganda National Council of Science and Technology. Names of participants were removed from the dataset to ensure anonymity, and participants were assigned an identifying number. Institutional Review Board - The AIDS Support Organization, Uganda: #TASOREC/048/2021-UG-REC-009. Uganda National Council of Science and Technology registration number: HS1764ES. References Maps G: Geography of Uganda . In . ; 2022. WorldAtlas: Regions of Uganda Map . In . ; 2021: https://www.worldatlas.com/maps/uganda. Vigo D, Thornicroft G, Atun R: Estimating the true global burden of mental illness . 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Am J Public Health 2013, 103 (5):777-780. Morgan AJ, Reavley NJ, Ross A, Too LS, Jorm AF: Interventions to reduce stigma towards people with severe mental illness: Systematic review and meta-analysis . J Psychiatr Res 2018, 103 :120-133. Table 1 Table 1 is available in Supplementary Files section. Additional Declarations Competing interest reported. Co-authors Yang Jae Lee, Scott Blackwell, Kazungu Rauben, Scott Blackwell, and Emery Monnig are either Directors or Affiliates in the 501©3 organization Empower Through Health, which funded and supported this study. There are no other competing interests for any other authors. Supplementary Files Table1.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2743636","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":187594880,"identity":"64485f62-6dc6-48d4-b9a3-5687d56b3181","order_by":0,"name":"Yang Jae Lee","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIie2OsUrDUBSG/xo4WY51PUFofIRIIGQoPosi3Cm4FFxaMFDI2DfwIbp0LgSuS0vXQJe6OQSsCMGpekOdbzMK3g/u5fxwPs4POBx/FTGvD/R2QNrmqJtCgBcdxy4KjgpJJyV6WZdv6WQI8qd6zBMZwJ8uxKqsHlQqWoFYqy1ricH60a4ssyQSKk2rLNkyyV1uBruyqY1y+AaF782ID/KUh/UJpcriXVAszRUm77yQWwjblaCqEwSzeyZWcfA8k+uC1Si1Kf1NFn9KczO48MvXfd0MQzPMK5tyZSpdmh7chrP2J9t6S5jD+9j/ht7XqXWHw+H4l/wAX8Q/hiLKKJwAAAAASUVORK5CYII=","orcid":"","institution":"Yale University","correspondingAuthor":true,"prefix":"","firstName":"Yang","middleName":"Jae","lastName":"Lee","suffix":""},{"id":187594882,"identity":"041e9eca-c8f5-41e0-8c61-990f7d21bfc8","order_by":1,"name":"Ryan Christ","email":"","orcid":"","institution":"Yale University","correspondingAuthor":false,"prefix":"","firstName":"Ryan","middleName":"","lastName":"Christ","suffix":""},{"id":187594883,"identity":"e1c8d3ec-fc2b-4639-8e52-bbbfbdc70881","order_by":2,"name":"Scott Blackwell","email":"","orcid":"","institution":"The University of Tennesse Health Sciences Center","correspondingAuthor":false,"prefix":"","firstName":"Scott","middleName":"","lastName":"Blackwell","suffix":""},{"id":187594884,"identity":"cf41c975-b298-4fde-8038-165ca690bcff","order_by":3,"name":"Kazungu Rauben","email":"","orcid":"","institution":"Empowerment to Heal – Uganda","correspondingAuthor":false,"prefix":"","firstName":"Kazungu","middleName":"","lastName":"Rauben","suffix":""},{"id":187594885,"identity":"ca40d4e1-feda-4143-8598-ab255fadc38b","order_by":4,"name":"Alyssa Krause","email":"","orcid":"","institution":"The Ohio State University","correspondingAuthor":false,"prefix":"","firstName":"Alyssa","middleName":"","lastName":"Krause","suffix":""},{"id":187594886,"identity":"35643bba-d0c4-4a5f-8a01-0d0cd293aadf","order_by":5,"name":"Emery Monnig","email":"","orcid":"","institution":"Empowerment to Heal – Uganda","correspondingAuthor":false,"prefix":"","firstName":"Emery","middleName":"","lastName":"Monnig","suffix":""},{"id":187594887,"identity":"78bcc0d2-5d49-497d-ad2d-64792b95fbf7","order_by":6,"name":"Ibrahim Ssekalo","email":"","orcid":"","institution":"University of Bern","correspondingAuthor":false,"prefix":"","firstName":"Ibrahim","middleName":"","lastName":"Ssekalo","suffix":""},{"id":187594888,"identity":"b9dedb15-94d4-4f15-83c9-faf3df18fbda","order_by":7,"name":"Theddeus Iheanacho","email":"","orcid":"","institution":"Yale University","correspondingAuthor":false,"prefix":"","firstName":"Theddeus","middleName":"","lastName":"Iheanacho","suffix":""},{"id":187594889,"identity":"03170ca9-d84a-42ba-acd3-78207dc38c97","order_by":8,"name":"Robert Rosenheck","email":"","orcid":"","institution":"Yale University","correspondingAuthor":false,"prefix":"","firstName":"Robert","middleName":"","lastName":"Rosenheck","suffix":""}],"badges":[],"createdAt":"2023-03-27 18:59:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2743636/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2743636/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":35107564,"identity":"8d545904-cdc1-4104-8c3b-fd00a86e0f99","added_by":"auto","created_at":"2023-03-31 14:54:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":260969,"visible":true,"origin":"","legend":"\u003cp\u003eRegions of Uganda, with Buyende District within the Eastern Region (Map from World Atlas [2])\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-2743636/v1/c1f05eff089fb12175760a40.png"},{"id":35107029,"identity":"7aef11cf-a952-4675-8225-9e206c6ec3d8","added_by":"auto","created_at":"2023-03-31 14:46:25","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":161428,"visible":true,"origin":"","legend":"\u003cp\u003eBuyende District Parishes which held theater interventions (Map data ©2022 GoogleMaps [1] )\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-2743636/v1/859efce2cbe3b43becd8f1a6.png"},{"id":35107026,"identity":"fb869cd2-8b5d-43a0-9bd6-35d5514e0890","added_by":"auto","created_at":"2023-03-31 14:46:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":18416,"visible":true,"origin":"","legend":"\u003cp\u003eBroad Acceptance Scale before intervention, after intervention, and one-year post intervention (n=46). The scale ranges from 0 (lowest acceptance) to 10 (highest acceptance)\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-2743636/v1/497012f76298bb78bed2cc5a.png"},{"id":35107563,"identity":"6979abc3-192e-4b60-9032-5c2430b3bf30","added_by":"auto","created_at":"2023-03-31 14:54:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":15823,"visible":true,"origin":"","legend":"\u003cp\u003ePersonal Acceptance Scale before intervention, after intervention, and one-year post intervention (n=46). The scale ranges from 0 (lowest acceptance) to 10 (highest acceptance)\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-2743636/v1/0b23c981dab348fe797126bd.png"},{"id":35877373,"identity":"ba3f95eb-922f-4f30-9df5-b09dd7363bcc","added_by":"auto","created_at":"2023-04-17 14:29:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1272302,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2743636/v1/0dd66b50-0af3-4b2c-be3d-9ee7135ff5de.pdf"},{"id":35107025,"identity":"3e3639a1-67b5-4ef9-a452-4b950aca45c4","added_by":"auto","created_at":"2023-03-31 14:46:25","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":30681,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-2743636/v1/ea52ad683b4ddb34d6f75cc1.docx"}],"financialInterests":"Competing interest reported. Co-authors Yang Jae Lee, Scott Blackwell, Kazungu Rauben, Scott Blackwell, and Emery Monnig are either Directors or Affiliates in the 501©3 organization Empower Through Health, which funded and supported this study. There are no other competing interests for any other authors.","formattedTitle":"Twelve-month Outcomes of a Mental Illness Destigmatizing Theatrical Intervention in Rural Uganda","fulltext":[{"header":"Background","content":"\u003cp\u003eMental illnesses are the leading cause of disability in the world [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The burden of mental illness is especially high in low- and middle-income countries (LMICs), where there is a limited supply of providers [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] and multiple barriers to care. Prominent among these barriers is stigma, a complex of negative cultural attitudes towards and beliefs about people who experience mental illness, which can lead to impaired self-esteem, social ostracism, shame, and reluctance to seek treatment [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eUganda, like many nations within East Africa, has seen a significant increase in population over the last few decades, from 36\u0026nbsp;million to 45\u0026nbsp;million people since 2014 [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. It is estimated that up to 35 percent of the Ugandan population suffers from at least one mental illness, resulting in a critical need for increased use of effective psychiatric services throughout the country [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This issue is exacerbated by the country\u0026rsquo;s lack of trained healthcare professionals as there are only 0.78 psychiatric nurses per 100,000 individuals, primarily concentrated in the country\u0026rsquo;s one psychiatric hospital, Butabika National Referral Mental Hospital located in the capital, Kampala [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. As a result, rural areas of Uganda are disproportionately affected by this treatment gap, due to long travel distances, high levels of poverty, and stigma around mental illness [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe strongest predictor of an individual\u0026rsquo;s ability to recover from a mental illness is the presence of a robust support system [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In LMICs, like Uganda, most individuals derive this support from their local community [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, misunderstandings about mental illness and prejudice against afflicted individuals result in personal, public, and structural stigma, all of which can erode community supports [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. A lack of health education, which is especially common in lower-income and rural populations, further exacerbates the stigmatization of people with mental illnesses [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Thus, mental illness destigmatization education is vital to reduce the burden of stigma towards those with mental illness and increasing access to care.\u003c/p\u003e \u003cp\u003eEducational interventions have been shown to successfully reduce mental health stigma [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. While a variety of educational approaches have been designed and tested, approaches to educational interventions using creative arts have been less studied than more didactic approaches [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Lee et al. in 2022 developed and evaluated the effectiveness of a community-led theatrical performance in the rural Busoga region of eastern Uganda, depicting an individual\u0026rsquo;s progression from intense, debilitating mental illness to establishing care opportunities at a health center, receiving individualized treatment, attaining gainful employment, and achieving reintegration into society [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Participants exposed to this intervention showed a significant and sizable reduction in mental health stigma from baseline to a one-week follow-up assessment. This is the first study, to our knowledge, to demonstrate the effectiveness of an arts intervention in reducing mental health stigma among the general population of a rural region of a low-income country.\u003c/p\u003e \u003cp\u003eThis study aims to extend the findings of Lee et al., in an evaluation of the long-term effectiveness of this community-led theatrical intervention in reducing mental health stigma by reporting the results of a one-year follow-up survey of the initial study participants. A detailed description of the community-led theater intervention, participant selection, and immediate post-intervention results have been reported previously by Lee et al. (2022) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe study was conducted in the Busoga region of rural Eastern Uganda, specifically in Buyende District (Fig.\u0026nbsp;1), which consists of sixty-eight parishes and is home to an estimated 450,100 people [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Participants were chosen after all villages in five parishes (Bukutula, Kabukye, Kagulu, Kirimwa, and Igalaza) were assigned a number, and residents of ten villages were randomly selected through a random number generator. At each involved village, ten households were identified through assigning each household in the village with a number and selecting subjects through a random number generator. At each selected household, researchers obtained a list of every household member aged 18 years or older, and each individual was assigned a number and one was randomly selected. If no household members were home or met the inclusion criteria, a different household was randomly selected. This process was iterated until ten participants were recruited from each village. Through this process, 101 participants were enrolled in the study.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eFigure 1\u003c/strong\u003e \u003cp\u003eRegions of Uganda, with Buyende District within the Eastern Region (Map from World Atlas [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e])\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eFigure 2\u003c/strong\u003e \u003cp\u003eBuyende District Parishes which held theater interventions (Map data \u0026copy;2022 GoogleMaps [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] )\u003c/p\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eINTERVENTION: THEATER PLAY DESIGN AND PERFORMANCE\u003c/h2\u003e \u003cp\u003eMessage design theory underpinned by an audience-channel-message-evaluation (ACME) framework was used to design the original theater intervention [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The ACME framework organizes the principles of an effective health education campaign into four major categories: audience, channel, message, and evaluation. In translating this theory into practice, the target audience\u0026rsquo;s attitudes and stigma towards mental illness was measured, and that information was utilized to develop and implement a community-led theater performance in collaboration with community health workers. Theater was used because it is a common channel of media in the region [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The message depicted a protagonist and a storyline that are relatable to the audience, and was grounded in translating social cognitive theory into practice [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eQualitative data was collected through four focus groups to identify common misconceptions and specific points of stigma related to mental health. Based on the responses from the focus groups, local community health workers developed a culturally appropriate theatrical performance that addressed these points of stigma and encouraged seeking care. This play was then performed in July 2021 in the villages where the 101 participants who completed the structured questionnaire resided, and the participants were encouraged to attend the performance although no financial compensation was offered.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eQUESTIONNAIRE DESIGN AND ADMINISTRATION\u003c/h2\u003e \u003cp\u003eOutcomes were assessed with a 61-item questionnaire that gathered demographic data and included two stigma-focused batteries, the Personal Acceptance Scale (PAS) and the Broad Acceptance Scale (BAS), described in Lee et al [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The PAS targets population stigma, and consists of community-influenced negative attitudes, beliefs, and behaviors towards people with mentally illness. The BAS targets structural and institutional stigma, such as the cultural norms and institutional practices likely to limit the resources, opportunities, and well-being of individuals with mental illness.\u003c/p\u003e \u003cp\u003eThe questionnaire was administered to all 101 participants within two weeks before the play performances (baseline). All participants were contacted for a follow-up interview, and 57 of the original participants were re-surveyed one week after the intervention with the BAS and PAS in August 2021 to measure changes in stigma towards mental illness. Those that were unable to be resurveyed either could either not be located or did not participate in the intervention. During the summer of 2022, 46 of the 57 participants that were re-surveyed after the intervention were re-interviewed to measure the permanence of attitude changes towards mental illness stigma.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eINCLUSION CRITERIA\u003c/h2\u003e \u003cp\u003eAll individuals who participated in the 2022 theater intervention who are over 18 years old and able to provide informed consent were eligible for the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eEXCLUSION CRITERIA\u003c/h2\u003e \u003cp\u003eIndividuals who did not participate in the 2022 theater intervention or who are under the age of 18 or could not give informed consent to participate in this study were excluded. Individuals who could not be reached or who did not consent to participate were excluded.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003ePARTICIPANT INFORMATION\u003c/h2\u003e \u003cp\u003eThe follow-up cohort consisted of nine males and thirty-seven females (Total N\u0026thinsp;=\u0026thinsp;46); the mean age of the cohort was 40.0 years. Thirty-nine participants were of Christian denominations (Catholic, Anglican, Pentecostal, Seventh Day Adventist, and Born-Again Churches) with the remaining seven individuals being Muslim. Thirty-one participants did not complete primary school or never attended primary school, fourteen completed primary school, and one individual completed some years of secondary school.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSTATISTICAL METHOD\u003c/h2\u003e \u003cp\u003eFor both the BAS and PAS, the average difference between each pair of time points was tested using a paired t-test.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe marginal distribution of BAS scores observed at each time point is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e; the marginal distribution of PAS scores, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The average improvement in BAS at baseline observed at time point two (one-year follow-up) was 1.435 (95% CI: 0.826\u0026ndash;2.044, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, SD: 1.64). This estimated effect was almost as strong as and within the confidence interval of the average improvement estimated at time point one, one week after the intervention, 1.609 (95% CI: .994\u0026ndash;2.224, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). The average improvement in PAS at baseline observed at time point two was 2.152 (95% CI: 1.444\u0026ndash;2.860, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, SD: 1.93). This estimated effect is higher than but within the confidence interval of the average improvement estimated at time point one, 1.804 (95% CI: 1.134\u0026ndash;2.475, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStatement of Principal Findings:\u003c/h2\u003e \u003cp\u003eThis study aimed to assess the persistence of stigma reduction among rural Ugandans one year after viewing the initial theater intervention. The results suggest that the effects on participants\u0026rsquo; attitudes towards individuals with mental illness were sustained significantly over one year with magnitude of the reduction of stigma at around one standard deviation. Both the initial post-intervention and one-year follow-up surveys showed substantially greater effect sizes when compared to similar studies that have attempted to quantify and reduce mental health-related stigma at the community level in LMICs [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. These results suggest that community-led, theatrical interventions may be an effective tool for inducing long-term, persistent reductions in mental illness-associated stigma among rural populations of low-income countries.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Weaknesses of the Study:\u003c/h2\u003e \u003cp\u003eThe effectiveness of the intervention likely derives from its theoretical audience-channel-message-evaluation (ACME) framework[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and its community-based approach, in which community health volunteers devised and performed a play that harmonized existing cultural ideas around the topic with new beliefs and knowledge about mental illness [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The intervention was therefore created by individuals with similar cultural perspectives as the target audience. The actors also utilized a variety of strategies to effectively engage their audience that included traditional music, props, and humor. The message depicted a protagonist and a storyline that are relatable to the audience[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Additionally, theater is a common channel of media in the region[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] likely contributing to its acceptance and success. This community-centered approach also likely contributed to the relatively low attrition rate (19.2%) from 57 participants in the one-week follow-up to this study\u0026rsquo;s twelve-month follow-up cohort (n\u0026thinsp;=\u0026thinsp;46). Community health volunteers are well-respected community members with substantial knowledge about other individuals in their respective villages and are a key component of the health infrastructure in Uganda as well as other countries in Sub-Saharan Africa [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA limitation of the study was its small sample size, which could limit the generalizability of the results. Additionally, a control group was not used in the initial study, so it is possible that various confounds such as selection biases could have contributed to the changes in mental health stigma in this particular group. Although the drop-out rate was relatively low between one week and twelve months after the intervention, it is possible that some participants could not be located or refused to consent for a non-random reason. However, demographic data comparing the entire intervention cohort and the follow-up cohort did not reveal statistically significant differences (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e), suggesting that the two cohorts were comparable and representative of the target population. The drop-out rate could potentially have been improved if the initial post-intervention cohort was informed that a follow-up study would be conducted after one year. Additionally, cash compensation for participating in the interviews could have helped with the retention. Another limitation was the use of self-reported measures of stigma, which may be subject to social desirability bias. Such bias has been shown to play a role in stigma around drug use [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], but to the authors\u0026rsquo; knowledge the role of this bias on mental health attitudes in particular and stigma in general have not been substantially studied. Finally, the study was limited to rural areas in the Busoga Region of Uganda, and although there are significant similarities between our study population and other rural populations in Sub-Saharan Africa, it is unclear whether similar effects of similar interventions would be found in other contexts or populations that may have different cultural practices, beliefs, and stigmas around mental illness.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifferences between cohorts interviewed at twelve months and the remaining\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eReinterviewed at twelve months (N\u0026thinsp;=\u0026thinsp;46)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003enot reinterviewed at twelve months (N\u0026thinsp;=\u0026thinsp;55)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eOverall (N\u0026thinsp;=\u0026thinsp;101)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0856\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(80.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(60.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(69.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(19.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(40.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(30.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.973\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(17.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(16.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian [Min, Max]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[18.0, 80.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[18.0, 86.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e[18.0, 86.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.833\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried or Cohabiting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(76.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(80.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(78.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeparated (married but not cohabiting)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(5.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(4.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle \u0026amp; Never Married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(10.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(5.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(7.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(10.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(5.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(7.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReligion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.388\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnglican\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(37.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(23.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(29.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBorn Again\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCatholic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(10.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(29.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(20.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuslim\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(15.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(27.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(21.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePentecostal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(32.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(12.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(21.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeventh Day Adventist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(3.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsa Masia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccupation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.998\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrewer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHairdresser\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeasant Farmer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(84.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(85.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(85.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProduce Seller\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShop Owner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTailor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUn-employed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(3.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePancake Seller\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetired Peasant Farmer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.905\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplete Primary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(28.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(29.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(28.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncomplete Primary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(45.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(45.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(45.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncomplete Secondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever Attended\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(21.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(14.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(17.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO-Level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(9.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNursery School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVillage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBulayi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(10.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(9.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(9.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBulondo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(17.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(9.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBunangwe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(13.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(7.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(9.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBusuyi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(10.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(9.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(9.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGabano\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(6.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(5.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGabona\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(6.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(5.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKinamagira\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(6.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(14.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(10.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKinatebe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(14.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(9.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMasaba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(14.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(9.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNadiyope\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(14.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(9.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNgereka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(15.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(5.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(9.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousehold Size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.381\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(1.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian [Min, Max]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[1.00, 12.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[1.00, 9.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e[1.00, 12.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBroad Acceptance Scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.847\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian [Min, Max]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[1.00, 8.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[2.00, 9.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e[1.00, 9.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePersonal Acceptance Scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.746\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(2.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(1.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian [Min, Max]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0, 7.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0, 8.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e[0, 8.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Weaknesses in Relation to Other Studies:\u003c/h2\u003e \u003cp\u003eTo our knowledge, this was the first long-term follow-up study attempting to quantify the persistence of mental illness stigma after a community-led theater intervention among rural populations in a low-income country. De-stigmatization interventions remain an understudied topic in low-income countries. A meta-analysis investigating interventional stigma reduction studies in LMICs identified notable literature gaps in research on this topic, such as generally poor quality of outcome reporting and a small number of studies overall that have collected empirical data and reported at least one outcome [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Of the studies that seek to counter stigma and discrimination, most research has focused on short-term outcomes and has been conducted in high-income settings [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In low-income countries, it has been suggested that targeted community interventions are more effective than top-down educational campaigns [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], a claim that is further supported by our study. As reported previously, most interventions have targeted healthcare workers, rather than community members [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Further, a systematic review of mental health stigma reduction interventions in low- and middle-income countries found that only a small minority were developed by local residents or culturally adapted [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study did not evaluate the relative effectiveness of different intervention types; therefore, it is possible that an intervention that was structured differently could have been more effective at reducing long-term stigma. Additionally, this study did not investigate the attitudes of community health workers towards mental illness after one year, although in the original study there was some qualitative evidence suggesting that community health workers may harbor their own stigmas towards individuals with mental illness. If this were the case, community-wide stigma would likely be significantly affected since community health workers are typically influential and sources of health-related information in their local communities. This study also focused on an intervention addressing mental health conditions that are most outwardly apparent to the community and most debilitating for the individual, i.e. schizophrenia and bipolar mania. It is unclear whether the same conclusions could be extrapolated to less apparent forms of mental illness, such as depression, anxiety, or substance abuse. More research into different types of community interventions addressing a variety of stigmatized conditions could help identify the optimal approach to address mental health stigma, as this remains a major barrier for afflicted individuals to seek treatment [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eMeaning of the Study:\u003c/h2\u003e \u003cp\u003eEvidence-based interventions are of critical importance to governments and non-governmental organizations as they seek to allocate funds to address these health problems. This study suggests that locally adapted, community-based, creative media interventions can be an effective, affordable, and scalable strategy to create meaningful, long-term reductions in mental illness stigma among rural populations in Sub-Saharan Africa. Reduction of stigma at around one standard deviation is greater than any other interventions that we have found reported to decrease mental illness stigma [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere are a variety of factors that could account for the success of this intervention. The performance script was both created and acted out by community health workers, which could have increased its credibility and acceptance among the villagers. Their involvement was also meant to ensure that the message was culturally sensitive, locally relevant, and engaging to the audience. Our results could also be attributed to the relatively limited access to mass media in the village communities we studied, thus the novelty of free theatrical performance may have attracted a larger audience and increased engagement with the educational content it conveyed. Furthermore, such limited access to media may have made the performance more memorable, potentially accounting for the lasting impact data we found. As a medium, theater allows for the depiction of real-life scenarios and challenges that an individual with mental illness faces in society, which can increase empathy and understanding among audience members. Encountering and grappling with the topic in this way could have been perceived by participants as more accessible and relatable than other interventional approaches.\u003c/p\u003e \u003cp\u003eThe report on the original study suggested that the intervention cohort demonstrated a greater willingness to live, work, interact, and understand those with mental illness [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This follow-up study demonstrated that these attitude shifts persist for at least one year and may even become more pronounced after a substantial period of time, suggesting that this model could be used to enact significant, long-term change in attitudes amongst rural Ugandans. Current literature suggests that interventional stigma reduction approaches can often fail to demonstrate lasting effects, so it is especially notable that these effects persisted in this one-year follow-up [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt is also worth noting that, while not statistically significant, the PAS effect size was larger in the year follow-up study (2.152, CI\u0026thinsp;=\u0026thinsp;1.444\u0026ndash;2.860) than it was among the initial post-intervention cohort (1.804, CI\u0026thinsp;=\u0026thinsp;1.134\u0026ndash;2.475). While this result could be due to random chance, it is also possible that a greater sample size would have demonstrated statistical significance. If this were the case, one potential explanation could be that the theater intervention acted as an impetus for critical reflection and attitude shifting on an individual level. It could also be the result of an increase in the number of conversations occurring among community members around this topic, as suggested qualitatively from focus group responses in the original Lee et al. study [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe broader implications of this study are significant, as reducing personal and community-wide stigma is a critical step in improving access to care and overall health outcomes for the mentally ill. Given the high burden of mental illness in many low- and middle-income countries, the use of community-led arts interventions to reduce stigma may be an important strategy for improving mental health outcomes in these settings [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eFuture Directions:\u003c/h2\u003e \u003cp\u003eFuture directions for this study should include an exploration of the efficacy of similar mental illness de-stigmatization interventions on a larger scale, such as through radio broadcasts or other forms of mass media that have high engagement in low-income, rural settings. This would allow the intervention to reach a wider audience and potentially have a greater impact on reducing stigma at the community level. Additionally, it would be valuable to assess the sustainability of the effects of the intervention over a longer period, such as three or five years. This would provide further insight into the persistence of changes in attitudes and beliefs towards mental illness.\u003c/p\u003e \u003cp\u003eAnother area for future research could be to evaluate the feasibility and impact of incorporating the intervention into routine healthcare services, such as mental health clinics and outreach campaigns. This would ensure that the intervention reaches those who may be most in need of support and can be delivered in a sustainable and cost-effective manner. Furthermore, it would be prudent to explore the generalizability of this intervention model in regard to other aspects of mental health, such as stigma towards more insidious forms of mental illness, care-seeking behavior, knowledge of mental health maintenance and self-care, and the reduction of harmful coping mechanisms such as substance abuse.\u003c/p\u003e \u003cp\u003eGiven the significant effect size demonstrated both in the original study and this follow-up, it would be valuable to explore the efficacy of this model in other cultural and linguistic contexts. Mental illness stigma is a complex and multifaceted issue, and it is plausible that the effect sizes of similar interventions could vary depending on cultural perspectives and linguistic idiosyncrasies of the unique population being studied. By examining the impact of the intervention in different contexts, we could gain a better understanding of how to adapt the intervention to maximize its effectiveness.\u003c/p\u003e \u003cp\u003eIn conclusion, this study provides promising evidence for the effectiveness of a community-led mental illness de-stigmatization theater intervention in reducing stigma towards mental illness in rural Uganda. It is our hope that the model presented in this manuscript can be further refined, tested, and implemented at scale to improve mental health outcomes among vulnerable global populations.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCo-authors Yang Jae Lee, Scott Blackwell, Kazungu Rauben, Scott Blackwell, and Emery Monnig are either Directors or Affiliates in the 501\u0026copy;3 organization Empower Through Health, which funded and supported this study. There are no other competing interests for any other authors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eEthics Approval:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBefore all surveys, a research assistant read a consent form describing the aim and potential risks of the study, and all participants gave verbal and written informed consent. All methods were carried out in accordance with relevant guidelines and regulations. This project was approved by the Institutional Review Board of The AIDS Support Organization, Uganda and Uganda National Council of Science and Technology. Names of participants were removed from the dataset to ensure anonymity, and participants were assigned an identifying number.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Institutional Review Board - The AIDS Support Organization, Uganda: #TASOREC/048/2021-UG-REC-009.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Uganda National Council of Science and Technology registration number: HS1764ES.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMaps G: \u003cstrong\u003eGeography of Uganda\u003c/strong\u003e. In\u003cem\u003e.\u003c/em\u003e; 2022.\u003c/li\u003e\n\u003cli\u003eWorldAtlas: \u003cstrong\u003eRegions of Uganda Map\u003c/strong\u003e. 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A meta-analysis of randomized controlled trials\u003c/strong\u003e. \u003cem\u003eWorld Psychiatry \u003c/em\u003e2014, \u003cstrong\u003e13\u003c/strong\u003e(2):161-175.\u003c/li\u003e\n\u003cli\u003eMusoke D, Atusingwize E, Ikhile D, Nalinya S, Ssemugabo C, Lubega GB, Omodara D, Ndejjo R, Gibson L: \u003cstrong\u003eCommunity health workers\u0026apos; involvement in the prevention and control of non-communicable diseases in Wakiso District, Uganda\u003c/strong\u003e. \u003cem\u003eGlobal Health \u003c/em\u003e2021, \u003cstrong\u003e17\u003c/strong\u003e(1):7.\u003c/li\u003e\n\u003cli\u003eLatkin CA, Edwards C, Davey-Rothwell MA, Tobin KE: \u003cstrong\u003eThe relationship between social desirability bias and self-reports of health, substance use, and social network factors among urban substance users in Baltimore, Maryland\u003c/strong\u003e. \u003cem\u003eAddict Behav \u003c/em\u003e2017, \u003cstrong\u003e73\u003c/strong\u003e:133-136.\u003c/li\u003e\n\u003cli\u003eKemp CG, Jarrett BA, Kwon CS, Song L, Jette N, Sapag JC, Bass J, Murray L, Rao D, Baral S: \u003cstrong\u003eImplementation science and stigma reduction interventions in low- and middle-income countries: a systematic review\u003c/strong\u003e. \u003cem\u003eBMC Med \u003c/em\u003e2019, \u003cstrong\u003e17\u003c/strong\u003e(1):6.\u003c/li\u003e\n\u003cli\u003eProctor E, Silmere H, Raghavan R, Hovmand P, Aarons G, Bunger A, Griffey R, Hensley M: \u003cstrong\u003eOutcomes for implementation research: conceptual distinctions, measurement challenges, and research agenda\u003c/strong\u003e. \u003cem\u003eAdm Policy Ment Health \u003c/em\u003e2011, \u003cstrong\u003e38\u003c/strong\u003e(2):65-76.\u003c/li\u003e\n\u003cli\u003eChu C, Roxas N, Aguocha CM, Nwefoh E, Wang K, Dike C, Iheanacho T: \u003cstrong\u003eIntegrating mental health into primary care: evaluation of the Health Action for Psychiatric Problems In Nigeria including Epilepsy and SubstanceS (HAPPINESS) pilot project\u003c/strong\u003e. \u003cem\u003eBMC Health Serv Res \u003c/em\u003e2022, \u003cstrong\u003e22\u003c/strong\u003e(1):333.\u003c/li\u003e\n\u003cli\u003ePetersen I, Lund C: \u003cstrong\u003eMental health service delivery in South Africa from 2000 to 2010: one step forward, one step back\u003c/strong\u003e. \u003cem\u003eS Afr Med J \u003c/em\u003e2011, \u003cstrong\u003e101\u003c/strong\u003e(10):751-757.\u003c/li\u003e\n\u003cli\u003eClay J, Eaton J, Gronholm PC, Semrau M, Votruba N: \u003cstrong\u003eCore components of mental health stigma reduction interventions in low- and middle-income countries: a systematic review\u003c/strong\u003e. \u003cem\u003eEpidemiol Psychiatr Sci \u003c/em\u003e2020, \u003cstrong\u003e29\u003c/strong\u003e:e164.\u003c/li\u003e\n\u003cli\u003eHenderson C, Evans-Lacko S, Thornicroft G: \u003cstrong\u003eMental illness stigma, help seeking, and public health programs\u003c/strong\u003e. \u003cem\u003eAm J Public Health \u003c/em\u003e2013, \u003cstrong\u003e103\u003c/strong\u003e(5):777-780.\u003c/li\u003e\n\u003cli\u003eMorgan AJ, Reavley NJ, Ross A, Too LS, Jorm AF: \u003cstrong\u003eInterventions to reduce stigma towards people with severe mental illness: Systematic review and meta-analysis\u003c/strong\u003e. \u003cem\u003eJ Psychiatr Res \u003c/em\u003e2018, \u003cstrong\u003e103\u003c/strong\u003e:120-133.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003eTable 1 is available in Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Global mental health, stigma, psychosis, mental illness, art-based interventions","lastPublishedDoi":"10.21203/rs.3.rs-2743636/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2743636/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eEvaluate the long-term effectiveness of a community-led theatrical intervention in reducing mental health stigma in a low-income setting in Uganda.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA follow-up survey of study participants was conducted 12 months after the initial community-led theatrical intervention measuring the primary outcomes of mental illness stigma using the Broad Acceptance Scale (BAS) and the Personal Acceptance Scale (PAS).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf the initial 57 participants, 46 (80%) completed the follow-up survey. The average improvement in Broad Acceptance Scale and Personal Acceptance Score observed from baseline to twelve months after the intervention was 1.435 (95% CI: 0.826\u0026ndash;2.044, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, SD: 1.64) and 2.152 (95% CI: 1.444\u0026ndash;2.860, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, SD: 1.93), respectively. Both effect sizes were within the confidence intervals of the average improvement observed one week after the intervention.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eExposure to the community-led theatrical intervention continued to confer a significant and substantial reduction in mental illness stigma.\u003c/p\u003e","manuscriptTitle":"Twelve-month Outcomes of a Mental Illness Destigmatizing Theatrical Intervention in Rural Uganda","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-03-31 14:46:20","doi":"10.21203/rs.3.rs-2743636/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"92727076-004c-4be0-98da-f5478808a3ba","owner":[],"postedDate":"March 31st, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-04-17T14:29:52+00:00","versionOfRecord":[],"versionCreatedAt":"2023-03-31 14:46:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2743636","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2743636","identity":"rs-2743636","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}