Transforming Noncommunicable Disease Services in Low- and Middle-Income countries: a Scoping Review

Transforming Noncommunicable Disease Services in Low- and Middle-Income countries: a Scoping Review | 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 Systematic Review Transforming Noncommunicable Disease Services in Low- and Middle-Income countries: a Scoping Review Aklilu Endalamaw, Yihalem Abebe Belay, Esiknder Wolka, Anteneh Zewdie, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6173948/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background : Understanding thepreferences, values, and needs of patients regarding what, where, when, and by whom comprehensive healthcare services provided is essential to improve utilization. This is especially critical among people requiring long-term care. There is a need to synthesise the available evidence on clients’ preference for noncommunicable diseases (NCDs) management. We conducted this scoping review to identify clients’ preferences for NCD-related services at the primary healthcare (PHC) level in low- and middle-income countries (LMICs). Methods: A scoping review was conducted based on the Preferred Reporting Items for Systematic Review and Meta-analysis extension for scoping review. The included data sources were articles conducted by using discrete choice experiment among clients with NCDs at PHC levels. The analysis was guided by the Differentiated Service Delivery Framework, with the main findings analyzed using what, who, where, when, and how of service provision. Results : Twenty-seven articles from nine LMICs were included. The most frequent attributes were cost, accessibility to PHC settings (distance or travel time), continuity of care (e.g., friendly provider), waiting time to receive care, availability of equipment or medication, frequency of institution visit, health worker (e.g., level of expertise and gender), and treatment type (modern versus traditional care, particularly in China). Telemedicine use and date of services were rarely used. Clients preferred a model of care with lower cost, nearby facilities, friendly providers, shorter waiting times, less frequent follow-ups, individual provider visits instead of group therapy, and care provided by better educated and culturally tailored health workers, with settings and dates or times varying due to service variations. Conclusions : This scoping review highlights the importance of understanding clients’ preferences for NCD services at PHC levels in LMICs. Preferred attributes could be integrated into chronic care models to satisfy clients’ needs in response to dynamic population characteristics, emerging pandemics, and growing technologies. The date and telecommunication use could be better adapted besides the mostly agreed and practiced care model elements, such as lower costs, nearby facilities, friendly providers, shorter waiting times, and individualized visits. Service settings and timing were shown to vary based on the type of service and disease, with clients prioritizing specific attributes within each care continuum. Clinical Trail Number : Not applicable Non-communicable disease Preference Client Service Low- and middle-income countries Figures Figure 1 Figure 2 Background Noncommunicable diseases (NCDs) cause a growing burden on the global communities. It causes 41 million overall and 17 million premature deaths annually ( 1 ), mainly due to cardiovascular diseases (17.9 million deaths), cancers (9.3 million deaths), chronic respiratory diseases (4.1 million deaths), and diabetes mellitus (DM) (2 million deaths) ( 1 ). The proportion of deaths attributed to these diseases increased from 80% in 2002 to 88.5% in 2019 ( 2 ). This burden is rapidly increased in low-and middle-income countries (LMICs), with a record of 73% of all deaths due to NCDs and 82% of all NCDs-related premature deaths in 2021( 3 ). Tobacco use, excessive alcohol consumption, unhealthy diets, and physical inactivity largely contribute to the increasing premature mortality ( 4 ). Tobacco use accounts for over 8 million deaths annually with 80% to world’s tobacco users live in LMICs ( 5 , 6 ). An estimated 1.8 million annual deaths are associated with excess sodium intake ( 5 ). Alcohol consumption and drug use accounts to more than half of the 3 million annual deaths, and insufficient physical activity contributes to 0.83 million deaths ( 5 ). Primary health care (PHC) is a whole-of-society approach to revitalize and realize NCDs-related best buys to reduce the burdens from these diseases ( 7 – 9 ). These approaches involve the private sectors, civil societies, and political decision-makers, and engage clients with a focus on contextualization, equity, transparency, respect, and inclusivity ( 10 , 11 ). The call for reduction of premature mortality due to NCDs by a third revolves around preventing the underlying causes and healthcare interventions ( 12 , 13 ). Primary health care can engage in promoting healthy lifestyle choices, implementing tobacco control policies, advocating for access to early detection, and providing curative care ( 14 , 15 ). Adaptation and implementation of ‘best buys’ for NCDs is possible with sustainable a whole-of-society and whole-of-government approaches ( 11 ), including financing, behavioral interventions, equity, integration, capacity building, and institutionalization ( 10 ). Entertaining clients’ preferences is crucial to provide person-centred care. Patient preferences are the choices and values that clients have regarding what, how, who, and when healthcare services are provided ( 16 ). Considering clients’ choices is essential to overcome a range of individual, interpersonal, societal, and organizational factors that influence preference and willingness to receive NCD services ( 17 ). There have been other challenges, such as poor community engagement ( 18 ), clients’ low adherence to treatment ( 19 ), higher lost follow-up from care ( 20 ), and cultures or traditions ( 21 ), barred NCDs-related services. These can be addressed by providing tailored care to their preferences. Considering clients’ preferences in healthcare results in greater satisfaction, higher treatment completion rates, and better clinical outcomes ( 22 ). This implies the necessity of developing a model of care based on the preferences, values, and needs of the patients to effectively implement treatment plans and care decisions ( 23 ). It is essential to understand clients’ preference due to the dynamic and changing health system that is constantly evolving and adapting to new technologies, health policies, healthcare landscapes. Understanding patient preferences regarding what, where, when, and by whom healthcare services are provided plays a critical role in tailoring care to patient needs ( 24 ). This aligns with differentiated service delivery (DSD) model ( 25 , 26 ). There is a need present clients’ preference in receiving NCDs services that tailored according to to the DSD model in LMICs settings. Evidence from this review will support the preparation and initiation of models of care for NCDs prevention and management. Therefore, we conducted this scoping review to identify the clients’ preferences for NCDs- related services at PHC level in LMICs. The study will provide a list of attributes and preferences to inform the adoption or development of new care models for NCDs management. Methods Reporting We followed Arksey and O’Malley’s guide on how to conduct a scoping review. They underscored five stages in conducting a scoping review: identifying the research question, identifying relevant studies, selecting studies, charting the data, and collating, summarizing and reporting the results ( 27 ). Identifying the research question The research question was to answer the health service delivery preference of clients with chronic diseases at PHC settings. Differentiated service delivery model was used to guide the current scoping review ( 25 ). This model is a client-centred care model used to understand what, how, where, who, and when of health care services are provided. It aims to tailor to the preferences and expectations of clients, care givers, and health workers in managing chronic diseases as care recipients and providers. There are essential building blocks to ensure the functionality of DSD: types of services or attributes, indicating the available, needed, or provided service attributes; the time, date or frequency of services provision; the health workers who provides the services, including level of education, expertise status, or experience; and the location or settings where the services are provided. It is assumed that clients needing chronic diseases services prefer one or more of the service attributes in each building block. We adapted the existing DSD model of care by adding the ‘how’ element. This element represents the methods or mechanisms through which services should be delivered to the clients by appropriate healthcare workers at the convenient location and on preferred dates. We also considered clients’ sociodemographic characteristics and health condition to understand how their backgrounds influence their own preferences for service delivery-related attributes. The DSD model will be integrated continuum of care. The continuum of care in PHC encompasses the range of services from health promotion to palliative care ( 28 ) (Fig. 1 ). Identifying relevant studies We included published articles from medical databases, including PubMed, EMBASE, Web of Science, and Scopus. We also searched articles from Google Scholar by writing the eligible articles from the databases into the Google Scholar search interface and clicking the ‘cited by’ button to list articles that cited the original articles, assuming these may be related to them, as Google Scholar does not have advanced search strategy method. The search strategy was guided by Population, Concept, and Context (PCC) framework ( 29 ). Studies that addressed all individuals with chronic non-communicable diseases regardless of age, gender, and other demographic and clinical characteristics were included. Attributes of services with the clients’ preferences, identified by discrete choice experiment, are the main concept of the review. We gave emphasis for studies that were conducted only using DCE, which identified preferences through simulating real-world decision making and clients are asked to choose between sets of alternatives in identifying the relative importance of each attribute. Discrete choice experiment also provides the willingness of clients to trade off one attribute for another, uses experimental design that provides lists of attributes and levels, and offers essential preferences amongst the examined several hypothetical preferences. The search strategies were based on keywords and/or phrases-related to DCE and non-communicable diseases. To illustrate, the key terms were “discrete choice experiment”, “discrete-choice experiment”, “noncommunicable disease”, “non communicable disease”, “non-communicable disease”, “chronic disease”, “chronic lifelong condition”, “chronic life long condition”, “chronic life-long condition”, “cardiovascular disease”, cancer, “chronic respiratory disease”, “COPD”, “diabetes”, “mental health problem”, and “NCD”. Regarding the context, studies from low- and middle-income countries (low, lower-middle- and upper-middle-income countries) conducted in PHC settings were considered. However, we did not restrict the search strategy by including the phrase “primary health care”, as most studies might not mention it, even though the study was conducted in clinics and health centres, or services were provided by PHC workers. The Boolean operators (OR, AND, and *) were used to expand and/or limit searches when needed. In general, we included articles on NCDs, conducted using DCE design, and published in English at anytime and anywhere. The last search date for databases was on October 23, 2024. The search strategy for each database is presented in the supplementary file (Supplementary file 1-search strategy). Selecting relevant studies We screened the relevant studies after thoroughly finding relevant articles and exporting them to EndNote 20 software ( 30 ). We first removed duplicates, followed by title and abstract screening. Titles and abstracts unrelated to NCDs, non-English articles, non-DCE articles, and studies not related to services in PHC settings were excluded. We also excluded other types of studies, such as cross-sectional, case control, and cohort studies conducted without DCE. Only studies involving clients were considered eligible. During the screening of irrelevant articles and inclusion of eligible ones, we held weekly meetings from the conception of the research question until the manuscript was prepared and submitted to the journal. In the meantime, we developed familiarity with the literature and were able to easily identify relevant and irrelevant articles, including those studies that were unclear from the abstract and required full article review. Hence, as abstracts do not represent the full-text ( 31 ), we reviewed all articles that passed the abstract screening phase during the full-text review. Charting the data Characteristics of articles and findings were extracted from the eligible articles. We used Microsoft Excel 2010 to record extracted data. Authors, year of publication, country, study population, research approach, sample size, disease category, services, attributes, preference, and sociodemographic and clinical factors influencing clients’ preferences were extracted. Collating, Summarizing and Reporting the Results This section mainly focuses on the synthesis of the findings. After we extracted the findings, iterative synthesis was conducted. The pre-identified framework guided the analysis to group the synthesized evidence. The information obtained from the articles was categorized into themes or key areas, such as study characteristics, attributes, and preferences. The analysis was guided by the DSD framework. The preferences were grouped according to the ‘who’, ‘when’, ‘where’, and ‘how’ questions of service delivery. The findings are presented with figure, texts, and tables. Results Search results We found a total of 1,154 records from EMBASE, 928 from SCOPUS, 731 from PubMed, and 372 from Web of Science. We also reviewed 123 articles from Google Scholar, resulting in a total of 3,308 articles. A total of 1,466 articles were eligible for title and abstract screening after removal of duplicates. Then, 346 were eligible for full-text review. With the focus to include studies from low- and middle-income countries conducted in PHC settings or on PHC services, only 27 articles were included (Figure 2). Characteristics of the studies Discrete choice analysis was employed to identify the service or medication preferences of individuals with chronic diseases (32-38). For example, it was used to identify clients’ preferences for screening services (34, 39-41), and comprehensive PHC services (33, 35-37, 39, 40, 42). The services include rescue medications for pain (43), HPV vaccination (41, 44), cervical cancer screening (CCS) (45, 46), early detection interventions for breast cancer (43), rectal cancer screening (38, 47), and follow‑up care (48). Preferences were also identified for DM, such as overall DM care (49), screening strategies of gestational DM (50, 51), and antidiabetic drugs (38, 40, 51-53). Preferences for antipsychotic medications for schizophrenia (51, 54) and epilepsy (39), hypertension-related services (55, 56), and healthcare-seeking decisions for individuals with HTN and DM (57) were identified. The study participants were adults of both sexes in most studies (33-40, 42, 43, 47-49, 51-53, 55-57), women (45, 46, 50, 58), parents of 12 to 16 years of age (44), adults 18 to 35 years of age and their caregivers (54), and community members of aged ten-years and above (41). A varying number of participants fall between 134 (43) and 3,327 (53) from different low- and middle-income countries, mostly from China (33, 35-40, 42-45, 48-51, 53, 54, 56), two from Malawi (55, 58), and one each from Nigeria (41), Argentina and Mexico (52), Sri Lanka (34), Uganda (57), South Africa (46), and Iran (47) (Table 1). Clients’ Preference for Primary Health Care Services in Chronic Diseases Management Services investigated to identify clients’ preferences were related to disease prevention (screening and vaccination), treatment, and rehabilitation care. Leadership and governance, health workforce, supplies and equipment, and infrastructure-related attributes were related to the ‘who’, ‘where’ and ‘how’ of the DSD care model. Who : Clients preferred care provided by physician or specialists (experts) (36, 48, 58) or senior care provider (33, 35, 37), and female health workers (58). Where : Clients preferred different location for the services, like community health gathering (58), workplace screening (34), screening location (town/lowest level of administration/ and village/community/ over country/highest level of administration/site) (45), static clinic over mobile clinic (46), home (47), and family planning (FP) clinic for breast cancer (BCa) screening (58). Remote communication outside clinic visits for follow-up care was also preferred (48). When : This includes fewer frequency of institution visit or longer gap between visits (45, 47, 48, 50), same day time of testing and treatment with diagnosis (46), and different access time (Saturday for urban and weekdays morning for estate sectors, all other time for rural sectors) (34), and adequate days before referral (4 days than 0 days) (49). How : Attributes related to cost were the most common tested and preferred, with clients’ preference were lower out-of-pocket costs (33-36, 42, 45-47, 50, 54, 56, 57), shorter travel time or nearest facility (33, 36, 37, 42, 55-58), continuity of care (e.g., friendly provider) (34, 42, 48, 49, 55-57), shorter waiting time (34, 45, 46, 50, 55, 56), facility with sufficient equipment and medication (42, 49, 55, 57), modern medicine service & integrated service over traditional medicine (33, 35, 36), and seeing by a provider alone than group therapy (55) (Table 2). Heterogeneity in preferences with clients-related characteristics Clients’ preference on how the services should be accessed, delivered, and overall experiences are varied based on sociodemographic and clinical status of clients (Table 3). Proposed model of care A model of care with lower cost, nearby facilities, friendly providers, shorter waiting times, less frequent follow-ups, individual provider visits instead of group therapy, and care provided by better-educated health workers, with settings and dates or times varying due to service variations. To provide specific example, a model of care provided by the same specialist person, with personalized plan and self-initiated remote counselling is preferred to follow-up care for clients with cancer (48). Women preferred free services, same-day testing and treatment, and provider-collected swabs for CCS in South Africa (46) (Table 4). Discussion This scoping review presents the clients’ preference for NCDs services in LMICs. A model of care that offers lower costs, nearby facilities, friendly providers, shorter waiting times, less frequent follow-ups, individual provider visits instead of group therapy (e.g., for hypertension care), and care provided by better-educated health workers was the most preferred. The settings and dates for the service provision vary due to service and disease differences. Clients’ preferences in receiving care for NCDs mostly pertain to the process aspects of PHC, which revolve around the ‘how’ dimensions of the DSD framework. One can argue that the PHC approach comprises most of the attributes, as it includes health system inputs, processes, outputs, and impacts ( 59 ). The health workforce is an essential input of PHC, representing the 'who' elements in the DSD framework. Clients prefer different types of care providers. Women, for example, prefer female over male providers and any provider over themselves to collect vaginal sample for CCS. Women preferred female frontline health workers at PHC level for maternal and neonatal services ( 60 ). It has been recommended to increase acceptability of male workers especially in the presence of few health workers ( 60 ). Clients’ preference for swab sampling seems unwanted by health system, as WHO estimated self-sampling can help reach the global target of 70% coverage of screening by 2030; self-sampling nearly doubled use of cervical cancer screening services ( 61 ). Self-sampling is also seen as cost effective, comfortable, safe, and user friendly ( 61 ), but women preferred provider swab in South Africa ( 46 ). Self-sampling is highly preferred in high-income countries. For instance, 95% of women attending clinic preferred self-sampling for CCS in UK ( 62 ). Globally, only 17 countries (three from Africa: Kenya, Uganda, and Rwanda) with identified screening programs recommend HPV self-sampling ( 63 ). It may also be important to consider community members’ preferences in relation to community health workers. Clients generally view them as having made a significant contribution to enhancing satisfaction, improving health status, and increasing health awareness in Ethiopia ( 64 ), while others place less trust in them due to their limited competence in handling certain services ( 65 , 66 ). According to the ‘where’ dimension of the DSD framework, the preferred locations for NCDs screening were home-based for CRC, workplace settings for general NCDs and cervical cancer, static clinics over mobile clinics for CCS, and family planning clinics for BCa. These settings are primarily based on screening, which implies that clients are likely to be in good health when accessing these services. It is important to consider the evolving needs arising from advanced health technologies and demographic changes (such as increased old age). Providing a combination of services comprising continuity of care, an individualized care plan, remote contact incorporating regular calls and counselling, and additional services (medication instructions or psychology support) could increase the acceptability of PHC services ( 48 ). Integrating health technology may determine the ‘where’ of services. Only one study considered the HIT attributes, and clients preferred remote communication for follow-up care outside of clinic visits. There are various attributes to be integrated, such as websites, mobile or tablet apps, electronic prescriptions, messaging between clinicians and patients, educational platforms, telemonitoring, multichannel centers, wearable devices or sensors, health apps, and artificial intelligence ( 67 ). According to a study in high-income countries (in Australia), consumers value the availability of telehealth and having flexibility to use telehealth when appropriate, but do not want to see telehealth replacing face-to-face delivery when physical examination was required ( 68 ). In the USA, among the general clients, one-third preferred a telehealth visit to a traditional in-person visit ( 69 ). Health technology assessment is one of the attributes for the systematic integration of patient preferences ( 16 ). Primary health care services need to be provided on the appropriate date and at the assigned time. Few studies have addressed the ‘when’ dimension of DSD. As clients prefer not to wait long for services and want to restrict frequent visits, and they favored same-day screening and treatment. However, women will undergo screening and take treatment at a return visit if services were free and the swab was collected by the provider ( 46 ). It is important to reorient PHC systems regarding the timing of certain chronic disease-related services, especially health education, mass screening, and immunization campaigns, to when community members are available or come to service areas. This includes considering when people are at home, when schools are closed, when church programs are available, market days, or specific seasons. In general, context-based care model with some-specificity is relevant. Clients’ preference could be integrated with the existing model of care. Wagner Chronic Care model links between acute settings, community services, specialist care, and self-management support via collaboration ( 70 ). There is another collaborative care model comprising self-management support, decision support, delivery system design, clinical information system, health system/organizational support, community support, case management, and family support. Each element needs to be seen into a very specific attribute. For instance, self-management support comprises essential components: patient education programmes, training for healthcare providers, awareness raising, accessibility, and technology use, with these components have also several alternatives ( 71 ). Preferences vary based on the service types: early screening and diagnosis, vaccination, medication, and treatment. Designing care model is prompting to people-centered care, focuses on the needs of people and communities by engaging people and make them more active in their care, shifting away from health systems designed around diseases and health institutions towards health systems designed for people ( 72 ). WHO has proposed strategies in implementing people-centered care: empowering and engaging people and communities; strengthening governance and accountability; reorienting the model of care; coordinating services within and across sectors; and creating an enabling environment ( 72 ). Models of care need to meet the clients’ life course demands and fulfills their preferences, which may vary depending on clients’ social class and clinical status. Designing care model for elders may give more emphasis to make services more accessible though this attribute is preferred by most clients, elders preferred nearby facility ( 42 , 55 , 56 ) more importantly, such as community health centers ( 49 ) and community-based vaccine provision than school ( 41 ). In the developed world, there have been elderly-specific model of care aimed at reaching them in the community or at their home. For instance, all-inclusive care for the elderly ( 73 ). Patients with higher health-related quality of life paid more attention to healthcare services that contributed to good treatment effects ( 56 ). For conditions perceived as minor, patients’ preferences were valued in the following order: treatment measures, travel time, and care provider. For conditions perceived as severe, clients’ preferences were ranked as follows: treatment measures, care provider, and type of service ( 33 ). As to research implications, the available articles on clients’ preferences were limited to nine LMICs, even though many other countries have NCD programs and adopt WHO treatment guidelines. Most studies were conducted in China. More research is needed in other low-income countries with a higher burden of NCDs but low service accessibility and coverage. For instance, there were no studies in Ethiopia, where in 2019, the incidence rate was 190,000 incidence was recorded ( 74 ), and only 8% of facilities provided all four NCD services ( 75 ). The continuum of care was partly addressed on disease prevention, treatment, and few on rehabilitation care. It is essential to understand clients’ preference on by whom, where, and how health promotion services provided. Attributes related to community engagement and multisectoral actions were not addressed. Eliciting clients’ or community members’ preference may be essential revolving the principles of community engagement: trust, accessibility, contextualization, equity, transparency, and autonomy ( 76 ). In multi-sectoral action, clients’ or stakeholders’ preference to identify which level of coordination is essential. The continuum of coordination begins from networking, coordinating, cooperating, collaborating, and integrating ( 77 ). Conclusions This scoping review highlights the key preferences of clients regarding NCD services in LMICs, emphasizing affordability, accessibility, friendly providers, shorter waiting times, individualized care, and the expertise of health workers. Preferences varied based on service type, disease condition, and social factors, with specific expectations for the who, where, when, and how of care delivery. While many clients prioritized provider-led services, self-sampling and telemedicine were underutilized, despite their potential benefits. Aligning PHC models with these preferences is essential for improving service utilization and patient satisfaction. A context-based, people-centered approach that integrates health technologies, community engagement, and flexible service delivery is crucial. Additionally, health systems should address gaps in rehabilitative and palliative care while ensuring comprehensive NCD management. Further research is needed in diverse LMICs, particularly in countries with high NCD burdens but limited access to services. By incorporating patient preferences into healthcare planning, PHC systems can enhance effectiveness, equity, and long-term health outcomes. Declarations Ethics approval and consent to participate: Not applicable because the review was dependent on published articles. Consent for publication : Not applicable. Availability of data and materials: The data used during the current study are available in this manuscript and/or the supplementary file. Conflicting interests : The authors declared no conflict of interest. Funding : Authors have no received fund to conduct this specific review Authors’ contributions : YA and AE conceptualised the project. AE extracted data, write the first draft and subsequent revision. YA supervised the whole research process. YAB cross-checked the data. YAB, AZ and EW revised the manuscript. All the authors approved the final manuscript. Acknowledgements: Not applicable. References World Health Organization. Noncommunicable diseases. 16 Sept 2023. Available from: https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases. Peng W, Chen S, Chen X, Ma Y, Wang T, Sun X, et al. Trends in major non-communicable diseases and related risk factors in China 2002–2019: an analysis of nationally representative survey data. The Lancet Regional Health–Western Pacific. 2024;43. World Health Organization. Noncommunicable diseases Geneva: World Health Organization,; [updated Dec 24, 2024; cited 2025 Feb 09]. Available from: https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases#:~:text=Noncommunicable%20diseases%20(NCDs)%20killed%20at,disease%20deaths%20caused%20by%20diabetes). United Nations. Political declaration of the High-level Meeting of the General Assembly on the Prevention and Control of Non-communicable Diseases. A/66/L.1. 16 Sept 2011. Available from: https://undocs.org/A/66/L.1. Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2019 (GBD 2019) Results. 2020. Institute for Health Metrics and Evaluation (IHME). Available from: https://vizhub.healthdata.org/gbd-results/. World Health Organization. Tobacco: Key facts Geneva: World Health Organization; [updated Jul 23, 2023; cited 2025 Feb 09]. Available from: https://www.who.int/news-room/fact-sheets/detail/tobacco. Endalamaw A, Zewdie A, Wolka E, Assefa Y. Care models for individuals with chronic multimorbidity: lessons for low-and middle-income countries. BMC health services research. 2024;24(1):895. World Health Organization. Primary health care. Geneva: World Health Organization; [cited 2024 Dec 20]. Available from: https://www.who.int/health-topics/primary-health-care#tab=tab_1. Kruk ME, Nigenda G, Knaul FM. Redesigning primary care to tackle the global epidemic of noncommunicable disease. American journal of public health. 2015;105(3):431-7. World Health Organization. WHO framework for meaningful engagement of people living with noncommunicable diseases, and mental health and neurological conditions. Geneva: World Health Organization; 2023. Available from: https://creativecommons.org/licenses/by-nc-sa/3.0/igo. ISBN 978–92–4-007307–4 (electronic version), ISBN 978–92–4-007308–1 (print version). Banatvala N, Small R, Bovet P, Perez CP. Whole-of-society response for NCD prevention and control. Noncommunicable Diseases: Routledge; 2023. p. 402-10. Nugent R, Bertram MY, Jan S, Niessen LW, Sassi F, Jamison DT, et al. Investing in non-communicable disease prevention and management to advance the Sustainable Development Goals. The Lancet. 2018;391(10134):2029-35. United Nations. Global indicator framework for the Sustainable Development Goals and targets of the 2030 Agenda for Sustainable Development. A/RES/71/313. E/CN.3/2018/2. 2018 [cited 2024 Dec 20]. Available from:https://unstats.un.org/sdgs/indicators/Global%20Indicator%20Framework%20after%20refinement_Eng.pdf. World Health Organization. Preventing and controlling noncommunicable diseases: World Health Organization; [cited 2025 Feb 09]. Available from: https://www.who.int/westernpacific/activities/preventing-and-controlling-noncommunicable-diseases#:~:text=Reduce%20the%20major%20modifiable%20risk,high%2Dquality%20research%20and%20development. Countdown N. NCD Countdown 2030: worldwide trends in non-communicable disease mortality and progress towards Sustainable Development Goal target 3.4. Lancet (London, England). 2018;392(10152):1072-88. Van Overbeeke E, Janssens R, Whichello C, Schölin Bywall K, Sharpe J, Nikolenko N, et al. Design, conduct, and use of patient preference studies in the medical product life cycle: a multi-method study. Frontiers in pharmacology. 2019;10:1395. Kabir A, Karim N, Billah B. Preference and willingness to receive non-communicable disease services from primary healthcare facilities in Bangladesh: A qualitative study. BMC Health Services Research. 2022;22(1):1473. Javadi D, Feldhaus I, Mancuso A, Ghaffar A. Applying systems thinking to task shifting for mental health using lay providers: a review of the evidence. Global Mental Health. 2017;4:e14. Fernandez-Lazaro CI, García-González JM, Adams DP, Fernandez-Lazaro D, Mielgo-Ayuso J, Caballero-Garcia A, et al. Adherence to treatment and related factors among patients with chronic conditions in primary care: a cross-sectional study. BMC family practice. 2019;20:1-12. Belay DG, Adugna A. Lost to follow up from chronic care services during COVID-19 from health facilities, in Northwest Ethiopia. Frontiers in Epidemiology. 2022;2:883316. Oliver SJ. The role of traditional medicine practice in primary health care within Aboriginal Australia: a review of the literature. Journal of ethnobiology and ethnomedicine. 2013;9:1-8. Lindhiem O, Bennett CB, Trentacosta CJ, McLear C. Client preferences affect treatment satisfaction, completion, and clinical outcome: a meta-analysis. Clinical psychology review. 2014;34(6):506-17. Van Haitsma K, Abbott KM, Arbogast A, Bangerter LR, Heid AR, Behrens LL, et al. A preference-based model of care: An integrative theoretical model of the role of preferences in person-centered care. The Gerontologist. 2020;60(3):376-84. Brennan PF, Strombom I. Improving health care by understanding patient preferences: the role of computer technology. Journal of the American Medical Informatics Association. 1998;5(3):257-62. Godfrey C, Vallabhaneni S, Shah MP, Grimsrud A. Providing differentiated service delivery to the ageing population of people living with HIV. Journal of the International AIDS Society. 2022;25:e26002. Liu L, Christie S, Munsamy M, Roberts P, Pillay M, Shenoi SV, et al. Expansion of a national differentiated service delivery model to support people living with HIV and other chronic conditions in South Africa: a descriptive analysis. BMC health services research. 2021;21:1-8. Arksey H, O'Malley L. Scoping studies: towards a methodological framework. International journal of social research methodology. 2005;8(1):19-32. Operational framework for primary health care. Geneva: World Health Organization; 2020 [cited 2024 Dec 20]. Available from: https://www.who.int/docs/default-source/primary-health/operational-framework-for-primary-health-care-wha73.pdf?sfvrsn=5c9b5b84_2. World Health Organization,. Pollock D, Peters MD, Khalil H, McInerney P, Alexander L, Tricco AC, et al. Recommendations for the extraction, analysis, and presentation of results in scoping reviews. JBI evidence synthesis. 2023;21(3):520-32. Clarivate. EndNote 20. Clarivate Analytics, 1500 Spring Garden Street, 10th Floor, Philadelphia, PA 19130. Available at: https://endnote.com. Badger D, Nursten J, Williams P, Woodward M. Should all literature reviews be systematic? Evaluation & Research in Education. 2000;14(3-4):220-30. Wang X, Song K, Chen L, Huang Y, Birch S. Eliciting preferences of providers in primary care settings for post hospital discharge patient follow-up. International Journal of Environmental Research and Public Health. 2021;18(16):8317. Jia E, Gu Y, Peng Y, Li X, Shen X, Jiang M, et al. Preferences of patients with non-communicable diseases for primary healthcare facilities: a discrete choice experiment in Wuhan, China. International journal of environmental research and public health. 2020;17(11):3987. Karunaratna S, Weerasinghe MC, Ranasinghe T, Jayasuriya R, Chandraratne N, Herath H, et al. Improving uptake of non-communicable disease screening in Sri Lanka: eliciting people’s preferences using a discrete choice experiment. Health Policy and Planning. 2022;37(2):218-31. Li X, Jiang M, Peng Y, Shen X, Jia E, Xiong J. Community residents’ preferences for chronic disease management in Primary Care Facilities in China: a stated preference survey. Archives of Public Health. 2021;79:1-9. Lv Y, Fu Q, Shen X, Jia E, Li X, Peng Y, et al. Treatment preferences of residents assumed to have severe chronic diseases in China: A discrete choice experiment. International journal of environmental research and public health. 2020;17(22):8420. Peng Y, Jiang M, Shen X, Li X, Jia E, Xiong J. Preferences for primary healthcare services among older adults with chronic disease: a discrete choice experiment. Patient preference and adherence. 2020:1625-37. Geng J, Bao H, Feng Z, Meng J, Yu X, Yu H. Investigating patients’ preferences for new anti-diabetic drugs to inform public health insurance coverage decisions: a discrete choice experiment in China. BMC Public Health. 2022;22(1):1860. Hua Y, Zhu Z, Li X, Gong J, Ding S, Lin J, et al. Patient preference for antiepileptic drugs treatment in China: evidence from the discrete choice experiment. Frontiers in Neurology. 2020;11:602481. Huang Y, Huang Q, Xu A, Lu M, Xi X. Patient preferences for diabetes treatment among people with type 2 diabetes mellitus in China: a discrete choice experiment. Frontiers in Public Health. 2022;9:782964. Balogun FM, Omotade OO, Svensson M. Stated preferences for human papillomavirus vaccination for adolescents in selected communities in Ibadan, Southwest Nigeria: A discrete choice experiment. Human Vaccines & Immunotherapeutics. 2022;18(6):2124091. Lv Y, Qin J, Feng X, Li S, Tang C, Wang H. Preferences of patients with diabetes mellitus for primary healthcare institutions: a discrete choice experiment in China. BMJ open. 2023;13(6):e072495. Wu D, Hua Y, Zhao Z, Huang X, Rao Q, Liu L, et al. Patient Preferences for Rescue Medications in the Treatment of Breakthrough Cancer Pain. Journal of Pain and Symptom Management. 2022;64(6):521-31. Zhu S, Chang J, Hayat K, Li P, Ji W, Fang Y. Parental preferences for HPV vaccination in junior middle school girls in China: a discrete choice experiment. Vaccine. 2020;38(52):8310-7. Li S, Liu S, Ratcliffe J, Gray A, Chen G. Preferences for cervical cancer screening service attributes in rural China: a discrete choice experiment. Patient preference and adherence. 2019:881-9. Oberlin AM, Pasipamire T, Chibwesha CJ. Exploring women's preferences for HPV‐based cervical cancer screening in South Africa. International Journal of Gynecology & Obstetrics. 2019;146(2):192-9. Ramezani_Doroh V, Delavari A, Yaseri M, Emamgholipour Sefiddashti S, Akbarisari A. Preferences of Iranian average risk population for colorectal cancer screening tests. International journal of health care quality assurance. 2019;32(4):677-87. Geng J, Li R, Wang X, Xu R, Liu J, Jiang H, et al. Eliciting Older Cancer Patients’ Preferences for Follow-Up Care to Inform a Primary Healthcare Follow-Up Model in China: A Discrete Choice Experiment. The Patient-Patient-Centered Outcomes Research. 2024:1-13. Zhu J, Li J, Zhang Z, Li H. Patients' choice and preference for common disease diagnosis and diabetes care: a discrete choice experiment. The International Journal of Health Planning and Management. 2019;34(4):e1544-e55. Xu T, Jiang Y, Guo X, Campbell JA, Ahmad H, Xia Q, et al. Maternal choices and preferences for screening strategies of gestational diabetes mellitus: A exploratory study using discrete choice experiment. Frontiers in Public Health. 2022;10:864482. Lv Y, Ren R, Tang C, Song K, Li S, Wang H. Preferences for patients with type 2 diabetes mellitus for medications in Shandong Province, China: a discrete choice experiment. Patient preference and adherence. 2022:2335-44. Costa Gil JE, Garnica Cuéllar JC, Perez Terns P, Ferreira-Hermosillo A, Cetina Canto JA, Garduno Perez AA, et al. Patients’ Preference Between DPP4i and SGLT2i for Type 2 Diabetes Treatment: A Cross-Sectional Evaluation. Patient preference and adherence. 2022:1201-11. Liu S, Liu J, Si L, Ke X, Liu L, Ren Y, et al. Patient preferences for anti-hyperglycaemic medication for type 2 diabetes mellitus in China: findings from a national survey. BMJ Global Health. 2023;8(4):e010942. Zhang W, He S, Wilson L, Foix-Colonier A, Pacou M, Zhu Y, et al. Factors Influencing Patient and Caregiver Preferences for Antipsychotic Treatment of Schizophrenia in China: A Discrete Choice Experiment. Patient preference and adherence. 2023:1421-30. Hoffman R, Phiri K, Kalande P, Whitehead H, Moses A, Rockers PC, et al. Preferences for Hypertension Care in Malawi: A Discrete Choice Experiment Among People Living with Hypertension, With and Without HIV. AIDS and Behavior. 2024:1-11. Yu X, Bao H, Shi J, Yuan X, Qian L, Feng Z, et al. Preferences for healthcare services among hypertension patients in China: a discrete choice experiment. BMJ open. 2021;11(12):e053270. Moor SE, Tusubira AK, Wood D, Akiteng AR, Galusha D, Tessier-Sherman B, et al. Patient preferences for facility-based management of hypertension and diabetes in rural Uganda: a discrete choice experiment. BMJ open. 2022;12(7):e059949. Kohler RE, Gopal S, Lee CN, Weiner BJ, Reeve BB, Wheeler SB. Breast cancer knowledge, behaviors, and preferences in Malawi: Implications for early detection interventions from a discrete choice experiment. Journal of global oncology. 2017;3(5):480-9. World Health Organization. PHC measurement framework and indicators: monitoring health systems through a primary health care lens [Internet]. World Health Organization; 2018 [cited 2024 Dec 22]. Available from: https://www.who.int/teams/integrated-health-services/health-services-performance-assessment/phc-measurement-framework-and-indicators. Okereke E, Unumeri G, Akinola A, Eluwa G, Adebajo S. Female clients’ gender preferences for frontline health workers who provide maternal, newborn and child health (MNCH) services at primary health care level in Nigeria. BMC Health Services Research. 2020;20(1):441. World Health Organization. WHO recommendations on self-care interventions: Human papillomavirus (HPV) self-sampling as part of cervical cancer screening and treatment, 2022 update. Geneva: World Health Organization; 2022. Available from: https://www.who.int/publications/i/item/WHO-SRH-22.6. Webb S, Mat Ali N, Sawyer A, Clark DJ, Brown MA, Augustin Y, et al. Patient preference and acceptability of self-sampling for cervical screening in colposcopy clinic attenders: A cross-sectional semi-structured survey. PLOS Global Public Health. 2024;4(5):e0003186. Serrano B, Ibáñez R, Robles C, Peremiquel-Trillas P, De Sanjosé S, Bruni L. Worldwide use of HPV self-sampling for cervical cancer screening. Preventive medicine. 2022;154:106900. Tilahun H, Fekadu B, Abdisa H, Canavan M, Linnander E, Bradley EH, et al. Ethiopia’s health extension workers use of work time on duty: time and motion study. Health policy and planning. 2017;32(3):320-8. Birhanu Z, Godesso A, Kebede Y, Gerbaba M. Mothers’ experiences and satisfactions with health extension program in Jimma zone, Ethiopia: a cross sectional study. BMC health services research. 2013;13:1-10. Aman K, Gobena T, Hawulte B, Maruta MB, Debella A, Eyeberu A, et al. Health extension workers' level of job satisfaction in western Hararghe Zone, eastern Ethiopia: an institutional-based cross-sectional study. Frontiers in Health Services. 2024;4:1353072. Conway N, Campbell I, Forbes P, Cunningham S, Wake D. mHealth applications for diabetes: user preference and implications for app development. Health informatics journal. 2016;22(4):1111-20. Toll K, Spark L, Neo B, Norman R, Elliott S, Wells L, et al. Consumer preferences, experiences, and attitudes towards telehealth: qualitative evidence from Australia. PLoS One. 2022;17(8):e0273935. Polinski JM, Barker T, Gagliano N, Sussman A, Brennan TA, Shrank WH. Patients’ satisfaction with and preference for telehealth visits. Journal of general internal medicine. 2016;31:269-75. Wagner EH. Chronic disease management: what will it take to improve care for chronic illness? Effective clinical practice. 1998;1(1). O’Connell S, Mc Carthy VJ, Savage E. Frameworks for self-management support for chronic disease: a cross-country comparative document analysis. BMC Health Services Research. 2018;18:1-10. World Health Organization. Framework on integrated, people-centred health services. Report No. A69/39. [Internet]. Geneva: World Health Organization; 2016 Apr 15 [cited 2024 Dec 22]. Available from: https://www.who.int. Perry M, McCall S, Nardone M, Dorris J, Obbin S, Stanik C. Program of All-Inclusive Care for the Elderly (PACE) Organizations Flip the Script in Response to the COVID-19 Pandemic. Journal of the American Medical Directors Association. 2024;25(2):335-41. e4. Awedew AF, Berheto TM, Dheresa M, Tadesse S, Hailmariam A, Tollera G, et al. The Burden of Non-Communicable Diseases and Its Implications for Sustainable Development Goals Across Regions in Ethiopia. Ethiopian Journal of Health Development. 2023;37(2). Tesema AG, Joshi R, Abimbola S, Mirkuzie AH, Berlina D, Collins T, et al. Readiness for non-communicable disease service delivery in Ethiopia: an empirical analysis. BMC Health Services Research. 2024;24(1):1021. UNAIDS. Rights in the time of COVID-19 Lessons from HIV for an effective, community-led response. Geneva, Switzerland: Joint United Nations Programme on HIV/AIDS (UNAIDS); 2020. Himmelman AT. Collaboration for a change: Definitions, decision-making models, roles, and collaboration process guide. Minneapolis: Himmelman Consulting. 2002. Tables Tables 1 to 4 are available in the Supplementary Files section. Supplementary File 1 Supplementary File 1 is not available with this version. Additional Declarations No competing interests reported. Supplementary Files Table1.docx Table2.docx Table3.docx Table4.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 14 Apr, 2025 Reviewers invited by journal 08 Apr, 2025 Editor assigned by journal 28 Mar, 2025 Submission checks completed at journal 28 Mar, 2025 First submitted to journal 06 Mar, 2025 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-6173948","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":439911863,"identity":"d20720fb-a583-4730-86bb-83215c790d3e","order_by":0,"name":"Aklilu Endalamaw","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYFACNsYDCQUMPPzsDUCOgQVRWhgOJBgwyEj2HABpkSBSC4MBg43BjQQQjwgtBsePJRx4YHCYh+Hm86sbfhRIMPC3dyfg13Im7QDQYYd5GGfnlN3sATpM4szZDfi1HEhvAGthls5Ju8ED1GIgkUtAy/nnEC1skmfSbv4hSssNqMN4JNiP3SbKFskbzxKAWtJ5JHhy2G7LGEjwEPQL3/k0w4c/Kqzt7Y8ff3bzzR8bOf72XvxaFA7AmTwGYBKvchCQb4Az2R8QVD0KRsEoGAUjEwAAMeJMrSicscEAAAAASUVORK5CYII=","orcid":"","institution":"Bahir Dar University","correspondingAuthor":true,"prefix":"","firstName":"Aklilu","middleName":"","lastName":"Endalamaw","suffix":""},{"id":439911864,"identity":"59384507-22d2-477c-8891-003e54362d31","order_by":1,"name":"Yihalem Abebe Belay","email":"","orcid":"","institution":"Debre Markos University","correspondingAuthor":false,"prefix":"","firstName":"Yihalem","middleName":"Abebe","lastName":"Belay","suffix":""},{"id":439911865,"identity":"3d3a10d0-a42c-4c85-a32f-4645b2f2b866","order_by":2,"name":"Esiknder Wolka","email":"","orcid":"","institution":"International Institute for Primary Health Care-Ethiopia","correspondingAuthor":false,"prefix":"","firstName":"Esiknder","middleName":"","lastName":"Wolka","suffix":""},{"id":439911866,"identity":"5e0aa406-6ddf-4967-a149-ef6d061c773a","order_by":3,"name":"Anteneh Zewdie","email":"","orcid":"","institution":"International Institute for Primary Health Care-Ethiopia","correspondingAuthor":false,"prefix":"","firstName":"Anteneh","middleName":"","lastName":"Zewdie","suffix":""},{"id":439911867,"identity":"9754b981-5655-4fee-8665-3a52f16b1a0b","order_by":4,"name":"Yibeltal Assefa","email":"","orcid":"","institution":"The University of Queensland","correspondingAuthor":false,"prefix":"","firstName":"Yibeltal","middleName":"","lastName":"Assefa","suffix":""}],"badges":[],"createdAt":"2025-03-07 00:53:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6173948/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6173948/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":80629761,"identity":"63a0fb5e-f6b0-41b7-8a60-d136679bbf65","added_by":"auto","created_at":"2025-04-15 11:36:29","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":42025,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual framework on DSD employed to identify client’s preference to service delivery attributes in general and based on social classes\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6173948/v1/70068a94bed38538507dfe14.png"},{"id":80629762,"identity":"2b7fbf10-6d6c-41d1-91c7-66a05f98fcb7","added_by":"auto","created_at":"2025-04-15 11:36:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":47643,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA flow diagram displaying the article selection process\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6173948/v1/d90f689d2443a581c964fec2.png"},{"id":80631950,"identity":"c51fa34a-519a-4ee6-a3b2-62a3a0f8c9aa","added_by":"auto","created_at":"2025-04-15 11:52:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":724197,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6173948/v1/f9ff1985-f1b7-4eaf-ac46-f95313535569.pdf"},{"id":80629765,"identity":"4a621152-ff41-4a59-94af-9b3b41b0bd5b","added_by":"auto","created_at":"2025-04-15 11:36:29","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":19001,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6173948/v1/821d9feaf895c95e81c662ec.docx"},{"id":80629768,"identity":"9dd3c2be-5fb5-469e-93b2-c63c9f9ca80c","added_by":"auto","created_at":"2025-04-15 11:36:29","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":69874,"visible":true,"origin":"","legend":"","description":"","filename":"Table2.docx","url":"https://assets-eu.researchsquare.com/files/rs-6173948/v1/cc18207bc856ad5c59376605.docx"},{"id":80630906,"identity":"4b7bb377-fcf2-4006-90a2-c7019a41b633","added_by":"auto","created_at":"2025-04-15 11:44:29","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":29018,"visible":true,"origin":"","legend":"","description":"","filename":"Table3.docx","url":"https://assets-eu.researchsquare.com/files/rs-6173948/v1/7d0fadc1afff9dfd7e30dd0a.docx"},{"id":80631949,"identity":"ced374bd-0dc7-4a2a-8820-2635077b9029","added_by":"auto","created_at":"2025-04-15 11:52:29","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":17055,"visible":true,"origin":"","legend":"","description":"","filename":"Table4.docx","url":"https://assets-eu.researchsquare.com/files/rs-6173948/v1/41e07a5c9b89452df9b329a6.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Transforming Noncommunicable Disease Services in Low- and Middle-Income countries: a Scoping Review","fulltext":[{"header":"Background","content":"\u003cp\u003eNoncommunicable diseases (NCDs) cause a growing burden on the global communities. It causes 41\u0026nbsp;million overall and 17\u0026nbsp;million premature deaths annually (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), mainly due to cardiovascular diseases (17.9\u0026nbsp;million deaths), cancers (9.3\u0026nbsp;million deaths), chronic respiratory diseases (4.1\u0026nbsp;million deaths), and diabetes mellitus (DM) (2\u0026nbsp;million deaths) (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The proportion of deaths attributed to these diseases increased from 80% in 2002 to 88.5% in 2019 (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). This burden is rapidly increased in low-and middle-income countries (LMICs), with a record of 73% of all deaths due to NCDs and 82% of all NCDs-related premature deaths in 2021(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Tobacco use, excessive alcohol consumption, unhealthy diets, and physical inactivity largely contribute to the increasing premature mortality (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Tobacco use accounts for over 8\u0026nbsp;million deaths annually with 80% to world\u0026rsquo;s tobacco users live in LMICs (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). An estimated 1.8\u0026nbsp;million annual deaths are associated with excess sodium intake (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Alcohol consumption and drug use accounts to more than half of the 3\u0026nbsp;million annual deaths, and insufficient physical activity contributes to 0.83\u0026nbsp;million deaths (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePrimary health care (PHC) is a whole-of-society approach to revitalize and realize NCDs-related best buys to reduce the burdens from these diseases (\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). These approaches involve the private sectors, civil societies, and political decision-makers, and engage clients with a focus on contextualization, equity, transparency, respect, and inclusivity (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). The call for reduction of premature mortality due to NCDs by a third revolves around preventing the underlying causes and healthcare interventions (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Primary health care can engage in promoting healthy lifestyle choices, implementing tobacco control policies, advocating for access to early detection, and providing curative care (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Adaptation and implementation of \u0026lsquo;best buys\u0026rsquo; for NCDs is possible with sustainable a whole-of-society and whole-of-government approaches (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), including financing, behavioral interventions, equity, integration, capacity building, and institutionalization (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEntertaining clients\u0026rsquo; preferences is crucial to provide person-centred care. Patient preferences are the choices and values that clients have regarding what, how, who, and when healthcare services are provided (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Considering clients\u0026rsquo; choices is essential to overcome a range of individual, interpersonal, societal, and organizational factors that influence preference and willingness to receive NCD services (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). There have been other challenges, such as poor community engagement (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), clients\u0026rsquo; low adherence to treatment (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), higher lost follow-up from care (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), and cultures or traditions (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), barred NCDs-related services. These can be addressed by providing tailored care to their preferences. Considering clients\u0026rsquo; preferences in healthcare results in greater satisfaction, higher treatment completion rates, and better clinical outcomes (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). This implies the necessity of developing a model of care based on the preferences, values, and needs of the patients to effectively implement treatment plans and care decisions (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIt is essential to understand clients\u0026rsquo; preference due to the dynamic and changing health system that is constantly evolving and adapting to new technologies, health policies, healthcare landscapes. Understanding patient preferences regarding what, where, when, and by whom healthcare services are provided plays a critical role in tailoring care to patient needs (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). This aligns with differentiated service delivery (DSD) model (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). There is a need present clients\u0026rsquo; preference in receiving NCDs services that tailored according to to the DSD model in LMICs settings. Evidence from this review will support the preparation and initiation of models of care for NCDs prevention and management.\u003c/p\u003e \u003cp\u003eTherefore, we conducted this scoping review to identify the clients\u0026rsquo; preferences for NCDs- related services at PHC level in LMICs. The study will provide a list of attributes and preferences to inform the adoption or development of new care models for NCDs management.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eReporting\u003c/h2\u003e \u003cp\u003e We followed Arksey and O\u0026rsquo;Malley\u0026rsquo;s guide on how to conduct a scoping review. They underscored five stages in conducting a scoping review: identifying the research question, identifying relevant studies, selecting studies, charting the data, and collating, summarizing and reporting the results (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eIdentifying the research question\u003c/h3\u003e\n\u003cp\u003eThe research question was to answer the health service delivery preference of clients with chronic diseases at PHC settings. Differentiated service delivery model was used to guide the current scoping review (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). This model is a client-centred care model used to understand what, how, where, who, and when of health care services are provided. It aims to tailor to the preferences and expectations of clients, care givers, and health workers in managing chronic diseases as care recipients and providers. There are essential building blocks to ensure the functionality of DSD: types of services or attributes, indicating the available, needed, or provided service attributes; the time, date or frequency of services provision; the health workers who provides the services, including level of education, expertise status, or experience; and the location or settings where the services are provided. It is assumed that clients needing chronic diseases services prefer one or more of the service attributes in each building block.\u003c/p\u003e \u003cp\u003eWe adapted the existing DSD model of care by adding the \u0026lsquo;how\u0026rsquo; element. This element represents the methods or mechanisms through which services should be delivered to the clients by appropriate healthcare workers at the convenient location and on preferred dates. We also considered clients\u0026rsquo; sociodemographic characteristics and health condition to understand how their backgrounds influence their own preferences for service delivery-related attributes. The DSD model will be integrated continuum of care. The continuum of care in PHC encompasses the range of services from health promotion to palliative care (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eIdentifying relevant studies\u003c/h3\u003e\n\u003cp\u003eWe included published articles from medical databases, including PubMed, EMBASE, Web of Science, and Scopus. We also searched articles from Google Scholar by writing the eligible articles from the databases into the Google Scholar search interface and clicking the \u0026lsquo;cited by\u0026rsquo; button to list articles that cited the original articles, assuming these may be related to them, as Google Scholar does not have advanced search strategy method.\u003c/p\u003e \u003cp\u003eThe search strategy was guided by Population, Concept, and Context (PCC) framework (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Studies that addressed all individuals with chronic non-communicable diseases regardless of age, gender, and other demographic and clinical characteristics were included. Attributes of services with the clients\u0026rsquo; preferences, identified by discrete choice experiment, are the main concept of the review. We gave emphasis for studies that were conducted only using DCE, which identified preferences through simulating real-world decision making and clients are asked to choose between sets of alternatives in identifying the relative importance of each attribute. Discrete choice experiment also provides the willingness of clients to trade off one attribute for another, uses experimental design that provides lists of attributes and levels, and offers essential preferences amongst the examined several hypothetical preferences.\u003c/p\u003e \u003cp\u003eThe search strategies were based on keywords and/or phrases-related to DCE and non-communicable diseases. To illustrate, the key terms were \u0026ldquo;discrete choice experiment\u0026rdquo;, \u0026ldquo;discrete-choice experiment\u0026rdquo;, \u0026ldquo;noncommunicable disease\u0026rdquo;, \u0026ldquo;non communicable disease\u0026rdquo;, \u0026ldquo;non-communicable disease\u0026rdquo;, \u0026ldquo;chronic disease\u0026rdquo;, \u0026ldquo;chronic lifelong condition\u0026rdquo;, \u0026ldquo;chronic life long condition\u0026rdquo;, \u0026ldquo;chronic life-long condition\u0026rdquo;, \u0026ldquo;cardiovascular disease\u0026rdquo;, cancer, \u0026ldquo;chronic respiratory disease\u0026rdquo;, \u0026ldquo;COPD\u0026rdquo;, \u0026ldquo;diabetes\u0026rdquo;, \u0026ldquo;mental health problem\u0026rdquo;, and \u0026ldquo;NCD\u0026rdquo;. Regarding the context, studies from low- and middle-income countries (low, lower-middle- and upper-middle-income countries) conducted in PHC settings were considered. However, we did not restrict the search strategy by including the phrase \u0026ldquo;primary health care\u0026rdquo;, as most studies might not mention it, even though the study was conducted in clinics and health centres, or services were provided by PHC workers. The Boolean operators (OR, AND, and *) were used to expand and/or limit searches when needed. In general, we included articles on NCDs, conducted using DCE design, and published in English at anytime and anywhere. The last search date for databases was on October 23, 2024. The search strategy for each database is presented in the supplementary file (Supplementary file 1-search strategy).\u003c/p\u003e\n\u003ch3\u003eSelecting relevant studies\u003c/h3\u003e\n\u003cp\u003eWe screened the relevant studies after thoroughly finding relevant articles and exporting them to EndNote 20 software (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). We first removed duplicates, followed by title and abstract screening. Titles and abstracts unrelated to NCDs, non-English articles, non-DCE articles, and studies not related to services in PHC settings were excluded. We also excluded other types of studies, such as cross-sectional, case control, and cohort studies conducted without DCE. Only studies involving clients were considered eligible. During the screening of irrelevant articles and inclusion of eligible ones, we held weekly meetings from the conception of the research question until the manuscript was prepared and submitted to the journal. In the meantime, we developed familiarity with the literature and were able to easily identify relevant and irrelevant articles, including those studies that were unclear from the abstract and required full article review. Hence, as abstracts do not represent the full-text (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), we reviewed all articles that passed the abstract screening phase during the full-text review.\u003c/p\u003e\n\u003ch3\u003eCharting the data\u003c/h3\u003e\n\u003cp\u003eCharacteristics of articles and findings were extracted from the eligible articles. We used Microsoft Excel 2010 to record extracted data. Authors, year of publication, country, study population, research approach, sample size, disease category, services, attributes, preference, and sociodemographic and clinical factors influencing clients\u0026rsquo; preferences were extracted.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCollating, Summarizing and Reporting the Results\u003c/h2\u003e \u003cp\u003eThis section mainly focuses on the synthesis of the findings. After we extracted the findings, iterative synthesis was conducted. The pre-identified framework guided the analysis to group the synthesized evidence. The information obtained from the articles was categorized into themes or key areas, such as study characteristics, attributes, and preferences. The analysis was guided by the DSD framework. The preferences were grouped according to the \u0026lsquo;who\u0026rsquo;, \u0026lsquo;when\u0026rsquo;, \u0026lsquo;where\u0026rsquo;, and \u0026lsquo;how\u0026rsquo; questions of service delivery. The findings are presented with figure, texts, and tables.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eSearch results\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe found a total of 1,154 records from EMBASE, 928 from SCOPUS, 731 from PubMed, and 372 from Web of Science. We also reviewed 123 articles from Google Scholar, resulting in a total of 3,308 articles. A total of 1,466 articles were eligible for title and abstract screening after removal of duplicates. Then, 346 were eligible for full-text review. With the focus to include studies from low- and middle-income countries conducted in PHC settings or on PHC services, only 27 articles were included (Figure 2). \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCharacteristics of the studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDiscrete choice analysis was employed to identify the service or medication preferences of individuals with chronic diseases (32-38). For example, it was used to identify clients’ preferences for screening services (34, 39-41), and comprehensive PHC services (33, 35-37, 39, 40, 42). The services include rescue medications for pain (43), HPV vaccination (41, 44), cervical cancer screening (CCS) (45, 46), early detection interventions for breast cancer (43), rectal cancer screening (38, 47), and follow‑up care (48). Preferences were also identified for DM, such as overall DM care (49), screening strategies of gestational DM (50, 51), and antidiabetic drugs (38, 40, 51-53). Preferences for antipsychotic medications for schizophrenia (51, 54) and epilepsy (39), hypertension-related services (55, 56), and healthcare-seeking decisions for individuals with HTN and DM (57) were identified. \u003c/p\u003e\n\u003cp\u003eThe study participants were adults of both sexes in most studies (33-40, 42, 43, 47-49, 51-53, 55-57), women (45, 46, 50, 58), parents of 12 to 16 years of age (44), adults 18 to 35 years of age and their caregivers (54), and community members of aged ten-years and above (41). A varying number of participants fall between 134 (43) and 3,327 (53) from different low- and middle-income countries, mostly from China (33, 35-40, 42-45, 48-51, 53, 54, 56), two from Malawi (55, 58), and one each from Nigeria (41), Argentina and Mexico (52), Sri Lanka (34), Uganda (57), South Africa (46), and Iran (47) (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClients’ Preference for Primary Health Care Services in Chronic Diseases Management\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eServices investigated to identify clients’ preferences were related to disease prevention (screening and vaccination), treatment, and rehabilitation care. Leadership and governance, health workforce, supplies and equipment, and infrastructure-related attributes were related to the ‘who’, ‘where’ and ‘how’ of the DSD care model. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWho\u003c/strong\u003e: Clients preferred care provided by physician or specialists (experts) (36, 48, 58) or senior care provider (33, 35, 37), and female health workers (58).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhere\u003c/strong\u003e: Clients preferred different location for the services, like community health gathering (58), workplace screening (34), screening location (town/lowest level of administration/ and village/community/ over country/highest level of administration/site) (45), static clinic over mobile clinic (46), home (47), and family planning (FP) clinic for breast cancer (BCa) screening (58). Remote communication outside clinic visits for follow-up care was also preferred (48). \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhen\u003c/strong\u003e: This includes fewer frequency of institution visit or longer gap between visits (45, 47, 48, 50), same day time of testing and treatment with diagnosis (46), and different access time (Saturday for urban and weekdays morning for estate sectors, all other time for rural sectors) (34), and adequate days before referral (4 days than 0 days) (49).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHow\u003c/strong\u003e: Attributes related to cost were the most common tested and preferred, with clients’ preference were lower out-of-pocket costs (33-36, 42, 45-47, 50, 54, 56, 57), shorter travel time or nearest facility (33, 36, 37, 42, 55-58), continuity of care (e.g., friendly provider) (34, 42, 48, 49, 55-57), shorter waiting time (34, 45, 46, 50, 55, 56), facility with sufficient equipment and medication (42, 49, 55, 57), modern medicine service \u0026amp; integrated service over traditional medicine (33, 35, 36), and seeing by a provider alone than group therapy (55) (Table 2). \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHeterogeneity in preferences with clients-related characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClients’ preference on how the services should be accessed, delivered, and overall experiences are varied based on sociodemographic and clinical status of clients (Table 3). \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProposed model of care\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA model of care with lower cost, nearby facilities, friendly providers, shorter waiting times, less frequent follow-ups, individual provider visits instead of group therapy, and care provided by better-educated health workers, with settings and dates or times varying due to service variations. To provide specific example, a model of care provided by the same specialist person, with personalized plan and self-initiated remote counselling is preferred to follow-up care for clients with cancer (48). Women preferred free services, same-day testing and treatment, and provider-collected swabs for CCS in South Africa (46) (Table 4).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis scoping review presents the clients\u0026rsquo; preference for NCDs services in LMICs. A model of care that offers lower costs, nearby facilities, friendly providers, shorter waiting times, less frequent follow-ups, individual provider visits instead of group therapy (e.g., for hypertension care), and care provided by better-educated health workers was the most preferred. The settings and dates for the service provision vary due to service and disease differences.\u003c/p\u003e \u003cp\u003eClients\u0026rsquo; preferences in receiving care for NCDs mostly pertain to the process aspects of PHC, which revolve around the \u0026lsquo;how\u0026rsquo; dimensions of the DSD framework. One can argue that the PHC approach comprises most of the attributes, as it includes health system inputs, processes, outputs, and impacts (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e). The health workforce is an essential input of PHC, representing the 'who' elements in the DSD framework. Clients prefer different types of care providers. Women, for example, prefer female over male providers and any provider over themselves to collect vaginal sample for CCS. Women preferred female frontline health workers at PHC level for maternal and neonatal services (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e). It has been recommended to increase acceptability of male workers especially in the presence of few health workers (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e). Clients\u0026rsquo; preference for swab sampling seems unwanted by health system, as WHO estimated self-sampling can help reach the global target of 70% coverage of screening by 2030; self-sampling nearly doubled use of cervical cancer screening services (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e). Self-sampling is also seen as cost effective, comfortable, safe, and user friendly (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e), but women preferred provider swab in South Africa (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). Self-sampling is highly preferred in high-income countries. For instance, 95% of women attending clinic preferred self-sampling for CCS in UK (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e). Globally, only 17 countries (three from Africa: Kenya, Uganda, and Rwanda) with identified screening programs recommend HPV self-sampling (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e). It may also be important to consider community members\u0026rsquo; preferences in relation to community health workers. Clients generally view them as having made a significant contribution to enhancing satisfaction, improving health status, and increasing health awareness in Ethiopia (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e), while others place less trust in them due to their limited competence in handling certain services (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e According to the \u0026lsquo;where\u0026rsquo; dimension of the DSD framework, the preferred locations for NCDs screening were home-based for CRC, workplace settings for general NCDs and cervical cancer, static clinics over mobile clinics for CCS, and family planning clinics for BCa. These settings are primarily based on screening, which implies that clients are likely to be in good health when accessing these services. It is important to consider the evolving needs arising from advanced health technologies and demographic changes (such as increased old age). Providing a combination of services comprising continuity of care, an individualized care plan, remote contact incorporating regular calls and counselling, and additional services (medication instructions or psychology support) could increase the acceptability of PHC services (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). Integrating health technology may determine the \u0026lsquo;where\u0026rsquo; of services. Only one study considered the HIT attributes, and clients preferred remote communication for follow-up care outside of clinic visits. There are various attributes to be integrated, such as websites, mobile or tablet apps, electronic prescriptions, messaging between clinicians and patients, educational platforms, telemonitoring, multichannel centers, wearable devices or sensors, health apps, and artificial intelligence (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e). According to a study in high-income countries (in Australia), consumers value the availability of telehealth and having flexibility to use telehealth when appropriate, but do not want to see telehealth replacing face-to-face delivery when physical examination was required (\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e). In the USA, among the general clients, one-third preferred a telehealth visit to a traditional in-person visit (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e). Health technology assessment is one of the attributes for the systematic integration of patient preferences (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePrimary health care services need to be provided on the appropriate date and at the assigned time. Few studies have addressed the \u0026lsquo;when\u0026rsquo; dimension of DSD. As clients prefer not to wait long for services and want to restrict frequent visits, and they favored same-day screening and treatment. However, women will undergo screening and take treatment at a return visit if services were free and the swab was collected by the provider (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). It is important to reorient PHC systems regarding the timing of certain chronic disease-related services, especially health education, mass screening, and immunization campaigns, to when community members are available or come to service areas. This includes considering when people are at home, when schools are closed, when church programs are available, market days, or specific seasons.\u003c/p\u003e \u003cp\u003eIn general, context-based care model with some-specificity is relevant. Clients\u0026rsquo; preference could be integrated with the existing model of care. Wagner Chronic Care model links between acute settings, community services, specialist care, and self-management support via collaboration (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e). There is another collaborative care model comprising self-management support, decision support, delivery system design, clinical information system, health system/organizational support, community support, case management, and family support. Each element needs to be seen into a very specific attribute. For instance, self-management support comprises essential components: patient education programmes, training for healthcare providers, awareness raising, accessibility, and technology use, with these components have also several alternatives (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e). Preferences vary based on the service types: early screening and diagnosis, vaccination, medication, and treatment. Designing care model is prompting to people-centered care, focuses on the needs of people and communities by engaging people and make them more active in their care, shifting away from health systems designed around diseases and health institutions towards health systems designed for people (\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e). WHO has proposed strategies in implementing people-centered care: empowering and engaging people and communities; strengthening governance and accountability; reorienting the model of care; coordinating services within and across sectors; and creating an enabling environment (\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eModels of care need to meet the clients\u0026rsquo; life course demands and fulfills their preferences, which may vary depending on clients\u0026rsquo; social class and clinical status. Designing care model for elders may give more emphasis to make services more accessible though this attribute is preferred by most clients, elders preferred nearby facility (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e) more importantly, such as community health centers (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e) and community-based vaccine provision than school (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). In the developed world, there have been elderly-specific model of care aimed at reaching them in the community or at their home. For instance, all-inclusive care for the elderly (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e). Patients with higher health-related quality of life paid more attention to healthcare services that contributed to good treatment effects (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e). For conditions perceived as minor, patients\u0026rsquo; preferences were valued in the following order: treatment measures, travel time, and care provider. For conditions perceived as severe, clients\u0026rsquo; preferences were ranked as follows: treatment measures, care provider, and type of service (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e As to research implications, the available articles on clients\u0026rsquo; preferences were limited to nine LMICs, even though many other countries have NCD programs and adopt WHO treatment guidelines. Most studies were conducted in China. More research is needed in other low-income countries with a higher burden of NCDs but low service accessibility and coverage. For instance, there were no studies in Ethiopia, where in 2019, the incidence rate was 190,000 incidence was recorded (\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e), and only 8% of facilities provided all four NCD services (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e). The continuum of care was partly addressed on disease prevention, treatment, and few on rehabilitation care. It is essential to understand clients\u0026rsquo; preference on by whom, where, and how health promotion services provided. Attributes related to community engagement and multisectoral actions were not addressed. Eliciting clients\u0026rsquo; or community members\u0026rsquo; preference may be essential revolving the principles of community engagement: trust, accessibility, contextualization, equity, transparency, and autonomy (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e). In multi-sectoral action, clients\u0026rsquo; or stakeholders\u0026rsquo; preference to identify which level of coordination is essential. The continuum of coordination begins from networking, coordinating, cooperating, collaborating, and integrating (\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis scoping review highlights the key preferences of clients regarding NCD services in LMICs, emphasizing affordability, accessibility, friendly providers, shorter waiting times, individualized care, and the expertise of health workers. Preferences varied based on service type, disease condition, and social factors, with specific expectations for the who, where, when, and how of care delivery. While many clients prioritized provider-led services, self-sampling and telemedicine were underutilized, despite their potential benefits. Aligning PHC models with these preferences is essential for improving service utilization and patient satisfaction. A context-based, people-centered approach that integrates health technologies, community engagement, and flexible service delivery is crucial. Additionally, health systems should address gaps in rehabilitative and palliative care while ensuring comprehensive NCD management. Further research is needed in diverse LMICs, particularly in countries with high NCD burdens but limited access to services. By incorporating patient preferences into healthcare planning, PHC systems can enhance effectiveness, equity, and long-term health outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e Not applicable because the review was dependent on published articles.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e: Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eThe data used during the current study are available in this manuscript and/or the supplementary file.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicting interests\u003c/strong\u003e: The authors declared no conflict of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: Authors have no received fund to conduct this specific review\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e: YA and AE conceptualised the project. AE extracted data, write the first draft and subsequent revision. YA supervised the whole research process. YAB cross-checked the data. YAB, AZ and EW revised the manuscript. All the authors approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWorld Health Organization. Noncommunicable diseases. 16 Sept 2023. Available from: https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases.\u003c/li\u003e\n\u003cli\u003ePeng W, Chen S, Chen X, Ma Y, Wang T, Sun X, et al. Trends in major non-communicable diseases and related risk factors in China 2002\u0026ndash;2019: an analysis of nationally representative survey data. The Lancet Regional Health\u0026ndash;Western Pacific. 2024;43.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Noncommunicable diseases Geneva: World Health Organization,; [updated Dec 24, 2024; cited 2025 Feb 09]. Available from: https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases#:~:text=Noncommunicable%20diseases%20(NCDs)%20killed%20at,disease%20deaths%20caused%20by%20diabetes).\u003c/li\u003e\n\u003cli\u003eUnited Nations. Political declaration of the High-level Meeting of the General Assembly on the Prevention and Control of Non-communicable Diseases. A/66/L.1. 16 Sept 2011. Available from: https://undocs.org/A/66/L.1.\u003c/li\u003e\n\u003cli\u003eGlobal Burden of Disease Collaborative Network. Global Burden of Disease Study 2019 (GBD 2019) Results. 2020. Institute for Health Metrics and Evaluation (IHME). Available from: https://vizhub.healthdata.org/gbd-results/.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Tobacco: Key facts Geneva: World Health Organization; [updated Jul 23, 2023; cited 2025 Feb 09]. Available from: https://www.who.int/news-room/fact-sheets/detail/tobacco.\u003c/li\u003e\n\u003cli\u003eEndalamaw A, Zewdie A, Wolka E, Assefa Y. Care models for individuals with chronic multimorbidity: lessons for low-and middle-income countries. BMC health services research. 2024;24(1):895.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Primary health care. Geneva: World Health Organization; [cited 2024 Dec 20]. Available from: https://www.who.int/health-topics/primary-health-care#tab=tab_1.\u003c/li\u003e\n\u003cli\u003eKruk ME, Nigenda G, Knaul FM. Redesigning primary care to tackle the global epidemic of noncommunicable disease. American journal of public health. 2015;105(3):431-7.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. WHO framework for meaningful engagement of people living with noncommunicable diseases, and mental health and neurological conditions. Geneva: World Health Organization; 2023. Available from: https://creativecommons.org/licenses/by-nc-sa/3.0/igo. ISBN 978\u0026ndash;92\u0026ndash;4-007307\u0026ndash;4 (electronic version), ISBN 978\u0026ndash;92\u0026ndash;4-007308\u0026ndash;1 (print version).\u003c/li\u003e\n\u003cli\u003eBanatvala N, Small R, Bovet P, Perez CP. Whole-of-society response for NCD prevention and control. Noncommunicable Diseases: Routledge; 2023. p. 402-10.\u003c/li\u003e\n\u003cli\u003eNugent R, Bertram MY, Jan S, Niessen LW, Sassi F, Jamison DT, et al. Investing in non-communicable disease prevention and management to advance the Sustainable Development Goals. The Lancet. 2018;391(10134):2029-35.\u003c/li\u003e\n\u003cli\u003eUnited Nations. Global indicator framework for the Sustainable Development Goals and targets of the 2030 Agenda for Sustainable Development. A/RES/71/313. E/CN.3/2018/2. 2018 [cited 2024 Dec 20]. Available from:https://unstats.un.org/sdgs/indicators/Global%20Indicator%20Framework%20after%20refinement_Eng.pdf.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Preventing and controlling noncommunicable diseases: World Health Organization; [cited 2025 Feb 09]. Available from: https://www.who.int/westernpacific/activities/preventing-and-controlling-noncommunicable-diseases#:~:text=Reduce%20the%20major%20modifiable%20risk,high%2Dquality%20research%20and%20development.\u003c/li\u003e\n\u003cli\u003eCountdown N. NCD Countdown 2030: worldwide trends in non-communicable disease mortality and progress towards Sustainable Development Goal target 3.4. Lancet (London, England). 2018;392(10152):1072-88.\u003c/li\u003e\n\u003cli\u003eVan Overbeeke E, Janssens R, Whichello C, Sch\u0026ouml;lin Bywall K, Sharpe J, Nikolenko N, et al. Design, conduct, and use of patient preference studies in the medical product life cycle: a multi-method study. Frontiers in pharmacology. 2019;10:1395.\u003c/li\u003e\n\u003cli\u003eKabir A, Karim N, Billah B. Preference and willingness to receive non-communicable disease services from primary healthcare facilities in Bangladesh: A qualitative study. BMC Health Services Research. 2022;22(1):1473.\u003c/li\u003e\n\u003cli\u003eJavadi D, Feldhaus I, Mancuso A, Ghaffar A. Applying systems thinking to task shifting for mental health using lay providers: a review of the evidence. Global Mental Health. 2017;4:e14.\u003c/li\u003e\n\u003cli\u003eFernandez-Lazaro CI, Garc\u0026iacute;a-Gonz\u0026aacute;lez JM, Adams DP, Fernandez-Lazaro D, Mielgo-Ayuso J, Caballero-Garcia A, et al. Adherence to treatment and related factors among patients with chronic conditions in primary care: a cross-sectional study. BMC family practice. 2019;20:1-12.\u003c/li\u003e\n\u003cli\u003eBelay DG, Adugna A. Lost to follow up from chronic care services during COVID-19 from health facilities, in Northwest Ethiopia. Frontiers in Epidemiology. 2022;2:883316.\u003c/li\u003e\n\u003cli\u003eOliver SJ. The role of traditional medicine practice in primary health care within Aboriginal Australia: a review of the literature. Journal of ethnobiology and ethnomedicine. 2013;9:1-8.\u003c/li\u003e\n\u003cli\u003eLindhiem O, Bennett CB, Trentacosta CJ, McLear C. Client preferences affect treatment satisfaction, completion, and clinical outcome: a meta-analysis. Clinical psychology review. 2014;34(6):506-17.\u003c/li\u003e\n\u003cli\u003eVan Haitsma K, Abbott KM, Arbogast A, Bangerter LR, Heid AR, Behrens LL, et al. A preference-based model of care: An integrative theoretical model of the role of preferences in person-centered care. The Gerontologist. 2020;60(3):376-84.\u003c/li\u003e\n\u003cli\u003eBrennan PF, Strombom I. Improving health care by understanding patient preferences: the role of computer technology. Journal of the American Medical Informatics Association. 1998;5(3):257-62.\u003c/li\u003e\n\u003cli\u003eGodfrey C, Vallabhaneni S, Shah MP, Grimsrud A. Providing differentiated service delivery to the ageing population of people living with HIV. Journal of the International AIDS Society. 2022;25:e26002.\u003c/li\u003e\n\u003cli\u003eLiu L, Christie S, Munsamy M, Roberts P, Pillay M, Shenoi SV, et al. Expansion of a national differentiated service delivery model to support people living with HIV and other chronic conditions in South Africa: a descriptive analysis. BMC health services research. 2021;21:1-8.\u003c/li\u003e\n\u003cli\u003eArksey H, O\u0026apos;Malley L. Scoping studies: towards a methodological framework. International journal of social research methodology. 2005;8(1):19-32.\u003c/li\u003e\n\u003cli\u003eOperational framework for primary health care. Geneva: World Health Organization; 2020 [cited 2024 Dec 20]. Available from: https://www.who.int/docs/default-source/primary-health/operational-framework-for-primary-health-care-wha73.pdf?sfvrsn=5c9b5b84_2. World Health Organization,.\u003c/li\u003e\n\u003cli\u003ePollock D, Peters MD, Khalil H, McInerney P, Alexander L, Tricco AC, et al. Recommendations for the extraction, analysis, and presentation of results in scoping reviews. JBI evidence synthesis. 2023;21(3):520-32.\u003c/li\u003e\n\u003cli\u003eClarivate. EndNote 20. Clarivate Analytics, 1500 Spring Garden Street, 10th Floor, Philadelphia, PA 19130. Available at: https://endnote.com.\u003c/li\u003e\n\u003cli\u003eBadger D, Nursten J, Williams P, Woodward M. Should all literature reviews be systematic? Evaluation \u0026amp; Research in Education. 2000;14(3-4):220-30.\u003c/li\u003e\n\u003cli\u003eWang X, Song K, Chen L, Huang Y, Birch S. Eliciting preferences of providers in primary care settings for post hospital discharge patient follow-up. International Journal of Environmental Research and Public Health. 2021;18(16):8317.\u003c/li\u003e\n\u003cli\u003eJia E, Gu Y, Peng Y, Li X, Shen X, Jiang M, et al. Preferences of patients with non-communicable diseases for primary healthcare facilities: a discrete choice experiment in Wuhan, China. International journal of environmental research and public health. 2020;17(11):3987.\u003c/li\u003e\n\u003cli\u003eKarunaratna S, Weerasinghe MC, Ranasinghe T, Jayasuriya R, Chandraratne N, Herath H, et al. Improving uptake of non-communicable disease screening in Sri Lanka: eliciting people\u0026rsquo;s preferences using a discrete choice experiment. Health Policy and Planning. 2022;37(2):218-31.\u003c/li\u003e\n\u003cli\u003eLi X, Jiang M, Peng Y, Shen X, Jia E, Xiong J. Community residents\u0026rsquo; preferences for chronic disease management in Primary Care Facilities in China: a stated preference survey. Archives of Public Health. 2021;79:1-9.\u003c/li\u003e\n\u003cli\u003eLv Y, Fu Q, Shen X, Jia E, Li X, Peng Y, et al. Treatment preferences of residents assumed to have severe chronic diseases in China: A discrete choice experiment. International journal of environmental research and public health. 2020;17(22):8420.\u003c/li\u003e\n\u003cli\u003ePeng Y, Jiang M, Shen X, Li X, Jia E, Xiong J. Preferences for primary healthcare services among older adults with chronic disease: a discrete choice experiment. Patient preference and adherence. 2020:1625-37.\u003c/li\u003e\n\u003cli\u003eGeng J, Bao H, Feng Z, Meng J, Yu X, Yu H. Investigating patients\u0026rsquo; preferences for new anti-diabetic drugs to inform public health insurance coverage decisions: a discrete choice experiment in China. BMC Public Health. 2022;22(1):1860.\u003c/li\u003e\n\u003cli\u003eHua Y, Zhu Z, Li X, Gong J, Ding S, Lin J, et al. Patient preference for antiepileptic drugs treatment in China: evidence from the discrete choice experiment. Frontiers in Neurology. 2020;11:602481.\u003c/li\u003e\n\u003cli\u003eHuang Y, Huang Q, Xu A, Lu M, Xi X. Patient preferences for diabetes treatment among people with type 2 diabetes mellitus in China: a discrete choice experiment. Frontiers in Public Health. 2022;9:782964.\u003c/li\u003e\n\u003cli\u003eBalogun FM, Omotade OO, Svensson M. Stated preferences for human papillomavirus vaccination for adolescents in selected communities in Ibadan, Southwest Nigeria: A discrete choice experiment. Human Vaccines \u0026amp; Immunotherapeutics. 2022;18(6):2124091.\u003c/li\u003e\n\u003cli\u003eLv Y, Qin J, Feng X, Li S, Tang C, Wang H. Preferences of patients with diabetes mellitus for primary healthcare institutions: a discrete choice experiment in China. BMJ open. 2023;13(6):e072495.\u003c/li\u003e\n\u003cli\u003eWu D, Hua Y, Zhao Z, Huang X, Rao Q, Liu L, et al. Patient Preferences for Rescue Medications in the Treatment of Breakthrough Cancer Pain. Journal of Pain and Symptom Management. 2022;64(6):521-31.\u003c/li\u003e\n\u003cli\u003eZhu S, Chang J, Hayat K, Li P, Ji W, Fang Y. Parental preferences for HPV vaccination in junior middle school girls in China: a discrete choice experiment. Vaccine. 2020;38(52):8310-7.\u003c/li\u003e\n\u003cli\u003eLi S, Liu S, Ratcliffe J, Gray A, Chen G. Preferences for cervical cancer screening service attributes in rural China: a discrete choice experiment. Patient preference and adherence. 2019:881-9.\u003c/li\u003e\n\u003cli\u003eOberlin AM, Pasipamire T, Chibwesha CJ. Exploring women\u0026apos;s preferences for HPV‐based cervical cancer screening in South Africa. International Journal of Gynecology \u0026amp; Obstetrics. 2019;146(2):192-9.\u003c/li\u003e\n\u003cli\u003eRamezani_Doroh V, Delavari A, Yaseri M, Emamgholipour Sefiddashti S, Akbarisari A. Preferences of Iranian average risk population for colorectal cancer screening tests. International journal of health care quality assurance. 2019;32(4):677-87.\u003c/li\u003e\n\u003cli\u003eGeng J, Li R, Wang X, Xu R, Liu J, Jiang H, et al. Eliciting Older Cancer Patients\u0026rsquo; Preferences for Follow-Up Care to Inform a Primary Healthcare Follow-Up Model in China: A Discrete Choice Experiment. The Patient-Patient-Centered Outcomes Research. 2024:1-13.\u003c/li\u003e\n\u003cli\u003eZhu J, Li J, Zhang Z, Li H. Patients\u0026apos; choice and preference for common disease diagnosis and diabetes care: a discrete choice experiment. The International Journal of Health Planning and Management. 2019;34(4):e1544-e55.\u003c/li\u003e\n\u003cli\u003eXu T, Jiang Y, Guo X, Campbell JA, Ahmad H, Xia Q, et al. Maternal choices and preferences for screening strategies of gestational diabetes mellitus: A exploratory study using discrete choice experiment. Frontiers in Public Health. 2022;10:864482.\u003c/li\u003e\n\u003cli\u003eLv Y, Ren R, Tang C, Song K, Li S, Wang H. Preferences for patients with type 2 diabetes mellitus for medications in Shandong Province, China: a discrete choice experiment. Patient preference and adherence. 2022:2335-44.\u003c/li\u003e\n\u003cli\u003eCosta Gil JE, Garnica Cu\u0026eacute;llar JC, Perez Terns P, Ferreira-Hermosillo A, Cetina Canto JA, Garduno Perez AA, et al. Patients\u0026rsquo; Preference Between DPP4i and SGLT2i for Type 2 Diabetes Treatment: A Cross-Sectional Evaluation. Patient preference and adherence. 2022:1201-11.\u003c/li\u003e\n\u003cli\u003eLiu S, Liu J, Si L, Ke X, Liu L, Ren Y, et al. Patient preferences for anti-hyperglycaemic medication for type 2 diabetes mellitus in China: findings from a national survey. BMJ Global Health. 2023;8(4):e010942.\u003c/li\u003e\n\u003cli\u003eZhang W, He S, Wilson L, Foix-Colonier A, Pacou M, Zhu Y, et al. Factors Influencing Patient and Caregiver Preferences for Antipsychotic Treatment of Schizophrenia in China: A Discrete Choice Experiment. Patient preference and adherence. 2023:1421-30.\u003c/li\u003e\n\u003cli\u003eHoffman R, Phiri K, Kalande P, Whitehead H, Moses A, Rockers PC, et al. Preferences for Hypertension Care in Malawi: A Discrete Choice Experiment Among People Living with Hypertension, With and Without HIV. AIDS and Behavior. 2024:1-11.\u003c/li\u003e\n\u003cli\u003eYu X, Bao H, Shi J, Yuan X, Qian L, Feng Z, et al. Preferences for healthcare services among hypertension patients in China: a discrete choice experiment. BMJ open. 2021;11(12):e053270.\u003c/li\u003e\n\u003cli\u003eMoor SE, Tusubira AK, Wood D, Akiteng AR, Galusha D, Tessier-Sherman B, et al. Patient preferences for facility-based management of hypertension and diabetes in rural Uganda: a discrete choice experiment. BMJ open. 2022;12(7):e059949.\u003c/li\u003e\n\u003cli\u003eKohler RE, Gopal S, Lee CN, Weiner BJ, Reeve BB, Wheeler SB. Breast cancer knowledge, behaviors, and preferences in Malawi: Implications for early detection interventions from a discrete choice experiment. Journal of global oncology. 2017;3(5):480-9.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. PHC measurement framework and indicators: monitoring health systems through a primary health care lens [Internet]. World Health Organization; 2018 [cited 2024 Dec 22]. Available from: https://www.who.int/teams/integrated-health-services/health-services-performance-assessment/phc-measurement-framework-and-indicators.\u003c/li\u003e\n\u003cli\u003eOkereke E, Unumeri G, Akinola A, Eluwa G, Adebajo S. Female clients\u0026rsquo; gender preferences for frontline health workers who provide maternal, newborn and child health (MNCH) services at primary health care level in Nigeria. BMC Health Services Research. 2020;20(1):441.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. WHO recommendations on self-care interventions: Human papillomavirus (HPV) self-sampling as part of cervical cancer screening and treatment, 2022 update. Geneva: World Health Organization; 2022. Available from: https://www.who.int/publications/i/item/WHO-SRH-22.6.\u003c/li\u003e\n\u003cli\u003eWebb S, Mat Ali N, Sawyer A, Clark DJ, Brown MA, Augustin Y, et al. Patient preference and acceptability of self-sampling for cervical screening in colposcopy clinic attenders: A cross-sectional semi-structured survey. PLOS Global Public Health. 2024;4(5):e0003186.\u003c/li\u003e\n\u003cli\u003eSerrano B, Ib\u0026aacute;\u0026ntilde;ez R, Robles C, Peremiquel-Trillas P, De Sanjos\u0026eacute; S, Bruni L. Worldwide use of HPV self-sampling for cervical cancer screening. Preventive medicine. 2022;154:106900.\u003c/li\u003e\n\u003cli\u003eTilahun H, Fekadu B, Abdisa H, Canavan M, Linnander E, Bradley EH, et al. Ethiopia\u0026rsquo;s health extension workers use of work time on duty: time and motion study. Health policy and planning. 2017;32(3):320-8.\u003c/li\u003e\n\u003cli\u003eBirhanu Z, Godesso A, Kebede Y, Gerbaba M. Mothers\u0026rsquo; experiences and satisfactions with health extension program in Jimma zone, Ethiopia: a cross sectional study. BMC health services research. 2013;13:1-10.\u003c/li\u003e\n\u003cli\u003eAman K, Gobena T, Hawulte B, Maruta MB, Debella A, Eyeberu A, et al. Health extension workers\u0026apos; level of job satisfaction in western Hararghe Zone, eastern Ethiopia: an institutional-based cross-sectional study. Frontiers in Health Services. 2024;4:1353072.\u003c/li\u003e\n\u003cli\u003eConway N, Campbell I, Forbes P, Cunningham S, Wake D. mHealth applications for diabetes: user preference and implications for app development. Health informatics journal. 2016;22(4):1111-20.\u003c/li\u003e\n\u003cli\u003eToll K, Spark L, Neo B, Norman R, Elliott S, Wells L, et al. Consumer preferences, experiences, and attitudes towards telehealth: qualitative evidence from Australia. PLoS One. 2022;17(8):e0273935.\u003c/li\u003e\n\u003cli\u003ePolinski JM, Barker T, Gagliano N, Sussman A, Brennan TA, Shrank WH. Patients\u0026rsquo; satisfaction with and preference for telehealth visits. Journal of general internal medicine. 2016;31:269-75.\u003c/li\u003e\n\u003cli\u003eWagner EH. Chronic disease management: what will it take to improve care for chronic illness? Effective clinical practice. 1998;1(1).\u003c/li\u003e\n\u003cli\u003eO\u0026rsquo;Connell S, Mc Carthy VJ, Savage E. Frameworks for self-management support for chronic disease: a cross-country comparative document analysis. BMC Health Services Research. 2018;18:1-10.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Framework on integrated, people-centred health services. Report No. A69/39. [Internet]. Geneva: World Health Organization; 2016 Apr 15 [cited 2024 Dec 22]. Available from: https://www.who.int.\u003c/li\u003e\n\u003cli\u003ePerry M, McCall S, Nardone M, Dorris J, Obbin S, Stanik C. Program of All-Inclusive Care for the Elderly (PACE) Organizations Flip the Script in Response to the COVID-19 Pandemic. Journal of the American Medical Directors Association. 2024;25(2):335-41. e4.\u003c/li\u003e\n\u003cli\u003eAwedew AF, Berheto TM, Dheresa M, Tadesse S, Hailmariam A, Tollera G, et al. The Burden of Non-Communicable Diseases and Its Implications for Sustainable Development Goals Across Regions in Ethiopia. Ethiopian Journal of Health Development. 2023;37(2).\u003c/li\u003e\n\u003cli\u003eTesema AG, Joshi R, Abimbola S, Mirkuzie AH, Berlina D, Collins T, et al. Readiness for non-communicable disease service delivery in Ethiopia: an empirical analysis. BMC Health Services Research. 2024;24(1):1021.\u003c/li\u003e\n\u003cli\u003eUNAIDS. Rights in the time of COVID-19 Lessons from HIV for an effective, community-led response. Geneva, Switzerland: Joint United Nations Programme on HIV/AIDS (UNAIDS); 2020.\u003c/li\u003e\n\u003cli\u003eHimmelman AT. Collaboration for a change: Definitions, decision-making models, roles, and collaboration process guide. Minneapolis: Himmelman Consulting. 2002.\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"},{"header":"Supplementary File 1","content":"\u003cp\u003eSupplementary File 1 is not available with this version.\u003c/p\u003e "}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-health-systems","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dihs","sideBox":"Learn more about [Discover Health Systems](https://www.springer.com/44250)","snPcode":"44250","submissionUrl":"https://submission.nature.com/new-submission/44250/3","title":"Discover Health Systems","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Non-communicable disease, Preference, Client, Service, Low- and middle-income countries","lastPublishedDoi":"10.21203/rs.3.rs-6173948/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6173948/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Understanding thepreferences, values, and needs of patients regarding what, where, when, and by whom comprehensive healthcare services provided is essential to improve utilization. This is especially critical among people requiring long-term care. There is a need to synthesise the available evidence on clients’ preference for noncommunicable diseases (NCDs) management. We conducted this scoping review to identify clients’ preferences for NCD-related services at the primary healthcare (PHC) level in low- and middle-income countries (LMICs).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A scoping review was conducted based on the Preferred Reporting Items for Systematic Review and Meta-analysis extension for scoping review. The included data sources were articles conducted by using discrete choice experiment among clients with NCDs at PHC levels. The analysis was guided by the Differentiated Service Delivery Framework, with the main findings analyzed using what, who, where, when, and how of service provision.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Twenty-seven articles from nine LMICs were included. The most frequent attributes were cost, accessibility to PHC settings (distance or travel time), continuity of care (e.g., friendly provider), waiting time to receive care, availability of equipment or medication, frequency of institution visit, health worker (e.g., level of expertise and gender), and treatment type (modern versus traditional care, particularly in China). Telemedicine use and date of services were rarely used. Clients preferred a model of care with lower cost, nearby facilities, friendly providers, shorter waiting times, less frequent follow-ups, individual provider visits instead of group therapy, and care provided by better educated and culturally tailored health workers, with settings and dates or times varying due to service variations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: This scoping review highlights the importance of understanding clients’ preferences for NCD services at PHC levels in LMICs. Preferred attributes could be integrated into chronic care models to satisfy clients’ needs in response to dynamic population characteristics, emerging pandemics, and growing technologies. The date and telecommunication use could be better adapted besides the mostly agreed and practiced care model elements, such as lower costs, nearby facilities, friendly providers, shorter waiting times, and individualized visits. Service settings and timing were shown to vary based on the type of service and disease, with clients prioritizing specific attributes within each care continuum.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trail Number\u003c/strong\u003e: Not applicable\u003c/p\u003e","manuscriptTitle":"Transforming Noncommunicable Disease Services in Low- and Middle-Income countries: a Scoping Review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-15 11:36:25","doi":"10.21203/rs.3.rs-6173948/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"338770963997896892661909969950176392922","date":"2025-04-14T07:34:54+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-08T06:05:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-28T05:19:15+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-28T05:17:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Health Systems","date":"2025-03-07T00:51:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-health-systems","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dihs","sideBox":"Learn more about [Discover Health Systems](https://www.springer.com/44250)","snPcode":"44250","submissionUrl":"https://submission.nature.com/new-submission/44250/3","title":"Discover Health Systems","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"67793d39-e982-447e-8131-2167d0eef609","owner":[],"postedDate":"April 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-10-09T07:24:06+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-15 11:36:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6173948","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6173948","identity":"rs-6173948","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}