Barriers and Facilitators to Tele-Support Psychotherapy Versus Standard In-Person Mental Health Services for Youth (15-30 Years) with Depression in Kampala District, Uganda.

Barriers and Facilitators to Tele-Support Psychotherapy Versus Standard In-Person Mental Health Services for Youth (15-30 Years) with Depression in Kampala District, 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 Barriers and Facilitators to Tele-Support Psychotherapy Versus Standard In-Person Mental Health Services for Youth (15-30 Years) with Depression in Kampala District, Uganda. Jeremiah Kwesiga Mutinye, JohnMark Bwanika, Davis Musingunzi, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6232041/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 Background: Depression remains a critical mental health challenge among young people in low-resource settings, where financial, structural, and social barriers frequently limit care access. Digital approaches, including tele-support psychotherapy (TSP), have emerged as promising, scalable alternatives to standard in-person mental health services (SMHS); however, comparative insights into their relative strengths and limitations remain scarce. Objective: This study sought to identify and compare facilitators and barriers influencing youth engagement with TSP versus SMHS for depression treatment in Kampala District, Uganda. Methods: We conducted a qualitative phenomenological investigation involving youth aged 15–30 enrolled in a randomized controlled trial evaluating both interventions. Data were gathered through semi-structured key informant interviews and focus groups with participants and lay counselors, and analyzed via inductive thematic analysis Results: Among 154 participants assigned to TSP, 95 engaged with the tele-psychotherapy call platform, compared to only 15 out of 146 in the SMHS group. This disparity in engagement underscores the potential of TSP to improve access to mental health care. Key facilitators for both interventions included strong social support networks and higher income levels, highlighting the crucial interplay of individual and systemic factors. Technological challenges, such as unreliable communication, hindered TSP, while high costs and limited awareness were barriers to SMHS. Government policies played a dual role, fostering trust in digital interventions while inadvertently limiting access for some. Lay counselor attributes, including flexibility and rapport-building skills, were critical facilitators. Conclusion: TSP presents a viable alternative to SMHS, particularly for youth facing financial and logistical barriers. However, optimizing its delivery requires addressing technological constraints, ensuring consistent government support, and integrating mental health literacy initiatives. Findings underscore the need for flexible and contextually tailored models that leverage technology and address individual and systemic barriers to enhance mental health service access in resource-constrained settings. Psychology Psychiatry Introduction Depression remains a critical mental health challenge among youth globally, with alarming prevalence rates observed across continents ( 1 – 3 ). In Africa, the burden of mental health disorders is particularly acute, evidenced by the region's disproportionately high suicide rates and limited access to psychosocial interventions at the primary healthcare level ( 4 , 5 ). Uganda, specifically, ranks among the top countries on the continent with high depression rates, a consequence of its history of conflict, high disease burden (including HIV), and persistent economic hardships ( 6 , 7 ). These factors have contributed to depression rates that exceed global averages ( 8 , 9 ). The COVID-19 pandemic further exacerbated this mental health crisis, particularly among youth. Lockdown measures, social isolation, job losses, and economic uncertainty created a perfect storm for increased depression and anxiety ( 10 – 12 ). This impact was especially pronounced in Sub-Saharan Africa (SSA), where the pooled prevalence of common mental disorders among youth was significantly higher compared to other regions ( 13 , 14 ). In Kampala District, Uganda, these challenges are compounded by a severe shortage of mental health resources. The district has limited specialized mental health facilities and a critical lack of trained mental health professionals ( 15 , 16 ). This creates a substantial gap in the care of young people with depression, who often face additional barriers such as stigma, financial constraints, and geographical limitations. To address these gaps in mental health service delivery, digital interventions, particularly telepsychotherapy, have emerged as promising solutions ( 17 , 18 ). These interventions have shown potential for increasing access to mental health care, especially in resource-limited settings ( 19 – 21 ). Notably, in response to the surge in mental health problems among youth during the COVID-19 pandemic, our research team adapted group support psychotherapy into tele-support psychotherapy (TSP) via mobile phones. In a 12-month pilot study, we observed significantly higher engagement with TSP than standard mental health services (SMHS) offered at health centers. Specifically, 95 participants (61.69%) attended TSP sessions, compared to only 15 participants (10.27%) in the control arm who sought in-person treatment( 22 ). This data demonstrates the potential of TSP to improve engagement with mental health care in resource-constrained environments. However, despite the promising results of TSP and other tele-psychotherapy approaches, traditional in-person mental health services remain the prevalent approach to youth mental health care in Uganda. This discrepancy highlights the need to understand the factors influencing the adoption of different service delivery models. In Kampala, the specific barriers and facilitators to telepsychotherapy and in-person mental health services for youth with depression remain largely unexplored. Understanding these factors is crucial for designing and implementing effective mental health interventions that are tailored to the local context. Therefore, this study aims to identify and compare the perceived barriers and facilitators to accessing telepsychotherapy and in-person mental health services among youth ( 15 – 30 ) with depression in Kampala District. We will address the following research questions: ( 1 )What are the perceived barriers and facilitators to accessing tele-psychotherapy among youth with depression in Kampala District? ( 2 ) How do these barriers and facilitators compare to those associated with in-person mental health services? The findings from this study will provide critical insights for policymakers, mental health practitioners, and researchers in designing, implementing, and scaling up mental health interventions for youth with depression in resource-limited settings. Methods Study Design This was a phenomenological community-based qualitative study that explored the experiences of youth with depression who received, and lay-counselors who provided, psychotherapy through mobile phones and/or standard in-person counseling during a randomized controlled trial (RCT) carried out in Kampala, Uganda ( 22 ). To comprehensively evaluate the implementation of tele-support psychotherapy (TSP) within this context, we employed the Consolidated Framework for Implementation Research (CFIR) ( 23 ). The CFIR is a widely used framework that guides the in-depth assessment of factors influencing the implementation of health innovations. It consists of five domains: Intervention Characteristics, Outer Setting, Inner Setting, Characteristics of Individuals, and Process ( 23 ). Guided by the CFIR, this study aimed to identify and understand the multi-level factors affecting the implementation of TSP and compare them with those associated with standard mental health services (SMHS). We chose a phenomenological approach as it allows for a rich exploration of individuals' lived experiences, enabling us to gain deeper insights into the barriers and facilitators influencing the adoption and use of both TSP and SMHS ( 24 , 25 ). We anticipated that this approach would generate contextualized, evidence-based data crucial for designing and implementing effective mental health programs in similar resource-limited settings ( 26 ).. Semi-structured key informant interviews (KIIs) and focus group discussions (FGDs) were conducted between March and July 2024. The study focused on youth and emancipated minors, as they constitute over 70% of the population in urban centers in Uganda and are disproportionately affected by mental health challenges due to socioeconomic hardships and stigma. The TSP model used in this study was adapted from the Group Support Psychotherapy (GSP) model, a culturally sensitive intervention that has demonstrated effectiveness in managing depression among adults with HIV ( 27 ). To optimize GSP for remote delivery via mobile phones, we made several key modifications. These included adapting the session content and structure to maintain engagement and minimize distractions, recognizing the unique challenges of telepsychotherapy. We also developed a comprehensive training program to equip lay counselors with the skills and knowledge necessary to deliver TSP effectively, ensuring fidelity to the model while accommodating the remote format. Additionally, we integrated technology-assisted tools, such as SMS reminders and mobile-based self-help resources, to enhance participant engagement and provide support between sessions. This adapted TSP model has proven feasible for managing depression and was well-received in the communities where it was implemented ( 22 ). The utilization of lay counselors to deliver TSP further amplifies its potential to bridge the substantial mental health support human resource gap prevalent in LMICs, offering a scalable and cost-effective solution. Study Setting This qualitative study was conducted in three communities within Kampala, Uganda: Kamwokya, Naguru, and Makerere. These communities represent the administrative divisions of Kampala Central, Nakawa, and Kawempe, respectively. Kampala, the capital city of Uganda, is made up of five distinct geographical divisions. Kampala is the most densely populated city in the country with over 2.5 million daytime inhabitants with over 40% of these individuals staying in slums ( 28 , 29 ). These slums are at increased risk for socioeconomic and public health-related challenges such as high rates of unemployment, substance abuse, poor access to healthcare services including mental health and insecurity ( 30 ). Study Population Study participants and lay-counselors (LCs) who had been assigned to receive and deliver psychotherapy respectively over mobile phones and/or standard mental health services were called for exit key-informant interviews (KIIs) and focus group discussions (FGDs). The study participants in this study were part of the 300 participants in the RCT whose details are published elsewhere ( 31 ). After 12 months, purposive sampling was used to select the participants for the exit KIIs from participants who had completed and those who had not completed sessions in both the cases and the controls. Participants were selected from Kamwokya, Naguru, Key population and Makerere communities aged between 16–30 years. The FGDs were gender-specific, ensuring both male and female perspectives were represented. Gender-specific groups allowed for open and comfortable discussions, particularly on sensitive topics like depression, stress and anxiety. These groups were designed to include 6–10 participants, likely to maintain an optimal size for productive discussions ( 32 ). Data Collection The KIIs and FGDs were designed to elicit in-depth information about the participants' experiences with TSP and SMHS, guided by the CFIR domains. The interview guide was structured to explore factors related user satisfaction with both interventions, including perceived benefits, challenges, and preferences (Intervention Characteristics). We also investigated external factors influencing service utilization, such as community attitudes towards mental health and the availability of alternative services (Outer Setting). Additionally, we examined structural factors within the implementing organizations, such as resource availability and staff attitudes towards technology (Inner Setting). Individual-level factors influencing service uptake and engagement, such as technology literacy, motivation, and prior experiences with mental health care, were also considered (Characteristics of Individuals). Finally, we explored implementation-related factors, such as communication strategies, training of lay counselors, and the fidelity of intervention delivery (Process). The interviews and focused group discussions were facilitated by the study’s lead research coordinators (BH and BK). By the fourth FGD data saturation was reached with no new codes generated. However, given our groups were gender-specific we intended to have an upper limit of the number of FGDs ( 6 ) to achieve saturation as recommended by different qualitative data collection literature ( 33 – 35 ). These focus group discussions were audio recorded, with the research assistants writing field notes for to contextualized the transcripts during the analysis. This practice has shown to improve on the interview process and the subsequent data analysis and a great supplement to the use of audio-recorded data alone ( 36 , 37 ). The audio recordings were then transcribed verbatim with the interviews in Luganda concurrently translated to English for analysis. The research assistants’ coordinator, HB reviewed the transcribed interviews against the audio recordings to ensure consistency before final approval for analysis. The study participants were reimbursed with approximately 5 dollars each for their time and participation in the interviews at the end of the interviews. Data Analysis Approved transcripts from the interviews were uploaded to qualitative analysis software (MAXQDA v22.5.0). This study employed deductive thematic analysis, guided by the Consolidated Framework for Implementation Research (CFIR), to identify and categorize barriers and facilitators of TSP and SMHS. The transcripts were pre-coded based on the five CFIR domains with two coders (HB and JMK) independently reviewing the data and assigning excerpts to the relevant CFIR category. Any discrepancies were resolved through discussion with the senior researchers (JMB and EN). This structured approach ensured that findings were systematically mapped to well-established implementation science constructs, facilitating a deeper understanding of the factors influencing mental health service delivery in resource-limited settings. The use of the CFIR framework allowed for a systematic and comprehensive analysis of the barriers and facilitators to TSP and SMHS implementation. By mapping our findings to the CFIR constructs, we aimed to provide a more nuanced understanding of the factors influencing mental health service delivery in resource-limited settings, ultimately informing the development and implementation of more effective interventions. Results Comparison of Baseline Characteristics between Tele-support psychotherapy (TSP) Engagers and Non-Engagers. No significant differences were found between engagers and non-engagers in terms of baseline anxiety, stigma, days unable to work due to health issues, alcohol use, social support, self-esteem, social group membership, or total social resources. However, there was a marginally significant difference in monthly income (p = 0.055), with engagers reporting higher income than non-engagers. Additionally, engagers were significantly older than non-engagers (p = 0.008). The proportion of individuals with different education levels was similar between the two groups. However, a significantly higher proportion of engagers were employed than non-engagers (χ²=5.14, p = 0.023). Females demonstrated the highest engagement, with 76.84% attending at least one TSP session. In contrast, only 18.95% of males engaged with the intervention. Notably, LGBTQ individuals had the lowest engagement, at 4.21%. Details are shown in Table 1 Comparison of Baseline Characteristics between Standard Mental Health Services(SMHS) engagers and non-engagers. A comparison of baseline characteristics between those who engaged with standard mental health services (SMHS) by attending at least one session (engagers) and those who did not (non-engagers) revealed some notable differences. While there were no significant differences in age, gender, education level, employment status, or income-generating activity, a marginally significant difference in marital status (p = 0.073) was observed, with a trend towards a higher proportion of married individuals among engagers. Furthermore, engagers had significantly higher monthly income (p = 0.021) and savings (p < 0.001) compared to non-Engagers. No significant differences were found between the groups in terms of total social resources, anxiety levels, perceived stigma, days unable to work due to health, alcohol use, social support, or self-esteem, although there was a trend towards higher social support among Engagers (p = 0.076). These findings suggest that while SMHS Engagers and Non-Engagers were generally comparable on most socio-demographic and psychosocial characteristics, differences in marital status, income, and savings should be considered when interpreting the impact of SMHS engagement on treatment outcomes. Details are shown in Table 2. Barriers and Facilitators to Tele-Support Psychotherapy Versus In-Person Mental Health Services Of the 248 study participants who completed the 12-month follow-up assessments, 140 also completed the Exit survey. This survey explored barriers and facilitators to engagement with both tele-support psychotherapy (TSP) and standard mental health services (SMHS). To provide a comprehensive analysis of these factors, we employed the Consolidated Framework for Implementation Research (CFIR) ( 23 ). The CFIR, with its five domains (Intervention Characteristics, Outer Setting, Inner Setting, Characteristics of Individuals, and Process) allowed us to systematically categorize the barriers and facilitators identified through our survey data. These findings are presented in Tables 3 and 4, offering a structured overview of the factors influencing engagement with TSP and SMHS. Engagement with TSP and SMHS mental health interventions was influenced by various factors across multiple domains. In terms of intervention characteristics, TSP faced barriers such as long call-waiting times and occasional unintended costs, while facilitators included a toll-free platform, culturally appropriate therapy, and remote continuity of care. For SMHS, the lack of mental health providers and high transport costs posed challenges. Restrictive government policies, criminal prosecution, and societal stigma hindered access, with some participants requiring spousal approval to engage in psychotherapy sessions affected participation in either intervention. Nonetheless, informal support from friends, family, and spiritual guidance helped facilitate engagement. The inner setting presented challenges such as poor communication infrastructure, scheduling conflicts, and unreliable mobile access, though nearby counseling services and reliable communication devices improved participation. The implementation process faced outreach gaps, including missed information, leading to low attendance. Nonetheless, partnerships with trusted institutions like Makerere University improved trust, while a well-structured recruitment strategy ensured better awareness of available services. Discussion Our previous study revealed a striking disparity in engagement rates between tele-support psychotherapy (TSP) and standard mental health services (SMHS) among youth with mild to moderate depression in Kampala. A remarkable 62% of participants engaged with TSP, compared to a mere 10% who engaged with SMHS. This sparked our curiosity and led us to delve deeper into understanding the factors that influence young people's access to mental health care in this setting. This study compared facilitators and barriers to tele-support psychotherapy (TSP) and standard in-person mental health services (SMHS) for youth experiencing depression in low-resource settings, utilizing the Consolidated Framework for Implementation Research (CFIR) to guide our investigation. Our findings highlight the critical role of facilitators, particularly income and family/spousal support, in influencing engagement with both TSP and SMHS. The observation that income facilitates engagement with both service delivery models underscore the pervasive influence of socioeconomic factors on mental health access and utilization. This aligns with existing literature demonstrating the association between poverty and mental health disparities ( 38 , 39 ). For TSP, this may be attributed to the costs associated with technology, data plans, and reliable internet access, which can be prohibitive for low-income families. For SMHS, income may influence the ability to afford transportation to clinics, or time off from work. Financial barriers must be addressed to ensure equitable access to mental healthcare, regardless of the delivery model. The strong influence of family and spousal support on engagement with both TSP and SMHS emphasizes the importance of social support in mental health-seeking behavior. This resonates with previous research highlighting the protective role of social support in mitigating the impact of mental health challenges ( 40 , 41 ). Our findings suggest that individuals with strong social networks are more likely to initiate and maintain engagement with mental health services, regardless of the delivery format. This highlights the potential for leveraging social support networks in mental health interventions. Interestingly, our findings revealed that support from friends facilitated access to TSP when individuals faced challenges accessing SMHS in health facilities. The participants sought help from friends who shared information about toll-free lines or community counselors, demonstrating a proactive approach to navigating barriers. This highlights the resourcefulness of individuals seeking mental healthcare and underscores the importance of community-based resources. Furthermore, the fact that individuals sought help through various channels indicates a strong motivation to address their mental health needs. This underscores the unmet need for accessible and affordable mental health services in these settings. Policymakers should consider these findings when designing and implementing mental health programs. Investing in digital mental health interventions like TSP while simultaneously strengthening existing community-based resources and addressing socioeconomic barriers could significantly improve mental health outcomes for youth in low-resource settings. Future research should focus on developing and evaluating strategies to integrate TSP effectively within existing healthcare systems, ensuring that it complements and enhances, rather than replaces, existing services ( 42 – 44 ). These findings remind us that mental health care needs to be accessible and affordable, especially for young people in low-resource settings. By investing in digital tools like TSP, strengthening community support, and addressing financial barriers, we can make a real difference in the lives of those who need it most. We also need to keep working on ways to make TSP a seamless part of the existing mental health system, ensuring it complements and enhances existing services. A strong network of partners facilitated the provision of both TSP and SMHS. Our team included university researchers, tech experts from a digital health company, skilled clinicians from the mental health facilities (Mulago, Butabika, Naguru), government folks, and local NGOs like SEEKGSP. The academic researchers designed the study and implemented the research, while the digital health company designed and provided support for the TSP platform. The clinicians brought their expertise in mental health care, and SEEKGSP identified and trained our lay counsellors and provided ongoing support through SEEKGSP Academy( 45 ). In our experience, engaging local government officials was instrumental in navigating policy barriers and connecting with the community. This partnership integrated research, technology, and on-the-ground expertise to better serve people in need. Importantly, it helped establish a foundation of trust and collaboration – a critical factor for successful mental health initiatives in underserved settings ( 45 ). We observed that profound socioeconomic hardships made it challenging for participants to prioritize mental health care. Many lived in poverty, which created obstacles to engaging with the technology-supported program (TSP) and standard mental health services (SMHS). For example, some lacked personal phones or lost them to theft, hindering their ability to connect with counselors. Others were intermittently detained for minor offenses, leading them to miss therapy sessions. These challenges mirror known disparities in mental health care access: patients with low income are at higher risk of dropping out of treatment ( 46 ), and “digital poverty” – lack of access to phones or internet – can impede participation in technology-based interventions ( 47 ). Effectively helping people in such communities requires addressing these social challenges alongside clinical care. This might involve providing financial or logistical support, alternative means of counselor contact (e.g. community phones or in-person outreach), and advocating for policies that foster a more stable, supportive environment. Simply offering therapy is not enough; improving everyday living conditions is essential for better mental health outcomes ( 48 ). We also learned the importance of flexibility and sustained engagement. Many individuals struggled to attend sessions consistently due to work, travel, or family demands, and some discontinued therapy once they felt better. However, continuing treatment beyond initial symptom relief is crucial to fully resolve depression and prevent relapse ( 49 ). To maintain long-term engagement, mental health services must adapt to patients’ lives – for instance, by offering flexible appointment times and reinforcing the value of ongoing attendance even when symptoms improve. By making therapy more accessible and relevant to patients’ daily realities, we can bolster adherence and achieve more enduring outcomes in these vulnerable communities. Technological issues, such as platform malfunctions and dropped calls due to poor network connectivity, further hampered service delivery, emphasizing the importance of reliable technology and contingency plans. These implementation challenges underscore the need for thorough training and support for both participants and counselors, clear communication channels, robust supervision and quality control measures, and investment in reliable technology to ensure the successful delivery of mental health interventions in similar settings. Our findings echo what others have seen in similar settings. Just like Sharma et al. (2023) found in their work, we saw how important it is for people to be able to afford and access technology if they're going to use digital mental health tools ( 50 ). They also showed how vital it is to make these tools accessible to everyone, especially those who are often left behind – something that really resonated with the challenges our participants faced in accessing both TSP and SMHS. And, like Araya et al. (2021) discovered in Brazil and Peru, family and friends played a big role in helping our participants engage with therapy ( 51 ). Their research highlighted how involving families can make a real difference, which is something we also saw in our study – strong connections help people stick with mental health support, whether it's TSP or SMHS. Our study also uncovered distinct contextual challenges in Uganda, notably the disruption caused by government policies and anti-LGBTQ + legislation, demonstrating how political and social instability can significantly impact mental health care delivery, particularly digital interventions reliant on stable technological infrastructures ( 52 ). Issues such as mandatory phone registration and poor connectivity underscored practical barriers associated with digital health implementation in low- and middle-income countries (LMICs), highlighting the necessity for adaptable strategies to mitigate unforeseen disruptions ( 53 ). This study has limitations. While our qualitative approach provided rich insights, it is inherently subjective, potentially limiting the generalizability of the findings. Despite efforts to ensure thoroughness, results might not apply to different populations or settings beyond Kampala's urban slums. Additionally, although the Consolidated Framework for Implementation Research (CFIR) guided our analysis, its complexity could have obscured subtle contextual nuances ( 54 ). Further limitations include reliance on self-reported data, susceptible to biases such as recall and social desirability ( 55 ). To advance understanding of digital mental health interventions, future research should adopt broader and more rigorous designs. Investigations should encompass diverse populations and contexts, employing mixed-methods and cluster randomized controlled trials (RCTs), and integrating alternative frameworks like RE-AIM to capture comprehensive implementation outcomes ( 56 ). Prioritizing analyses of mediating mechanisms and subgroup responsiveness will clarify for whom and how tele-support psychotherapy (TSP) is most effective ( 57 ). Moreover, incorporating cost-effectiveness evaluations will be crucial for informing policy and resource allocation, ultimately enhancing mental health care accessibility and outcomes for youth in resource-constrained environments ( 58 ). Conclusion This study illuminates the multifaceted factors influencing access to tele-support psychotherapy (TSP) and standard mental health services (SMHS) for young people experiencing depression in Kampala, Uganda. Our findings emphasize the interplay of individual-level factors, such as income and social support, with broader socio-economic and policy contexts in shaping engagement with mental health services. By integrating these findings, we can inform the development of more effective and equitable mental health services, ultimately enhancing the well-being of vulnerable youth and contributing to a more just mental healthcare landscape. Declarations Consent: This study was approved by the Makerere University College of Health Sciences Research Ethics Committee and the Uganda National Council for Science and Technology. Written informed consent was obtained from all participants before enrollment. Individuals aged 15–17 years were mature or emancipated minors who provided consent independently. Participants received a financial incentive to compensate for their time and defray internet data costs. All participants consented to the use and publication of anonymized data collected during the study. References Shorey S, Ng ED, Wong CHJ. Global prevalence of depression and elevated depressive symptoms among adolescents: A systematic review and meta‐analysis. British Journal of Clinical Psychology. 2022 Jun 26;61(2):287–305. Yang C hao, Lv J jie, Kong X meng, Chu F, Li Z bin, Lu W, et al. Global, regional and national burdens of depression in adolescents and young adults aged 10–24 years, from 1990 to 2019: findings from the 2019 Global Burden of Disease study. The British Journal of Psychiatry. 2024 Aug 25;225(2):311–20. Kieling C, Buchweitz C, Caye A, Silvani J, Ameis SH, Brunoni AR, et al. Worldwide Prevalence and Disability From Mental Disorders Across Childhood and Adolescence. JAMA Psychiatry. 2024 Apr 1;81(4):347. iAHO NCD Team. Suicide in Africa: A Neglected Reality – Regional Fact Sheet [Internet]. 2022 Aug [cited 2025 Feb 25]. Available from: https://files.aho.afro.who.int/afahobckpcontainer/production/files/iAHO_Suicide_Regional_Fact_sheet_August2022.pdf Petersen I, Ssebunnya J, Bhana A, Baillie K. Lessons from case studies of integrating mental health into primary health care in South Africa and Uganda. Int J Ment Health Syst. 2011;5(1):8. Kaggwa MM, Najjuka SM, Bongomin F, Mamun MA, Griffiths MD. Prevalence of depression in Uganda: A systematic review and meta-analysis. PLoS One. 2022 Oct 20;17(10):e0276552. Kinyanda E, Woodburn P, Tugumisirize J, Kagugube J, Ndyanabangi S, Patel V. Poverty, life events and the risk for depression in Uganda. Soc Psychiatry Psychiatr Epidemiol. 2011 Jan 16;46(1):35–44. Shorey S, Ng ED, Wong CHJ. Global prevalence of depression and elevated depressive symptoms among adolescents: A systematic review and meta‐analysis. British Journal of Clinical Psychology. 2022 Jun 26;61(2):287–305. Kaggwa MM, Najjuka SM, Bongomin F, Mamun MA, Griffiths MD. Prevalence of depression in Uganda: A systematic review and meta-analysis. PLoS One. 2022 Oct 20;17(10):e0276552. Amiri S. Unemployment associated with major depression disorder and depressive symptoms: a systematic review and meta-analysis. International Journal of Occupational Safety and Ergonomics. 2022 Oct 2;28(4):2080–92. Virgolino A, Costa J, Santos O, Pereira ME, Antunes R, Ambrósio S, et al. Lost in transition: a systematic review of the association between unemployment and mental health. Journal of Mental Health. 2022 May 4;31(3):432–44. Mokona H, Yohannes K, Ayano G. Youth unemployment and mental health: prevalence and associated factors of depression among unemployed young adults in Gedeo zone, Southern Ethiopia. Int J Ment Health Syst. 2020 Dec 8;14(1):61. Magamela MR, Dzinamarira T, Hlongwa M. COVID-19 consequences on mental health: An African perspective. South African Journal of Psychiatry. 2021 Jan 11;27. Chen J, Farah N, Dong RK, Chen RZ, Xu W, Yin J, et al. Mental Health during the COVID-19 Crisis in Africa: A Systematic Review and Meta-Analysis. Int J Environ Res Public Health. 2021 Oct 10;18(20):10604. Kaggwa MM, Harms S, Mamun MA. Mental health care in Uganda. Lancet Psychiatry. 2022 Oct;9(10):766–7. Mutamba BB, Twikirize G, Ssemalulu J, Babirye R, Semakula L, Cappo D. Diagnostic pattern of mental, neurological and substance use disorders at primary health care facilities in Uganda. Int J Ment Health Syst. 2024 Jul 15;18(1):26. Watts S, Marchand A, Bouchard S, Gosselin P, Langlois F, Belleville G, et al. Telepsychotherapy for generalized anxiety disorder: Impact on the working alliance. J Psychother Integr. 2020 Jun;30(2):208–25. Wang L, Fagan C, Yu C li. Popular mental health apps (MH apps) as a complement to telepsychotherapy: Guidelines for consideration. J Psychother Integr. 2020 Jun;30(2):265–73. Ben-Zeev D, Larsen A, Attah DA, Obeng K, Beaulieu A, Asafo SM, et al. Combining mHealth Technology and Pharmacotherapy to Improve Mental Health Outcomes and Reduce Human Rights Abuses in West Africa: Intervention Field Trial. JMIR Ment Health. 2024 Mar 27;11:e53096–e53096. Dosani A, Arora H, Mazmudar S. mHealth and Perinatal Depression in Low-and Middle-Income Countries: A Scoping Review of the Literature. Int J Environ Res Public Health. 2020 Oct 21;17(20):7679. Hampshire K, Porter G, Owusu SA, Mariwah S, Abane A, Robson E, et al. Informal m-health: How are young people using mobile phones to bridge healthcare gaps in Sub-Saharan Africa? Soc Sci Med. 2015 Oct;142:90–9. Nakimuli-Mpungu E, Mutinye Kwesiga J, Mark Bwanika J, Musinguzi D, Nakanyike C, Iya J, et al. Developing and Testing Tele-Support Psychotherapy through Mobile Phones for Youth (15–30 Years) with Depression in Uganda. In: Psychotherapy - New Trends and Developments [Working Title]. IntechOpen; 2025. Damschroder LJ, Reardon CM, Widerquist MAO, Lowery J. The updated Consolidated Framework for Implementation Research based on user feedback. Implementation Science. 2022 Oct 29;17(1):75. Researching Lived Experience, Second Edition. Routledge; 2016. Laverty SM. Hermeneutic Phenomenology and Phenomenology: A Comparison of Historical and Methodological Considerations. Int J Qual Methods. 2003 Sep 1;2(3):21–35. Coles E, Anderson J, Maxwell M, Harris FM, Gray NM, Milner G, et al. The influence of contextual factors on healthcare quality improvement initiatives: a realist review. Syst Rev. 2020 Dec 26;9(1):94. Nakimuli-Mpungu E, Wamala K, Okello J, Alderman S, Odokonyero R, Mojtabai R, et al. Group support psychotherapy for depression treatment in people with HIV/AIDS in northern Uganda: a single-centre randomised controlled trial. Lancet HIV. 2015 May;2(5):e190–9. Uganda Bureau of Statistics. National Population and Housing Census 2024 – Final Report - Volume 1 (Main). Kampala; 2024. Ismail S. “Informal Settlements” a Great Threat to Uganda’s Realization of Sustainable Development: A Case Study of Slums in Kampala Capital City/Uganda. International Journal of Humanities, Arts and Social Sciences. 2020 Oct 25;6(5):195–201. Ssemugabo C, Nalinya S, Lubega GB, Ndejjo R, Musoke D. Health Risks in Our Environment: Urban Slum Youth’ Perspectives Using Photovoice in Kampala, Uganda. Sustainability. 2020 Dec 29;13(1):248. Nakimuli-Mpungu E, Mutinye KJ, Bwanika JM, Musinguzi D, CarolineNakanyike, Iya J, et al. Developing and Testing Tele-Support Psychotherapy Using Mobile Phones for Depression Among Youth in Kampala District, Uganda: Study Protocol for a Pilot Randomized Controlled Trial. 2024. Tang KC, Davis A. Critical factors in the determination of focus group size. Fam Pract. 1995;12(4):474–5. Guest G, Namey E, McKenna K. How Many Focus Groups Are Enough? Building an Evidence Base for Nonprobability Sample Sizes. Field methods. 2017 Feb 24;29(1):3–22. Hennink MM, Kaiser BN, Weber MB. What Influences Saturation? Estimating Sample Sizes in Focus Group Research. Qual Health Res. 2019 Aug 10;29(10):1483–96. Coenen M, Stamm TA, Stucki G, Cieza A. Individual interviews and focus groups in patients with rheumatoid arthritis: a comparison of two qualitative methods. Quality of Life Research. 2012 Mar 25;21(2):359–70. Rutakumwa R, Mugisha JO, Bernays S, Kabunga E, Tumwekwase G, Mbonye M, et al. Conducting in-depth interviews with and without voice recorders: a comparative analysis. Qualitative Research. 2020 Oct 7;20(5):565–81. Hill Z, Tawiah-Agyemang C, Kirkwood B, Kendall C. Are verbatim transcripts necessary in applied qualitative research: experiences from two community-based intervention trials in Ghana. Emerg Themes Epidemiol. 2022 Jun 28;19(1):5. Chang Q, Peng C, Guo Y, Cai Z, Yip PSF. Mechanisms connecting objective and subjective poverty to mental health: Serial mediation roles of negative life events and social support. Soc Sci Med. 2020 Nov;265:113308. Marbin D, Gutwinski S, Schreiter S, Heinz A. Perspectives in poverty and mental health. Front Public Health. 2022 Aug 4;10. Gariépy G, Honkaniemi H, Quesnel-Vallée A. Social support and protection from depression: systematic review of current findings in Western countries. British Journal of Psychiatry. 2016 Oct 2;209(4):284–93. Wickramaratne PJ, Yangchen T, Lepow L, Patra BG, Glicksburg B, Talati A, et al. Social connectedness as a determinant of mental health: A scoping review. PLoS One. 2022 Oct 13;17(10):e0275004. Cross SP, Nicholas J, Bell IH, Mangelsdorf S, Valentine L, Thompson A, et al. Integrating digital interventions with clinical practice in youth mental health services. Australasian Psychiatry. 2023 Jun 18;31(3):302–5. Hoffman L, Benedetto E, Huang H, Grossman E, Kaluma D, Mann Z, et al. Augmenting Mental Health in Primary Care: A 1-Year Study of Deploying Smartphone Apps in a Multi-site Primary Care/Behavioral Health Integration Program. Front Psychiatry. 2019 Feb 28;10. Naslund JA, Shidhaye R, Patel V. Digital Technology for Building Capacity of Nonspecialist Health Workers for Task Sharing and Scaling Up Mental Health Care Globally. Harv Rev Psychiatry. 2019 May;27(3):181–92. Bromley E, Figueroa C, Castillo EG, Kadkhoda F, Chung B, Miranda J, et al. Community Partnering for Behavioral Health Equity: Public Agency and Community Leaders’ Views of its Promise and Challenge. Ethn Dis. 2018 Sep 6;28(Supp):397–406. Edlund MJ, Wang PS, Berglund PA, Katz SJ, Lin E, Kessler RC. Dropping Out of Mental Health Treatment: Patterns and Predictors Among Epidemiological Survey Respondents in the United States and Ontario. American Journal of Psychiatry. 2002 May;159(5):845–51. Eisner E, Faulkner S, Allan S, Ball H, Di Basilio D, Nicholas J, et al. Barriers and Facilitators of User Engagement With Digital Mental Health Interventions for People With Psychosis or Bipolar Disorder: Systematic Review and Best-Fit Framework Synthesis. JMIR Ment Health. 2025 Jan 20;12:e65246. Allen J, Balfour R, Bell R, Marmot M. Social determinants of mental health. International Review of Psychiatry. 2014 Aug 19;26(4):392–407. Geddes JR, Carney SM, Davies C, Furukawa TA, Kupfer DJ, Frank E, et al. Relapse prevention with antidepressant drug treatment in depressive disorders: a systematic review. The Lancet. 2003 Feb;361(9358):653–61. Sharma A, Tyszka A. Understanding the Mental Health of Occupational Therapy Students During the COVID-19 Pandemic. Journal of Occupational Therapy Education. 2023 Jan 1;7(1). Araya R, Menezes PR, Claro HG, Brandt LR, Daley KL, Quayle J, et al. Effect of a Digital Intervention on Depressive Symptoms in Patients With Comorbid Hypertension or Diabetes in Brazil and Peru. JAMA. 2021 May 11;325(18):1852. Müller A, & DK. Mental health among LGBTQ+ populations in low- and middle-income countries: A review of the evidence. Glob Public Health. 2019;14(8):1139–56. Naslund JA, Shidhaye R, Patel V. Digital Technology for Building Capacity of Nonspecialist Health Workers for Task Sharing and Scaling Up Mental Health Care Globally. Harv Rev Psychiatry. 2019 May;27(3):181–92. Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implementation Science. 2009 Dec 7;4(1):50. Althubaiti A. Information bias in health research: definition, pitfalls, and adjustment methods. J Multidiscip Healthc. 2016 May;211. Glasgow RE, Vogt TM, Boles SM. Evaluating the public health impact of health promotion interventions: the RE-AIM framework. Am J Public Health. 1999 Sep;89(9):1322–7. Kazdin AE. Mediators and Mechanisms of Change in Psychotherapy Research. Annu Rev Clin Psychol. 2007 Apr 1;3(1):1–27. Patel V, Saxena S, Lund C, Thornicroft G, Baingana F, Bolton P, et al. The Lancet Commission on global mental health and sustainable development. The Lancet. 2018 Oct;392(10157):1553–98. Tables Tables 1 to 4 are available in the Supplementary Files section. Additional Declarations The authors declare no competing interests. Supplementary Files TablesBariersandFacilitatorsofTSPVsSMHS.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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-6232041","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":429176438,"identity":"b835b438-0f91-4f88-b914-6212065d4c11","order_by":0,"name":"Jeremiah Kwesiga Mutinye","email":"","orcid":"","institution":"Medical Research Council, Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine (MRC/UVRI/ LSHTM ) Research Unit, Entebbe, Uganda","correspondingAuthor":false,"prefix":"","firstName":"Jeremiah","middleName":"Kwesiga","lastName":"Mutinye","suffix":""},{"id":429176439,"identity":"af2a9e3a-9969-4c4c-9f20-7aa46be7b88c","order_by":1,"name":"JohnMark Bwanika","email":"","orcid":"","institution":"The Medical Concierge Group/Rocket Health Africa, Kampala, Uganda.","correspondingAuthor":false,"prefix":"","firstName":"JohnMark","middleName":"","lastName":"Bwanika","suffix":""},{"id":429176440,"identity":"43346ac2-96c3-494a-8379-066660c976a1","order_by":2,"name":"Davis Musingunzi","email":"","orcid":"","institution":"The Medical Concierge Group/Rocket Health Africa, Kampala, Uganda.","correspondingAuthor":false,"prefix":"","firstName":"Davis","middleName":"","lastName":"Musingunzi","suffix":""},{"id":429176441,"identity":"b2fa6b69-2cfe-4f67-9321-39a4b848e097","order_by":3,"name":"Benedict Akimana","email":"","orcid":"","institution":"Butabika National Referral Mental Hospital, Ministry of Health of Uganda, Kampala, Uganda","correspondingAuthor":false,"prefix":"","firstName":"Benedict","middleName":"","lastName":"Akimana","suffix":""},{"id":429176442,"identity":"302b869e-5ccb-4953-aa22-1fc3f0d7a451","order_by":4,"name":"Happy Banonya","email":"","orcid":"","institution":"The Medical Concierge Group/Rocket Health Africa, Kampala, Uganda.","correspondingAuthor":false,"prefix":"","firstName":"Happy","middleName":"","lastName":"Banonya","suffix":""},{"id":429176443,"identity":"f9501038-0b0d-418d-bece-53f3695a4b76","order_by":5,"name":"Brenda Kabakari","email":"","orcid":"","institution":"The Medical Concierge Group/Rocket Health Africa, Kampala, Uganda.","correspondingAuthor":false,"prefix":"","firstName":"Brenda","middleName":"","lastName":"Kabakari","suffix":""},{"id":429176444,"identity":"88b786ef-f6fe-4f33-8e43-c1ba43ac7cf8","order_by":6,"name":"Sowed Mutumba","email":"","orcid":"","institution":"The Medical Concierge Group/Rocket Health Africa, Kampala, Uganda.","correspondingAuthor":false,"prefix":"","firstName":"Sowed","middleName":"","lastName":"Mutumba","suffix":""},{"id":429176445,"identity":"55d384ee-6b50-4e05-8e95-f0df525eec27","order_by":7,"name":"Sabrina Bakeera Kitaka","email":"","orcid":"","institution":"Department of Pediatrics, College of Health Sciences, Makerere University, Kampala, Uganda","correspondingAuthor":false,"prefix":"","firstName":"Sabrina","middleName":"Bakeera","lastName":"Kitaka","suffix":""},{"id":429176446,"identity":"f87bcd3f-f947-40da-b373-793442c55e48","order_by":8,"name":"Musisi Seggane","email":"","orcid":"","institution":"Department of Psychiatry, College of Health Sciences, Makerere University, Kampala, Uganda","correspondingAuthor":false,"prefix":"","firstName":"Musisi","middleName":"","lastName":"Seggane","suffix":""},{"id":429176447,"identity":"9c689ffd-ad5a-411a-a706-ee0587406038","order_by":9,"name":"Moffat Nyirenda","email":"data:image/png;base64,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","orcid":"","institution":"Medical Research Council, Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine (MRC/UVRI/ LSHTM ) Research Unit, Entebbe, Uganda","correspondingAuthor":true,"prefix":"","firstName":"Moffat","middleName":"","lastName":"Nyirenda","suffix":""},{"id":429176448,"identity":"3bd0fa0d-ce28-409f-90dd-6796408ddf84","order_by":10,"name":"Etheldreda Nakimuli-Mpungu","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0001-6857-8931","institution":"Medical Research Council, Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine (MRC/UVRI/ LSHTM ) Research Unit, Entebbe, Uganda","correspondingAuthor":true,"prefix":"","firstName":"Etheldreda","middleName":"","lastName":"Nakimuli-Mpungu","suffix":""}],"badges":[],"createdAt":"2025-03-15 09:59:25","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":true,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6232041/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6232041/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":79730332,"identity":"2d4a8481-aeee-49b5-b659-4471b9ce95b1","added_by":"auto","created_at":"2025-04-02 05:31:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":632905,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6232041/v1/95ea047a-d3e1-4dc8-ae70-d9dd02ab46bd.pdf"},{"id":79728935,"identity":"376d826f-79ea-4b4c-8d3a-b0ecf4a2920c","added_by":"auto","created_at":"2025-04-02 05:07:53","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":32189,"visible":true,"origin":"","legend":"","description":"","filename":"TablesBariersandFacilitatorsofTSPVsSMHS.docx","url":"https://assets-eu.researchsquare.com/files/rs-6232041/v1/8519c084a6c5bcef46cd6458.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eBarriers and Facilitators to Tele-Support Psychotherapy Versus Standard In-Person Mental Health Services for Youth (15-30 Years) with Depression in Kampala District, Uganda.\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDepression remains a critical mental health challenge among youth globally, with alarming prevalence rates observed across continents (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). In Africa, the burden of mental health disorders is particularly acute, evidenced by the region's disproportionately high suicide rates and limited access to psychosocial interventions at the primary healthcare level (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Uganda, specifically, ranks among the top countries on the continent with high depression rates, a consequence of its history of conflict, high disease burden (including HIV), and persistent economic hardships (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). These factors have contributed to depression rates that exceed global averages (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe COVID-19 pandemic further exacerbated this mental health crisis, particularly among youth. Lockdown measures, social isolation, job losses, and economic uncertainty created a perfect storm for increased depression and anxiety (\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). This impact was especially pronounced in Sub-Saharan Africa (SSA), where the pooled prevalence of common mental disorders among youth was significantly higher compared to other regions (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn Kampala District, Uganda, these challenges are compounded by a severe shortage of mental health resources. The district has limited specialized mental health facilities and a critical lack of trained mental health professionals (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). This creates a substantial gap in the care of young people with depression, who often face additional barriers such as stigma, financial constraints, and geographical limitations.\u003c/p\u003e \u003cp\u003eTo address these gaps in mental health service delivery, digital interventions, particularly telepsychotherapy, have emerged as promising solutions (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). These interventions have shown potential for increasing access to mental health care, especially in resource-limited settings (\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Notably, in response to the surge in mental health problems among youth during the COVID-19 pandemic, our research team adapted group support psychotherapy into tele-support psychotherapy (TSP) via mobile phones. In a 12-month pilot study, we observed significantly higher engagement with TSP than standard mental health services (SMHS) offered at health centers. Specifically, 95 participants (61.69%) attended TSP sessions, compared to only 15 participants (10.27%) in the control arm who sought in-person treatment(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). This data demonstrates the potential of TSP to improve engagement with mental health care in resource-constrained environments.\u003c/p\u003e \u003cp\u003eHowever, despite the promising results of TSP and other tele-psychotherapy approaches, traditional in-person mental health services remain the prevalent approach to youth mental health care in Uganda. This discrepancy highlights the need to understand the factors influencing the adoption of different service delivery models. In Kampala, the specific barriers and facilitators to telepsychotherapy and in-person mental health services for youth with depression remain largely unexplored. Understanding these factors is crucial for designing and implementing effective mental health interventions that are tailored to the local context.\u003c/p\u003e \u003cp\u003eTherefore, this study aims to identify and compare the perceived barriers and facilitators to accessing telepsychotherapy and in-person mental health services among youth (\u003cspan additionalcitationids=\"CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23 CR24 CR25 CR26 CR27 CR28 CR29\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) with depression in Kampala District. We will address the following research questions: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)What are the perceived barriers and facilitators to accessing tele-psychotherapy among youth with depression in Kampala District? (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) How do these barriers and facilitators compare to those associated with in-person mental health services?\u003c/p\u003e \u003cp\u003eThe findings from this study will provide critical insights for policymakers, mental health practitioners, and researchers in designing, implementing, and scaling up mental health interventions for youth with depression in resource-limited settings.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eThis was a phenomenological community-based qualitative study that explored the experiences of youth with depression who received, and lay-counselors who provided, psychotherapy through mobile phones and/or standard in-person counseling during a randomized controlled trial (RCT) carried out in Kampala, Uganda (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). To comprehensively evaluate the implementation of tele-support psychotherapy (TSP) within this context, we employed the Consolidated Framework for Implementation Research (CFIR) (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). The CFIR is a widely used framework that guides the in-depth assessment of factors influencing the implementation of health innovations. It consists of five domains: Intervention Characteristics, Outer Setting, Inner Setting, Characteristics of Individuals, and Process (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGuided by the CFIR, this study aimed to identify and understand the multi-level factors affecting the implementation of TSP and compare them with those associated with standard mental health services (SMHS). We chose a phenomenological approach as it allows for a rich exploration of individuals' lived experiences, enabling us to gain deeper insights into the barriers and facilitators influencing the adoption and use of both TSP and SMHS (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). We anticipated that this approach would generate contextualized, evidence-based data crucial for designing and implementing effective mental health programs in similar resource-limited settings (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e)..\u003c/p\u003e \u003cp\u003eSemi-structured key informant interviews (KIIs) and focus group discussions (FGDs) were conducted between March and July 2024. The study focused on youth and emancipated minors, as they constitute over 70% of the population in urban centers in Uganda and are disproportionately affected by mental health challenges due to socioeconomic hardships and stigma.\u003c/p\u003e \u003cp\u003eThe TSP model used in this study was adapted from the Group Support Psychotherapy (GSP) model, a culturally sensitive intervention that has demonstrated effectiveness in managing depression among adults with HIV (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). To optimize GSP for remote delivery via mobile phones, we made several key modifications. These included adapting the session content and structure to maintain engagement and minimize distractions, recognizing the unique challenges of telepsychotherapy. We also developed a comprehensive training program to equip lay counselors with the skills and knowledge necessary to deliver TSP effectively, ensuring fidelity to the model while accommodating the remote format. Additionally, we integrated technology-assisted tools, such as SMS reminders and mobile-based self-help resources, to enhance participant engagement and provide support between sessions. This adapted TSP model has proven feasible for managing depression and was well-received in the communities where it was implemented (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). The utilization of lay counselors to deliver TSP further amplifies its potential to bridge the substantial mental health support human resource gap prevalent in LMICs, offering a scalable and cost-effective solution.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Setting\u003c/h3\u003e\n\u003cp\u003eThis qualitative study was conducted in three communities within Kampala, Uganda: Kamwokya, Naguru, and Makerere. These communities represent the administrative divisions of Kampala Central, Nakawa, and Kawempe, respectively. Kampala, the capital city of Uganda, is made up of five distinct geographical divisions. Kampala is the most densely populated city in the country with over 2.5\u0026nbsp;million daytime inhabitants with over 40% of these individuals staying in slums (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). These slums are at increased risk for socioeconomic and public health-related challenges such as high rates of unemployment, substance abuse, poor access to healthcare services including mental health and insecurity (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eStudy Population\u003c/h3\u003e\n\u003cp\u003e Study participants and lay-counselors (LCs) who had been assigned to receive and deliver psychotherapy respectively over mobile phones and/or standard mental health services were called for exit key-informant interviews (KIIs) and focus group discussions (FGDs). The study participants in this study were part of the 300 participants in the RCT whose details are published elsewhere (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAfter 12 months, purposive sampling was used to select the participants for the exit KIIs from participants who had completed and those who had not completed sessions in both the cases and the controls. Participants were selected from Kamwokya, Naguru, Key population and Makerere communities aged between 16\u0026ndash;30 years. The FGDs were gender-specific, ensuring both male and female perspectives were represented. Gender-specific groups allowed for open and comfortable discussions, particularly on sensitive topics like depression, stress and anxiety. These groups were designed to include 6\u0026ndash;10 participants, likely to maintain an optimal size for productive discussions (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003e The KIIs and FGDs were designed to elicit in-depth information about the participants' experiences with TSP and SMHS, guided by the CFIR domains. The interview guide was structured to explore factors related user satisfaction with both interventions, including perceived benefits, challenges, and preferences (Intervention Characteristics). We also investigated external factors influencing service utilization, such as community attitudes towards mental health and the availability of alternative services (Outer Setting). Additionally, we examined structural factors within the implementing organizations, such as resource availability and staff attitudes towards technology (Inner Setting). Individual-level factors influencing service uptake and engagement, such as technology literacy, motivation, and prior experiences with mental health care, were also considered (Characteristics of Individuals). Finally, we explored implementation-related factors, such as communication strategies, training of lay counselors, and the fidelity of intervention delivery (Process).\u003c/p\u003e \u003cp\u003eThe interviews and focused group discussions were facilitated by the study\u0026rsquo;s lead research coordinators (BH and BK). By the fourth FGD data saturation was reached with no new codes generated. However, given our groups were gender-specific we intended to have an upper limit of the number of FGDs (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) to achieve saturation as recommended by different qualitative data collection literature (\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). These focus group discussions were audio recorded, with the research assistants writing field notes for to contextualized the transcripts during the analysis. This practice has shown to improve on the interview process and the subsequent data analysis and a great supplement to the use of audio-recorded data alone (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). The audio recordings were then transcribed verbatim with the interviews in Luganda concurrently translated to English for analysis. The research assistants\u0026rsquo; coordinator, HB reviewed the transcribed interviews against the audio recordings to ensure consistency before final approval for analysis. The study participants were reimbursed with approximately 5 dollars each for their time and participation in the interviews at the end of the interviews.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eApproved transcripts from the interviews were uploaded to qualitative analysis software (MAXQDA v22.5.0). This study employed deductive thematic analysis, guided by the Consolidated Framework for Implementation Research (CFIR), to identify and categorize barriers and facilitators of TSP and SMHS. The transcripts were pre-coded based on the five CFIR domains with two coders (HB and JMK) independently reviewing the data and assigning excerpts to the relevant CFIR category. Any discrepancies were resolved through discussion with the senior researchers (JMB and EN). This structured approach ensured that findings were systematically mapped to well-established implementation science constructs, facilitating a deeper understanding of the factors influencing mental health service delivery in resource-limited settings. The use of the CFIR framework allowed for a systematic and comprehensive analysis of the barriers and facilitators to TSP and SMHS implementation. By mapping our findings to the CFIR constructs, we aimed to provide a more nuanced understanding of the factors influencing mental health service delivery in resource-limited settings, ultimately informing the development and implementation of more effective interventions.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eComparison of Baseline Characteristics between Tele-support psychotherapy (TSP) Engagers and Non-Engagers.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eNo significant differences were found between engagers and non-engagers in terms of baseline anxiety, stigma, days unable to work due to health issues, alcohol use, social support, self-esteem, social group membership, or total social resources. However, there was a marginally significant difference in monthly income (p\u0026thinsp;=\u0026thinsp;0.055), with engagers reporting higher income than non-engagers. Additionally, engagers were significantly older than non-engagers (p\u0026thinsp;=\u0026thinsp;0.008). The proportion of individuals with different education levels was similar between the two groups. However, a significantly higher proportion of engagers were employed than non-engagers (χ\u0026sup2;=5.14, p\u0026thinsp;=\u0026thinsp;0.023). Females demonstrated the highest engagement, with 76.84% attending at least one TSP session. In contrast, only 18.95% of males engaged with the intervention. Notably, LGBTQ individuals had the lowest engagement, at 4.21%. Details are shown in Table\u0026nbsp;1\u003c/p\u003e \u003cp\u003e \u003cb\u003eComparison of Baseline Characteristics between Standard Mental Health Services(SMHS) engagers and non-engagers.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA comparison of baseline characteristics between those who engaged with standard mental health services (SMHS) by attending at least one session (engagers) and those who did not (non-engagers) revealed some notable differences. While there were no significant differences in age, gender, education level, employment status, or income-generating activity, a marginally significant difference in marital status (p\u0026thinsp;=\u0026thinsp;0.073) was observed, with a trend towards a higher proportion of married individuals among engagers. Furthermore, engagers had significantly higher monthly income (p\u0026thinsp;=\u0026thinsp;0.021) and savings (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to non-Engagers. No significant differences were found between the groups in terms of total social resources, anxiety levels, perceived stigma, days unable to work due to health, alcohol use, social support, or self-esteem, although there was a trend towards higher social support among Engagers (p\u0026thinsp;=\u0026thinsp;0.076). These findings suggest that while SMHS Engagers and Non-Engagers were generally comparable on most socio-demographic and psychosocial characteristics, differences in marital status, income, and savings should be considered when interpreting the impact of SMHS engagement on treatment outcomes. Details are shown in Table\u0026nbsp;2.\u003c/p\u003e\n\u003ch3\u003eBarriers and Facilitators to Tele-Support Psychotherapy Versus In-Person Mental Health Services\u003c/h3\u003e\n\u003cp\u003eOf the 248 study participants who completed the 12-month follow-up assessments, 140 also completed the Exit survey. This survey explored barriers and facilitators to engagement with both tele-support psychotherapy (TSP) and standard mental health services (SMHS). To provide a comprehensive analysis of these factors, we employed the Consolidated Framework for Implementation Research (CFIR) (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). The CFIR, with its five domains (Intervention Characteristics, Outer Setting, Inner Setting, Characteristics of Individuals, and Process) allowed us to systematically categorize the barriers and facilitators identified through our survey data. These findings are presented in Tables\u0026nbsp;3 and 4, offering a structured overview of the factors influencing engagement with TSP and SMHS.\u003c/p\u003e \u003cp\u003eEngagement with TSP and SMHS mental health interventions was influenced by various factors across multiple domains. In terms of intervention characteristics, TSP faced barriers such as long call-waiting times and occasional unintended costs, while facilitators included a toll-free platform, culturally appropriate therapy, and remote continuity of care. For SMHS, the lack of mental health providers and high transport costs posed challenges. Restrictive government policies, criminal prosecution, and societal stigma hindered access, with some participants requiring spousal approval to engage in psychotherapy sessions affected participation in either intervention. Nonetheless, informal support from friends, family, and spiritual guidance helped facilitate engagement. The inner setting presented challenges such as poor communication infrastructure, scheduling conflicts, and unreliable mobile access, though nearby counseling services and reliable communication devices improved participation. The implementation process faced outreach gaps, including missed information, leading to low attendance. Nonetheless, partnerships with trusted institutions like Makerere University improved trust, while a well-structured recruitment strategy ensured better awareness of available services.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur previous study revealed a striking disparity in engagement rates between tele-support psychotherapy (TSP) and standard mental health services (SMHS) among youth with mild to moderate depression in Kampala. A remarkable 62% of participants engaged with TSP, compared to a mere 10% who engaged with SMHS. This sparked our curiosity and led us to delve deeper into understanding the factors that influence young people's access to mental health care in this setting.\u003c/p\u003e \u003cp\u003eThis study compared facilitators and barriers to tele-support psychotherapy (TSP) and standard in-person mental health services (SMHS) for youth experiencing depression in low-resource settings, utilizing the Consolidated Framework for Implementation Research (CFIR) to guide our investigation. Our findings highlight the critical role of facilitators, particularly income and family/spousal support, in influencing engagement with both TSP and SMHS. The observation that income facilitates engagement with both service delivery models underscore the pervasive influence of socioeconomic factors on mental health access and utilization. This aligns with existing literature demonstrating the association between poverty and mental health disparities (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). For TSP, this may be attributed to the costs associated with technology, data plans, and reliable internet access, which can be prohibitive for low-income families. For SMHS, income may influence the ability to afford transportation to clinics, or time off from work. Financial barriers must be addressed to ensure equitable access to mental healthcare, regardless of the delivery model.\u003c/p\u003e \u003cp\u003eThe strong influence of family and spousal support on engagement with both TSP and SMHS emphasizes the importance of social support in mental health-seeking behavior. This resonates with previous research highlighting the protective role of social support in mitigating the impact of mental health challenges (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Our findings suggest that individuals with strong social networks are more likely to initiate and maintain engagement with mental health services, regardless of the delivery format. This highlights the potential for leveraging social support networks in mental health interventions.\u003c/p\u003e \u003cp\u003eInterestingly, our findings revealed that support from friends facilitated access to TSP when individuals faced challenges accessing SMHS in health facilities. The participants sought help from friends who shared information about toll-free lines or community counselors, demonstrating a proactive approach to navigating barriers. This highlights the resourcefulness of individuals seeking mental healthcare and underscores the importance of community-based resources.\u003c/p\u003e \u003cp\u003eFurthermore, the fact that individuals sought help through various channels indicates a strong motivation to address their mental health needs. This underscores the unmet need for accessible and affordable mental health services in these settings. Policymakers should consider these findings when designing and implementing mental health programs. Investing in digital mental health interventions like TSP while simultaneously strengthening existing community-based resources and addressing socioeconomic barriers could significantly improve mental health outcomes for youth in low-resource settings. Future research should focus on developing and evaluating strategies to integrate TSP effectively within existing healthcare systems, ensuring that it complements and enhances, rather than replaces, existing services (\u003cspan additionalcitationids=\"CR43\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThese findings remind us that mental health care needs to be accessible and affordable, especially for young people in low-resource settings. By investing in digital tools like TSP, strengthening community support, and addressing financial barriers, we can make a real difference in the lives of those who need it most. We also need to keep working on ways to make TSP a seamless part of the existing mental health system, ensuring it complements and enhances existing services.\u003c/p\u003e \u003cp\u003eA strong network of partners facilitated the provision of both TSP and SMHS. Our team included university researchers, tech experts from a digital health company, skilled clinicians from the mental health facilities (Mulago, Butabika, Naguru), government folks, and local NGOs like SEEKGSP. The academic researchers designed the study and implemented the research, while the digital health company designed and provided support for the TSP platform. The clinicians brought their expertise in mental health care, and SEEKGSP identified and trained our lay counsellors and provided ongoing support through SEEKGSP Academy(\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e In our experience, engaging local government officials was instrumental in navigating policy barriers and connecting with the community. This partnership integrated research, technology, and on-the-ground expertise to better serve people in need. Importantly, it helped establish a foundation of trust and collaboration \u0026ndash; a critical factor for successful mental health initiatives in underserved settings (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe observed that profound socioeconomic hardships made it challenging for participants to prioritize mental health care. Many lived in poverty, which created obstacles to engaging with the technology-supported program (TSP) and standard mental health services (SMHS). For example, some lacked personal phones or lost them to theft, hindering their ability to connect with counselors. Others were intermittently detained for minor offenses, leading them to miss therapy sessions. These challenges mirror known disparities in mental health care access: patients with low income are at higher risk of dropping out of treatment (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e), and \u0026ldquo;digital poverty\u0026rdquo; \u0026ndash; lack of access to phones or internet \u0026ndash; can impede participation in technology-based interventions (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEffectively helping people in such communities requires addressing these social challenges alongside clinical care. This might involve providing financial or logistical support, alternative means of counselor contact (e.g. community phones or in-person outreach), and advocating for policies that foster a more stable, supportive environment. Simply offering therapy is not enough; improving everyday living conditions is essential for better mental health outcomes (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe also learned the importance of flexibility and sustained engagement. Many individuals struggled to attend sessions consistently due to work, travel, or family demands, and some discontinued therapy once they felt better. However, continuing treatment beyond initial symptom relief is crucial to fully resolve depression and prevent relapse (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). To maintain long-term engagement, mental health services must adapt to patients\u0026rsquo; lives \u0026ndash; for instance, by offering flexible appointment times and reinforcing the value of ongoing attendance even when symptoms improve. By making therapy more accessible and relevant to patients\u0026rsquo; daily realities, we can bolster adherence and achieve more enduring outcomes in these vulnerable communities.\u003c/p\u003e \u003cp\u003eTechnological issues, such as platform malfunctions and dropped calls due to poor network connectivity, further hampered service delivery, emphasizing the importance of reliable technology and contingency plans. These implementation challenges underscore the need for thorough training and support for both participants and counselors, clear communication channels, robust supervision and quality control measures, and investment in reliable technology to ensure the successful delivery of mental health interventions in similar settings.\u003c/p\u003e \u003cp\u003eOur findings echo what others have seen in similar settings. Just like Sharma et al. (2023) found in their work, we saw how important it is for people to be able to afford and access technology if they're going to use digital mental health tools (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e). They also showed how vital it is to make these tools accessible to everyone, especially those who are often left behind \u0026ndash; something that really resonated with the challenges our participants faced in accessing both TSP and SMHS. And, like Araya et al. (2021) discovered in Brazil and Peru, family and friends played a big role in helping our participants engage with therapy (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). Their research highlighted how involving families can make a real difference, which is something we also saw in our study \u0026ndash; strong connections help people stick with mental health support, whether it's TSP or SMHS.\u003c/p\u003e \u003cp\u003eOur study also uncovered distinct contextual challenges in Uganda, notably the disruption caused by government policies and anti-LGBTQ\u0026thinsp;+\u0026thinsp;legislation, demonstrating how political and social instability can significantly impact mental health care delivery, particularly digital interventions reliant on stable technological infrastructures (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e). Issues such as mandatory phone registration and poor connectivity underscored practical barriers associated with digital health implementation in low- and middle-income countries (LMICs), highlighting the necessity for adaptable strategies to mitigate unforeseen disruptions (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study has limitations. While our qualitative approach provided rich insights, it is inherently subjective, potentially limiting the generalizability of the findings. Despite efforts to ensure thoroughness, results might not apply to different populations or settings beyond Kampala's urban slums. Additionally, although the Consolidated Framework for Implementation Research (CFIR) guided our analysis, its complexity could have obscured subtle contextual nuances (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). Further limitations include reliance on self-reported data, susceptible to biases such as recall and social desirability (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo advance understanding of digital mental health interventions, future research should adopt broader and more rigorous designs. Investigations should encompass diverse populations and contexts, employing mixed-methods and cluster randomized controlled trials (RCTs), and integrating alternative frameworks like RE-AIM to capture comprehensive implementation outcomes (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e). Prioritizing analyses of mediating mechanisms and subgroup responsiveness will clarify for whom and how tele-support psychotherapy (TSP) is most effective (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Moreover, incorporating cost-effectiveness evaluations will be crucial for informing policy and resource allocation, ultimately enhancing mental health care accessibility and outcomes for youth in resource-constrained environments (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study illuminates the multifaceted factors influencing access to tele-support psychotherapy (TSP) and standard mental health services (SMHS) for young people experiencing depression in Kampala, Uganda. Our findings emphasize the interplay of individual-level factors, such as income and social support, with broader socio-economic and policy contexts in shaping engagement with mental health services. By integrating these findings, we can inform the development of more effective and equitable mental health services, ultimately enhancing the well-being of vulnerable youth and contributing to a more just mental healthcare landscape.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eConsent:\u003c/p\u003e\u003cp\u003eThis study was approved by the Makerere University College of Health Sciences Research Ethics Committee and the Uganda National Council for Science and Technology. Written informed consent was obtained from all participants before enrollment. Individuals aged 15–17 years were mature or emancipated minors who provided consent independently. Participants received a financial incentive to compensate for their time and defray internet data costs. All participants consented to the use and publication of anonymized data collected during the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eShorey S, Ng ED, Wong CHJ. Global prevalence of depression and elevated depressive symptoms among adolescents: A systematic review and meta‐analysis. British Journal of Clinical Psychology. 2022 Jun 26;61(2):287\u0026ndash;305. \u003c/li\u003e\n\u003cli\u003eYang C hao, Lv J jie, Kong X meng, Chu F, Li Z bin, Lu W, et al. Global, regional and national burdens of depression in adolescents and young adults aged 10\u0026ndash;24 years, from 1990 to 2019: findings from the 2019 Global Burden of Disease study. The British Journal of Psychiatry. 2024 Aug 25;225(2):311\u0026ndash;20. \u003c/li\u003e\n\u003cli\u003eKieling C, Buchweitz C, Caye A, Silvani J, Ameis SH, Brunoni AR, et al. Worldwide Prevalence and Disability From Mental Disorders Across Childhood and Adolescence. JAMA Psychiatry. 2024 Apr 1;81(4):347. \u003c/li\u003e\n\u003cli\u003eiAHO NCD Team. Suicide in Africa: A Neglected Reality \u0026ndash; Regional Fact Sheet [Internet]. 2022 Aug [cited 2025 Feb 25]. Available from: https://files.aho.afro.who.int/afahobckpcontainer/production/files/iAHO_Suicide_Regional_Fact_sheet_August2022.pdf\u003c/li\u003e\n\u003cli\u003ePetersen I, Ssebunnya J, Bhana A, Baillie K. Lessons from case studies of integrating mental health into primary health care in South Africa and Uganda. Int J Ment Health Syst. 2011;5(1):8. \u003c/li\u003e\n\u003cli\u003eKaggwa MM, Najjuka SM, Bongomin F, Mamun MA, Griffiths MD. Prevalence of depression in Uganda: A systematic review and meta-analysis. PLoS One. 2022 Oct 20;17(10):e0276552. \u003c/li\u003e\n\u003cli\u003eKinyanda E, Woodburn P, Tugumisirize J, Kagugube J, Ndyanabangi S, Patel V. Poverty, life events and the risk for depression in Uganda. Soc Psychiatry Psychiatr Epidemiol. 2011 Jan 16;46(1):35\u0026ndash;44. \u003c/li\u003e\n\u003cli\u003eShorey S, Ng ED, Wong CHJ. Global prevalence of depression and elevated depressive symptoms among adolescents: A systematic review and meta‐analysis. British Journal of Clinical Psychology. 2022 Jun 26;61(2):287\u0026ndash;305. \u003c/li\u003e\n\u003cli\u003eKaggwa MM, Najjuka SM, Bongomin F, Mamun MA, Griffiths MD. Prevalence of depression in Uganda: A systematic review and meta-analysis. PLoS One. 2022 Oct 20;17(10):e0276552. \u003c/li\u003e\n\u003cli\u003eAmiri S. Unemployment associated with major depression disorder and depressive symptoms: a systematic review and meta-analysis. International Journal of Occupational Safety and Ergonomics. 2022 Oct 2;28(4):2080\u0026ndash;92. \u003c/li\u003e\n\u003cli\u003eVirgolino A, Costa J, Santos O, Pereira ME, Antunes R, Ambr\u0026oacute;sio S, et al. Lost in transition: a systematic review of the association between unemployment and mental health. Journal of Mental Health. 2022 May 4;31(3):432\u0026ndash;44. \u003c/li\u003e\n\u003cli\u003eMokona H, Yohannes K, Ayano G. Youth unemployment and mental health: prevalence and associated factors of depression among unemployed young adults in Gedeo zone, Southern Ethiopia. Int J Ment Health Syst. 2020 Dec 8;14(1):61. \u003c/li\u003e\n\u003cli\u003eMagamela MR, Dzinamarira T, Hlongwa M. COVID-19 consequences on mental health: An African perspective. South African Journal of Psychiatry. 2021 Jan 11;27. \u003c/li\u003e\n\u003cli\u003eChen J, Farah N, Dong RK, Chen RZ, Xu W, Yin J, et al. Mental Health during the COVID-19 Crisis in Africa: A Systematic Review and Meta-Analysis. Int J Environ Res Public Health. 2021 Oct 10;18(20):10604. \u003c/li\u003e\n\u003cli\u003eKaggwa MM, Harms S, Mamun MA. Mental health care in Uganda. Lancet Psychiatry. 2022 Oct;9(10):766\u0026ndash;7. \u003c/li\u003e\n\u003cli\u003eMutamba BB, Twikirize G, Ssemalulu J, Babirye R, Semakula L, Cappo D. Diagnostic pattern of mental, neurological and substance use disorders at primary health care facilities in Uganda. Int J Ment Health Syst. 2024 Jul 15;18(1):26. \u003c/li\u003e\n\u003cli\u003eWatts S, Marchand A, Bouchard S, Gosselin P, Langlois F, Belleville G, et al. Telepsychotherapy for generalized anxiety disorder: Impact on the working alliance. J Psychother Integr. 2020 Jun;30(2):208\u0026ndash;25. \u003c/li\u003e\n\u003cli\u003eWang L, Fagan C, Yu C li. Popular mental health apps (MH apps) as a complement to telepsychotherapy: Guidelines for consideration. J Psychother Integr. 2020 Jun;30(2):265\u0026ndash;73. \u003c/li\u003e\n\u003cli\u003eBen-Zeev D, Larsen A, Attah DA, Obeng K, Beaulieu A, Asafo SM, et al. Combining mHealth Technology and Pharmacotherapy to Improve Mental Health Outcomes and Reduce Human Rights Abuses in West Africa: Intervention Field Trial. JMIR Ment Health. 2024 Mar 27;11:e53096\u0026ndash;e53096. \u003c/li\u003e\n\u003cli\u003eDosani A, Arora H, Mazmudar S. mHealth and Perinatal Depression in Low-and Middle-Income Countries: A Scoping Review of the Literature. Int J Environ Res Public Health. 2020 Oct 21;17(20):7679. \u003c/li\u003e\n\u003cli\u003eHampshire K, Porter G, Owusu SA, Mariwah S, Abane A, Robson E, et al. Informal m-health: How are young people using mobile phones to bridge healthcare gaps in Sub-Saharan Africa? Soc Sci Med. 2015 Oct;142:90\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eNakimuli-Mpungu E, Mutinye Kwesiga J, Mark Bwanika J, Musinguzi D, Nakanyike C, Iya J, et al. Developing and Testing Tele-Support Psychotherapy through Mobile Phones for Youth (15\u0026ndash;30 Years) with Depression in Uganda. In: Psychotherapy - New Trends and Developments [Working Title]. IntechOpen; 2025. \u003c/li\u003e\n\u003cli\u003eDamschroder LJ, Reardon CM, Widerquist MAO, Lowery J. The updated Consolidated Framework for Implementation Research based on user feedback. Implementation Science. 2022 Oct 29;17(1):75. \u003c/li\u003e\n\u003cli\u003eResearching Lived Experience, Second Edition. Routledge; 2016. \u003c/li\u003e\n\u003cli\u003eLaverty SM. Hermeneutic Phenomenology and Phenomenology: A Comparison of Historical and Methodological Considerations. Int J Qual Methods. 2003 Sep 1;2(3):21\u0026ndash;35. \u003c/li\u003e\n\u003cli\u003eColes E, Anderson J, Maxwell M, Harris FM, Gray NM, Milner G, et al. The influence of contextual factors on healthcare quality improvement initiatives: a realist review. Syst Rev. 2020 Dec 26;9(1):94. \u003c/li\u003e\n\u003cli\u003eNakimuli-Mpungu E, Wamala K, Okello J, Alderman S, Odokonyero R, Mojtabai R, et al. Group support psychotherapy for depression treatment in people with HIV/AIDS in northern Uganda: a single-centre randomised controlled trial. Lancet HIV. 2015 May;2(5):e190\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eUganda Bureau of Statistics. National Population and Housing Census 2024 \u0026ndash; Final Report - Volume 1 (Main). Kampala; 2024. \u003c/li\u003e\n\u003cli\u003eIsmail S. \u0026ldquo;Informal Settlements\u0026rdquo; a Great Threat to Uganda\u0026rsquo;s Realization of Sustainable Development: A Case Study of Slums in Kampala Capital City/Uganda. International Journal of Humanities, Arts and Social Sciences. 2020 Oct 25;6(5):195\u0026ndash;201. \u003c/li\u003e\n\u003cli\u003eSsemugabo C, Nalinya S, Lubega GB, Ndejjo R, Musoke D. Health Risks in Our Environment: Urban Slum Youth\u0026rsquo; Perspectives Using Photovoice in Kampala, Uganda. Sustainability. 2020 Dec 29;13(1):248. \u003c/li\u003e\n\u003cli\u003eNakimuli-Mpungu E, Mutinye KJ, Bwanika JM, Musinguzi D, CarolineNakanyike, Iya J, et al. Developing and Testing Tele-Support Psychotherapy Using Mobile Phones for Depression Among Youth in Kampala District, Uganda: Study Protocol for a Pilot Randomized Controlled Trial. 2024. \u003c/li\u003e\n\u003cli\u003eTang KC, Davis A. Critical factors in the determination of focus group size. Fam Pract. 1995;12(4):474\u0026ndash;5. \u003c/li\u003e\n\u003cli\u003eGuest G, Namey E, McKenna K. How Many Focus Groups Are Enough? Building an Evidence Base for Nonprobability Sample Sizes. Field methods. 2017 Feb 24;29(1):3\u0026ndash;22. \u003c/li\u003e\n\u003cli\u003eHennink MM, Kaiser BN, Weber MB. What Influences Saturation? Estimating Sample Sizes in Focus Group Research. Qual Health Res. 2019 Aug 10;29(10):1483\u0026ndash;96. \u003c/li\u003e\n\u003cli\u003eCoenen M, Stamm TA, Stucki G, Cieza A. Individual interviews and focus groups in patients with rheumatoid arthritis: a comparison of two qualitative methods. Quality of Life Research. 2012 Mar 25;21(2):359\u0026ndash;70. \u003c/li\u003e\n\u003cli\u003eRutakumwa R, Mugisha JO, Bernays S, Kabunga E, Tumwekwase G, Mbonye M, et al. Conducting in-depth interviews with and without voice recorders: a comparative analysis. Qualitative Research. 2020 Oct 7;20(5):565\u0026ndash;81. \u003c/li\u003e\n\u003cli\u003eHill Z, Tawiah-Agyemang C, Kirkwood B, Kendall C. Are verbatim transcripts necessary in applied qualitative research: experiences from two community-based intervention trials in Ghana. Emerg Themes Epidemiol. 2022 Jun 28;19(1):5. \u003c/li\u003e\n\u003cli\u003eChang Q, Peng C, Guo Y, Cai Z, Yip PSF. Mechanisms connecting objective and subjective poverty to mental health: Serial mediation roles of negative life events and social support. Soc Sci Med. 2020 Nov;265:113308. \u003c/li\u003e\n\u003cli\u003eMarbin D, Gutwinski S, Schreiter S, Heinz A. Perspectives in poverty and mental health. Front Public Health. 2022 Aug 4;10. \u003c/li\u003e\n\u003cli\u003eGari\u0026eacute;py G, Honkaniemi H, Quesnel-Vall\u0026eacute;e A. Social support and protection from depression: systematic review of current findings in Western countries. British Journal of Psychiatry. 2016 Oct 2;209(4):284\u0026ndash;93. \u003c/li\u003e\n\u003cli\u003eWickramaratne PJ, Yangchen T, Lepow L, Patra BG, Glicksburg B, Talati A, et al. Social connectedness as a determinant of mental health: A scoping review. PLoS One. 2022 Oct 13;17(10):e0275004. \u003c/li\u003e\n\u003cli\u003eCross SP, Nicholas J, Bell IH, Mangelsdorf S, Valentine L, Thompson A, et al. Integrating digital interventions with clinical practice in youth mental health services. Australasian Psychiatry. 2023 Jun 18;31(3):302\u0026ndash;5. \u003c/li\u003e\n\u003cli\u003eHoffman L, Benedetto E, Huang H, Grossman E, Kaluma D, Mann Z, et al. Augmenting Mental Health in Primary Care: A 1-Year Study of Deploying Smartphone Apps in a Multi-site Primary Care/Behavioral Health Integration Program. Front Psychiatry. 2019 Feb 28;10. \u003c/li\u003e\n\u003cli\u003eNaslund JA, Shidhaye R, Patel V. Digital Technology for Building Capacity of Nonspecialist Health Workers for Task Sharing and Scaling Up Mental Health Care Globally. Harv Rev Psychiatry. 2019 May;27(3):181\u0026ndash;92. \u003c/li\u003e\n\u003cli\u003eBromley E, Figueroa C, Castillo EG, Kadkhoda F, Chung B, Miranda J, et al. Community Partnering for Behavioral Health Equity: Public Agency and Community Leaders\u0026rsquo; Views of its Promise and Challenge. Ethn Dis. 2018 Sep 6;28(Supp):397\u0026ndash;406. \u003c/li\u003e\n\u003cli\u003eEdlund MJ, Wang PS, Berglund PA, Katz SJ, Lin E, Kessler RC. Dropping Out of Mental Health Treatment: Patterns and Predictors Among Epidemiological Survey Respondents in the United States and Ontario. American Journal of Psychiatry. 2002 May;159(5):845\u0026ndash;51. \u003c/li\u003e\n\u003cli\u003eEisner E, Faulkner S, Allan S, Ball H, Di Basilio D, Nicholas J, et al. Barriers and Facilitators of User Engagement With Digital Mental Health Interventions for People With Psychosis or Bipolar Disorder: Systematic Review and Best-Fit Framework Synthesis. JMIR Ment Health. 2025 Jan 20;12:e65246. \u003c/li\u003e\n\u003cli\u003eAllen J, Balfour R, Bell R, Marmot M. Social determinants of mental health. International Review of Psychiatry. 2014 Aug 19;26(4):392\u0026ndash;407. \u003c/li\u003e\n\u003cli\u003eGeddes JR, Carney SM, Davies C, Furukawa TA, Kupfer DJ, Frank E, et al. Relapse prevention with antidepressant drug treatment in depressive disorders: a systematic review. The Lancet. 2003 Feb;361(9358):653\u0026ndash;61. \u003c/li\u003e\n\u003cli\u003eSharma A, Tyszka A. Understanding the Mental Health of Occupational Therapy Students During the COVID-19 Pandemic. Journal of Occupational Therapy Education. 2023 Jan 1;7(1). \u003c/li\u003e\n\u003cli\u003eAraya R, Menezes PR, Claro HG, Brandt LR, Daley KL, Quayle J, et al. Effect of a Digital Intervention on Depressive Symptoms in Patients With Comorbid Hypertension or Diabetes in Brazil and Peru. JAMA. 2021 May 11;325(18):1852. \u003c/li\u003e\n\u003cli\u003eM\u0026uuml;ller A, \u0026amp; DK. Mental health among LGBTQ+ populations in low- and middle-income countries: A review of the evidence. Glob Public Health. 2019;14(8):1139\u0026ndash;56. \u003c/li\u003e\n\u003cli\u003eNaslund JA, Shidhaye R, Patel V. Digital Technology for Building Capacity of Nonspecialist Health Workers for Task Sharing and Scaling Up Mental Health Care Globally. Harv Rev Psychiatry. 2019 May;27(3):181\u0026ndash;92. \u003c/li\u003e\n\u003cli\u003eDamschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implementation Science. 2009 Dec 7;4(1):50. \u003c/li\u003e\n\u003cli\u003eAlthubaiti A. Information bias in health research: definition, pitfalls, and adjustment methods. J Multidiscip Healthc. 2016 May;211. \u003c/li\u003e\n\u003cli\u003eGlasgow RE, Vogt TM, Boles SM. Evaluating the public health impact of health promotion interventions: the RE-AIM framework. Am J Public Health. 1999 Sep;89(9):1322\u0026ndash;7. \u003c/li\u003e\n\u003cli\u003eKazdin AE. Mediators and Mechanisms of Change in Psychotherapy Research. Annu Rev Clin Psychol. 2007 Apr 1;3(1):1\u0026ndash;27. \u003c/li\u003e\n\u003cli\u003ePatel V, Saxena S, Lund C, Thornicroft G, Baingana F, Bolton P, et al. The Lancet Commission on global mental health and sustainable development. The Lancet. 2018 Oct;392(10157):1553\u0026ndash;98. \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 4 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"ab985a59-b9ad-41b4-825c-15b7a2fa7a39","identifier":"10.13039/100000200","name":"United States Agency for International Development","awardNumber":"7200AA21FA00017 ","order_by":0}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"MRC/UVRI/LSHTM Uganda Research Unit","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":"","lastPublishedDoi":"10.21203/rs.3.rs-6232041/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6232041/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Depression remains a critical mental health challenge among young people in low-resource settings, where financial, structural, and social barriers frequently limit care access. Digital approaches, including tele-support psychotherapy (TSP), have emerged as promising, scalable alternatives to standard in-person mental health services (SMHS); however, comparative insights into their relative strengths and limitations remain scarce.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e This study sought to identify and compare facilitators and barriers influencing youth engagement with TSP versus SMHS for depression treatment in Kampala District, Uganda.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We conducted a qualitative phenomenological investigation involving youth aged 15–30 enrolled in a randomized controlled trial evaluating both interventions. Data were gathered through semi-structured key informant interviews and focus groups with participants and lay counselors, and analyzed via inductive thematic analysis\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Among 154 participants assigned to TSP, 95 engaged with the tele-psychotherapy call platform, compared to only 15 out of 146 in the SMHS group. This disparity in engagement underscores the potential of TSP to improve access to mental health care. Key facilitators for both interventions included strong social support networks and higher income levels, highlighting the crucial interplay of individual and systemic factors. Technological challenges, such as unreliable communication, hindered TSP, while high costs and limited awareness were barriers to SMHS. Government policies played a dual role, fostering trust in digital interventions while inadvertently limiting access for some. Lay counselor attributes, including flexibility and rapport-building skills, were critical facilitators.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e TSP presents a viable alternative to SMHS, particularly for youth facing financial and logistical barriers. However, optimizing its delivery requires addressing technological constraints, ensuring consistent government support, and integrating mental health literacy initiatives. Findings underscore the need for flexible and contextually tailored models that leverage technology and address individual and systemic barriers to enhance mental health service access in resource-constrained settings.\u003c/p\u003e","manuscriptTitle":"Barriers and Facilitators to Tele-Support Psychotherapy Versus Standard In-Person Mental Health Services for Youth (15-30 Years) with Depression in Kampala District, Uganda.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-02 05:07:48","doi":"10.21203/rs.3.rs-6232041/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":"fbc2b14f-5a72-43bf-b793-2e3a05676c21","owner":[],"postedDate":"April 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":45719282,"name":"Psychology"},{"id":45719283,"name":"Psychiatry"}],"tags":[],"updatedAt":"2025-04-02T05:07:48+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-02 05:07:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6232041","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6232041","identity":"rs-6232041","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}