A systematic literature review to identify delivery strategies of digital health for low SEP populations

A systematic literature review to identify delivery strategies of digital health for low SEP populations | 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 A systematic literature review to identify delivery strategies of digital health for low SEP populations Lucille Margot Bartha Standaar, Rosalie van der Vaart, Karlijn Leenaars, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8659891/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract Background Inclusive implementation, tailored delivery of e-health applications, and support in e-health use could help overcome the digital divide between people with a low and a high socio-economic position (SEP). However, limited knowledge is available on how e-health and support is best delivered to people with a low SEP and whether these strategies are based upon scientific or experiential knowledge. This literature review aims to (1) provide an overview of strategies to deliver e-health to people with a low SEP, (2) offer insight into the effectivity in reach of people with a low SEP by these e-health delivery strategies, and (3) identify scientific and experiential underpinnings for e-health delivery strategies’ design. Methods This systematic review followed the PRISMA 2022 guidelines. A systematic search was conducted using five databases: PsycINFO, Web of Science, Embase, PubMed and Sociological Abstracts. Search terms were built around the following key-concepts: socio-economic position, e-health and delivery strategy. Delivery strategies were categorized according to five delivery strategy components: place, point-of-contact, promotion, facilitation and incentive. Results The search strategy yielded 5141 papers. The included papers (n = 35) described 33 studies. Place and point-of-contact strategies were most often applied and combined in e-health delivery. Some evidence for reach effectivity exists for the following strategies: e-health delivery at locations visited by target groups, delivery via authorities and via offline promotion. In health organization contexts, how and which healthcare professional delivers e-health is relevant for effective reach. Applied underpinnings for delivery strategy design included stakeholder involvement for implementation strategy design, and identification and operationalization of delivery strategies. Conclusion This literature review identified a gap in the existing knowledge concerning effective strategies for the delivery of e-health delivery to people with a low SEP. Results show that almost all strategies used multiple delivery strategy components of which place and point-of-contact were most common. The evidence regarding the reach effectiveness of delivery strategies is insufficient and too scattered to support definitive conclusions. Nonetheless, it offers valuable insights into potential effective approaches. Researchers report little on theoretical or experiential underpinnings used for the design of e-health delivery strategies, nor are real world evaluations often conducted. Registration: PROSPERO: CRD42024572294 e-health health promotion health marketing socioeconomic outreach health equity implementation Figures Figure 1 Background As digital health becomes increasingly integrated into healthcare systems, concerns about equitable access and utilization are raised ( 1 , 2 ). Digital health, or e-health, is the use of information and communications technologies in health care to manage illnesses and health risks and to promote wellbeing ( 3 ). E-health includes the use of wearable devices, mobile health, telehealth, health information technology, and telemedicine ( 3 ). Although access to digital devices and the internet is increasing, less frequent and diverse use of e-health is observed among people with a lower socio-economic position (SEP) ( 4 – 7 ). Equitable delivery of e-health has proven to be difficult ( 7 – 10 ). Previous research shows that people with low SEP have diverse barriers in access and use of e-health ( 11 , 12 ). These needs include improvement of digital health skills, language skills, knowledge about the healthcare system, and awareness about e-health and its potential value ( 8 , 11 , 13 – 15 ). Scaioli et al. (2024) found that the lack of awareness about the existence and value of a patient portal is associated with low SEP ( 8 ). Researchers underline the role of organizations in realizing inclusive implementation strategies and accessible e-health applications to facilitate equitable access to e-health ( 16 – 19 ). O’Connor et al. (2016) describes that awareness, implementation strategies, support and promotion are crucial for engagement with digital health ( 17 ). Although research indicates what factors are important in the reach of people with a low SEP ( 16 – 20 ), there is limited clarity on what strategies exist to deliver e-health to people with a low SEP. Successful approaches in reaching people with a low SEP is studied in other health fields ( 21 – 23 ). Evidence shows that tailored delivery strategies and community engagement approaches are effective in reaching people with a low SEP ( 21 – 23 ). A literature review by O’Mara-Eves (2015) found that delivery of public health interventions for disadvantaged groups via community engagement approaches were effective to improve health outcomes ( 22 ). Approaches in which community peers were involved in the delivery of the public health intervention were particularly effective compared to interventions that empower the community or interventions that involved members in the design of the intervention ( 22 ). However, there is limited knowledge about what strategies successfully reach and introduce e-health to people with a low SEP ( 24 – 26 ). Successful access and use of e-health requires inclusive implementation strategies. Implementation is defined by Palinkas & Soydan (2012, p.10) as: “ a purposefully designed set of actions for the application of a purposefully designed program or intervention to cause change ” ( 27 ). The design and execution of e-health delivery strategies is one of the aspects of implementation. Insights into what e-health delivery strategies are employed and whether these are effective for people with a low SEP is vital for realizing equitable access to e-health in the real world context ( 17 , 28 , 29 ). The aim of this literature review is to provide insight into what e-health delivery strategies have been used to reach people with a low SEP. Secondly, it aims to gain insight in the effectivity in reach of these delivery strategies. Furthermore, this literature review focuses on whether the identified delivery strategies were derived from experiential knowledge or earlier scientific research. Such underpinnings might provide insight into why and how delivery strategies do or do not work. In this literature review, an e-health delivery strategy is defined as: a strategy employed to facilitate the use of e-health or e-health enabling services. This literature review is registered in the Prospero database under the registration number: CRD42024572294. Methods Search strategy Five databases were searched on 07-06-2024 electronically to identify relevant literature: Embase.com, Pubmed, PsycINFO, Web of Science and Sociological Abstracts. The key search terms were built around the concepts: (low) socio-economic populations, e-health and delivery strategies of products and services. A complete overview of the search terms can be found in Appendix 1. Search terms were constructed in consultation with two librarians. Study Design The PRISMA guidelines (2020) were used to structure this literature review and to ensure a systematic and rigorous analysis ( 30 ). The PRISMA checklist can be found in Appendix 2. The software package Rayyan was used as a tool for manual detection and removal of duplicates and screening. There was no use of AI technology. One researcher (LMBS) and two reviewers (JM and LS) were involved in the screening process. All involved had at least a bachelor degree in a health related field and were experienced in conducting research. Screening based upon title and abstract, and full-text screening were done independently. In the title and abstract screening phase, LMBS screened all articles and JM screened 3012/5127 (59%) articles. In the full-text screening phase, LMBS and LS both screened all papers. In both screening phases the researchers held regular meetings to discuss conflicts and find consensus. When consensus between the first and second reviewer could not be reached during the screening phase, a third researcher (LvT or RvdV) was consulted to resolve the conflict. The data extraction form was developed and pilot tested by LMBS. RvdV, LvT and LS reviewed the data extraction form and provided suggestions for improvement. LMBS extracted the data from all the papers, LS extracted the data from 20% of the papers. Conflicts in data extraction were resolved between LMBS and LS. LS conducted the critical appraisal of all included articles, JM appraised 11/35 (31%) of the included papers. Conflicts in the critical appraisal were resolved by LMBS by rereading the articles. Eligibility Population Studies were included when the delivery strategy was aimed at a low SEP population. To allow us to gain broader insight into SEP, three indicators were included: education, income and the socio-economic status of the living area. Education, income and socio-economic status of the living area are classic SEP indicators ( 31 ). It was expected that most research that described or evaluated e-health delivery strategies used one of these indicators to address SEP. Studies either had eligibility criteria that reflected a low SEP by one of the three previously mentioned SEP indicators or the study was held in a low SEP setting. If the study was conducted in a low SEP setting, demographics needed to provide insight into either education, income or neighborhood status of the study sample to confirm that the intervention was targeted to people with a low SEP. Income could also be derived from insurance status, type of employment such as blue-collar or white-collar jobs, or, attendance to specific clinics when eligibility to access these services requires a low income. Intervention The papers revolved around an e-health application or e-health enabling service. An e-health application was defined as follows: “The use of information and communications technology (ICT) in support of health and health related fields, including health care services, health surveillance, health literature, and health education, knowledge and research.” ( 32 ). Additionally, SMS based interventions were also included as SMS involves the use of a mobile phone. Included articles concerned both digital health care applications and digital public health applications ( 33 ). Digital health care applications aim for individual improvement of health, for example a diabetes management application or a patient portal, whereas digital public health applications aim to improve health on a population level, such as an COVID-19 tracking application or public health website ( 33 ). Support services are services that are tailored to enable people to adopt e-health. These services can either enable the individuals from vulnerable groups to gain access and use to e-health or improve the inclusivity of surroundings and services to be able to service vulnerable groups better. Examples of services that enable vulnerable individuals are: skills education, access to devices or increasing awareness around e-health. Delivery strategy & delivery strategy components The papers described a delivery strategy which was employed to facilitate the use of e-health or e-health enabling services. A delivery strategy can consist of one or multiple components that contribute to the reach of an e-health application or e-health enabling service. This literature review defined five delivery strategy components: place, point of contact, facilitation promotion and, incentive. The definitions of the delivery strategy components were derived from the marketing mix model described by McCarthy (1964) ( 34 , 35 ). The marketing mix model described the 4 P’s: product, price, place and promotion ( 34 , 35 ). As this review’s focus is to understand how low SEP populations are reached and how e-health is delivered, there was no focus on the product itself. McCarthy’s concept of ‘place’ encompassed place, the point-of-contact and facilitation. In our review those three elements of ‘place’ are discussed separately. McCarthy’s concept of price was interpreted as ‘incentive’ in this review, as digital health is often offered for free or as part of users’ healthcare plans. Digital health use is, therefore, often stimulated via other means rather than the price of the product. The delivery strategy components were used a priori as a tool to categorize the actions executed as part of delivery strategies. Place: the location where people can access the product. This includes the physical location but also the accessibility of the location in terms of opening hours and accessibility via (public) transport. Online products don’t have a “place” as online services are not bound to a location or opening hours. Example of an intended delivery strategy: a mobile health clinic in the center of a low socioeconomic neighborhood that provides information and support for use of e-health. Point of contact: Organizations and people that provide information, goods and services to facilitate the delivery of the product. Point of contact can be particularly important when the person involved is someone with specific authority or skill, for example health care professionals or the municipality. Promotion: All the activities that are intended to convey the message about the product or the place, point of contact or facilitation of the product. The following are considered promotion activities: online and offline advertisement, promotional items, promotional events, and, face-to-face selling. Facilitation: The provided information, goods and support that enable use of the product. Examples can be: an helpdesk that aids potential clients to use an e-health application or facilitation of devices and data plans. Incentive: the efforts done to stimulate potential users to use e-health or the e-health enabling service. Incentives can be financial, time-based, leisure, material or mental. Examples are: free health check, free gym membership or, coupons for a grocery store. Inclusion criteria The following inclusion criteria had to be met to be included in the review. The papers described the delivery strategy, the description had to include who performed the delivery, what the delivery strategy entailed and how the delivery strategy was performed. The study objective concerned the evaluation of an e-health application, e-health enabling service or, e-health delivery strategy with the aim to serve people with a low SEP. Demographics reported SEP by education, income or socio-economic status of the living area of the target population. Included study designs were: randomized controlled trail (RCT), quasi-experimental studies, mixed-method studies and observational study designs. Papers were required to be peer-reviewed and published on 01-01-2014 and onwards and written in the English or Dutch language. The research took place within Western societies, namely: Countries in Europe, the United States of America, Canada, Australia or New-Zealand. Exclusion criteria Qualitative and meta study designs were excluded. Papers that were protocols or pilot studies for future RCTs were excluded as these strategies were not executed on a full scale. Data extraction Overview of strategies For all papers the following data were extracted and presented in Supplementary file 1. In case papers referred to other published work for more information about the data of interest, this literature was used to gain more insight. Additional references were noted in the tables and appendices. Bibliographic information: title, first author, year of publication, doi; E-health or e-health enabling service: e-health application or e-health enabling service, type of e-health (web application, mobile application, electronic health record, video communication, wearable, domotics, robotics, medical integration networks, general integration networks, business intelligence and big data solutions and telehealth) ( 36 ) and, description primary health outcome; Context of study: type of study, delivery strategy (described/evaluated), country of study and, description of the research setting; Intervention: description of the delivery strategy, category of stakeholders involved in the delivery strategy (research, healthcare, education, social services, community, commercial, citizens), description of roles of the stakeholders, components of delivery strategy (X if applicable): place, point of contact, promotion, facilitation and incentive; authors reflections upon delivery strategies; Population: SEP selection criteria (individual, clinic or area characteristics), description of target population, description of inclusion criteria, description of exclusion criteria, information available of SEP variables of study participants (education, income, neighborhood), number of participants at baseline and, demographic data on socio-economic variables. The types of e-health are derived from an e-health application overview created by Krijgsman & Klein-Wolterink (2012) ( 36 ). The category ‘telehealth’ was added and represented all text-message based interventions. If the paper described and evaluated the reach or described scientific or experiential underpinnings of the delivery strategy, additional data was extracted. Reach Reach was defined by the number of people reached by the delivery strategy. Reach effectivity was measured by studies if the results showed a comparative analysis of the number of people reached between delivery strategies, between contexts that employed similar de strategies or between time points. Evidence for reach effectivity was found when the comparative analysis between delivery strategies was significant (p < 0.05). Data that described the reach per delivery strategy component or provided evidence for reach effectivity was extracted. Included data points for evaluation of delivery strategies: statistical analyses used, description of outcome measurements, the aim of the evaluation study, description outcome, exact outcome, and outcome significant (yes/no). Scientific and experiential underpinning of delivery strategies Data describing scientific or experiential underpinnings were systematically extracted from the articles. Scientific underpinning refers to theories or findings about the design of delivery strategies that were published in scientific literature. Experiential underpinnings refer to knowledge derived from experience from researchers or other stakeholders that was used to design the delivery strategy. Experiential underpinnings might be published in scientific literature, especially if stakeholders were involved during the design of the RCT or other prior conducted research. If this is the case, the underpinning is considered both scientific and experiential. Included data points for scientific or experiential underpinnings: scientific or experiential underpinning used (yes/no, if yes, experiential/scientific/experiential and scientific), description scientific or experiential underpinning, and sources scientific underpinning ((type of scientific underpinning: theory (name theory), scientific publications, prior research author), (focus: implementation, delivery, incentivization, or advertisement), doi or citation). Report on reach effectivity, and used scientific and experiential underpinnings for delivery strategies might be susceptible to missing values as it’s not common practice to discuss these findings in evaluation studies. Researchers might have the data to evaluate reach effectivity but did not include these results. All researchers used a delivery strategy to conduct their research and it is possible that researchers made decisions based upon knowledge or experience that was not described in the paper. When these data points were missing, the assumptions were made respectively: no evaluation of reach effectivity was performed, and no scientific or experiential underpinnings were used. Data synthesis First, papers were described upon study characteristics: type of study, setting, target group, type of e-health application, target health outcome and, how studies aimed to recruit a low SEP population, either via individual, clinic or area characteristics. Overview of papers’ characteristics are presented in Table 1. Secondly, an overview was created of the delivery strategy components and presented in Table 2. An overview of the stakeholders involved in the delivery strategy, the delivery strategy components and, theoretical and experiential underpinnings were described. Thirdly, the communalities and irregularities within each delivery strategy were assessed. Assessment was done via grouping studies by context, stakeholders involved and, the mechanisms of the delivery strategies used, including reported reach effectivity derived from the evaluation studies. Fourthly, the results were assessed across components by reviewing the occurrence of components, the combinations of components and whether studies that used scientific or experiential underpinnings had characteristics in common. Fifthly, an overview of the studies that described or evaluated reach was described and presented in Table 3. Quality Appraisal Joanna Briggs Institute (JBI) Critical appraisal tools for RCT, cross-sectional studies, quasi-experimental studies and cohort studies were applied to review the quality of the literature, see Supplementary file 2 for the critical appraisal including scores per question ( 37 ). Studies were scored by counting the number of questions that were answered with yes divided by the total number of questions. Longitudinal studies were appraised using the checklist for analytical cross sectional studies ( 37 ). Most studies included reported but did not evaluate e-health delivery strategies. The quality appraisal of these studies evaluate the aim of the study as is, which was the effect of the e-health intervention itself and not the delivery strategy. Articles that had a score of 75% or more were deemed of high quality. Articles were not excluded based upon quality appraisal. Results Study selection The screening process is described in detail in the PRISMA flowchart in Fig. 1. The search term yielded 7361 articles. After duplicate removal, 5127 articles were included. LMBS and JM screened 3014 (59%) articles on title and abstract independently. Cohen’s kappa was 0.56 which is considered a moderate agreement, percentage of agreement was 96% (2903/3014) ( 38 ). Thereafter, LMBS screened all remaining articles which resulted in 202 articles that were considered for full text screening. Additionally, LMBS screened three literature reviews ( 39 – 41 ) that were identified during the title and abstract screening. This yielded 7 more articles. LMBS and LS independently screened the full text of all 209 articles. A list of all the full-text screened articles can be found in Supplementary file 3. After screening on the eligibility criteria 35 articles were included. Cohen's kappa was 0.64, which is considered a substantial agreement, percentage of agreement was 89% (186/209) ( 38 ). The 35 included articles described 33 research projects. Critical appraisal Critical appraisal revealed that 14 studies had a quality score of 75% or higher, these studies were considered to be of high quality. Risk for bias related to selection and administration was identified in many studies (n = 19), all considering the blinding of participants or administrators. Furthermore, studies (n = 12) failed to identify and manage confounding factors. A detailed overview can be found in Supplementary file 2. Insert Fig. 1 here Figure 1. PRISMA Flowchart General study characteristics The search strategy resulted in the inclusion of 35 papers that described 33 research projects ( 42 – 85 ). An overview of the characteristics of the papers can be found in Table 1. Table 1 presents a subset of the following data: type of study, e-health type, primary health outcome, description target population, SEP selection criteria. Majority of the included papers were RCT’s (n = 19) ( 43 – 50 , 52 – 55 , 61 , 65 , 68 , 73 – 79 , 83 – 85 ). Furthermore, the following study designs were identified: cross sectional (n = 8) ( 58 – 60 , 66 , 70 , 71 , 80 – 82 ), longitudinal (n = 4) ( 48 , 49 , 62 – 64 , 69 , 72 ), cohort (n = 2) ( 42 , 56 , 57 ), and quasi-experimental (n = 2) ( 51 , 67 ). Eight papers ( 48 , 49 , 56 – 59 , 62 – 64 , 70 , 71 , 82 ) concerned secondary analyses from RCT studies. Twelve papers ( 42 , 47 , 51 , 56 – 60 , 62 – 64 , 69 – 71 , 80 , 81 ) evaluated the reach of the applied delivery strategy. Other papers (n = 23) only described the delivery strategy as part of the research design. Most studies were conducted in the United States (US) (n = 29), other countries were Australia (n = 3) ( 42 , 61 , 83 ), the UK (n = 2) ( 62 – 64 , 68 ) and the Netherlands (n = 1) ( 71 ). Most studies were published between 2020–2024 (n = 25) ( 42 , 46 – 51 , 56 – 65 , 68 – 76 , 78 – 81 , 83 ) . The majority of papers (n = 34) focused on an e-health application. Different types of e-health were studied: mobile applications (n = 10), web applications (n = 9), wearables (n = 6), telehealth (n = 11), video communication (n = 6) and electronic health records (n = 4). Alcaraz, Vereen & Burnham evaluated the reach from an e-health enabling service (n = 1): a national-wide information and referral system, that aimed to connect people with a low SEP with resources to meet their basic human needs ( 81 ). Papers focused on the management of disease (n = 15): diabetes, COVID19, asthma, dementia, glaucoma, and children’s development. Twelve papers concerned behaviour-related health topics, with the focus on weight, physical activity, and alcohol consumption. Five papers focused on healthcare processes: patient screening to identify needs and family history, and access to care. Three papers focused on mental health related conditions. The papers’ range in number of participants was n = 33–32.523 (mean: 2.259) ( 42 – 85 ). Target populations were mainly adults except for two papers which included: all residents including children ( 60 ) and adolescents and their parents ( 85 ). Some papers focused on specific adult groups: parents (n = 11), adults from ethnic minority populations (n = 5), and older adults (n = 2) or pregnant women (n = 1). Staples et al. and McEntee et al. recruited adults with a high and low SEP ( 42 , 76 – 78 ). Danila et al. recruited older adults and adults with a low SEP ( 73 ). Eight papers enacted individual-bound low SEP eligibility criteria or recruited participants in low SEP-bound contexts ( 42 , 45 – 49 , 68 , 69 , 75 – 78 ). Other papers (n = 27) recruited participants in low SEP contexts: clinics that predominantly serve low SEP populations or areas where predominantly low SEP populations live or visit. Twelve papers had in- or exclusion criteria based upon having digital skills or having access to devices and text- or data plans ( 52 – 55 , 62 – 65 , 67 , 68 , 70 – 73 , 75 ). Nelson et al. offered training to use the intervention as part of their recruitment procedure, where participants that could not successfully use the intervention after training were excluded ( 72 ). Table 1. Summary of paper characteristics (N = 35). Insert Table 1 here. a Only the data concerning the United Kingdom population was included in this literature review b RCT: Randomized Controlled Trial c USA: United States of America d UK: United Kingdom e EHR: Electronic Health Record f FQHC: Federally Qualified Healthcare Centre g BMI: Body Mass Index h SEP: Socioeconomic Position i NICU: Neonatal Intensive Care Unit Description and evaluation of delivery strategies An overview of the delivery strategies is presented in Table 2. From here onwards, the results are described per research project (n = 33) and are referred to as study. First, a general description of the delivery strategies are discussed which include: the occurrence of delivery strategies and the stakeholders involved. After the general overview, a description of each delivery strategy component is presented. Followed by a description of the combinations of delivery strategy components. Finally, the studies that evaluated the reach effectivity of delivery strategies are presented. General overview Delivery strategies consisted mostly of three (n = 10), four (n = 10) or two (n = 9) delivery strategy components. Less frequent were delivery strategies with five (n = 3) or one (n = 1) delivery strategy components. Delivery strategies were often organized with stakeholders. Healthcare organisations (n = 26) were often involved in the execution of delivery strategies. Furthermore, collaborations with community partners (n = 6), citizens (n = 2), commercial parties (n = 3), social services (n = 2), government (n = 3) and education (n = 1) were also described. 1. Point of contact Point of contact was used in 31 studies ( 42 – 59 , 61 – 75 , 79 – 85 ). Literature shows that research staff, healthcare professionals or healthcare organisation staff were often the person that introduced participants to the e-health application or e-health enabling service (n = 29) ( 42 – 59 , 61 – 64 , 67 – 75 , 79 – 85 ) Community organisations, governmental bodies, social services and key figures were also used for e-health delivery ( 54 – 57 , 62 – 66 , 71 ). Invitation letters in the study from Bennett et al. were signed by the head of the healthcare clinic, a key figure in the area, for a personal approach ( 54 , 55 ). Personal recruitment occurred via in-person recruitment (n = 10), phone call recruitment (n = 10), referrals (n = 9), invitation letters (n = 9), e-mail recruitment (n = 4) or text message recruitment (n = 1). 2. Place Twenty-seven studies deployed their delivery strategies at places that were commonly visited by people with a low SEP ( 43 – 61 , 65 – 70 , 72 – 74 , 79 – 85 ). Two studies recruited participants online and used location targeted social media advertisements to reach low SEP participants ( 71 , 76 – 78 ), locations were determined via geographical deprivation indexes. Fifteen studies executed the delivery of e-health within specific healthcare organizations that have to treat patients regardless of their insurance status, which attracts low SEP populations ( 43 , 44 , 47 – 59 , 70 , 72 , 79 , 80 , 82 , 83 ). Studies reported conducting research in American safety-net hospitals, community healthcare centres, federally qualified healthcare centres, free clinics and private non-profit clinics. Three studies recruited participants during healthcare that is only available for people with a public health insurance, such as during Women, Infants and Children appointments ( 45 , 46 , 58 , 59 , 79 ). Fourteen studies delivered e-health in the following settings that were located in low SEP areas: healthcare clinics (n = 10) ( 45 , 46 , 58 – 61 , 65 , 68 , 69 , 73 , 74 , 84 ), social service organizations (n = 2) ( 56 , 57 , 67 ), schools (n = 1) ( 85 ), and church (n = 1) ( 66 ). Several studies used geographical deprivation data to first select low SEP areas before identifying study sites within the selected areas ( 60 , 66 , 68 , 69 , 71 , 76 – 78 , 85 ). Kling et al. reviewed patient data to identify the number of low SEP participants to determine that clinics were located in a low SEP area ( 45 , 46 ). 3. Promotion Fifteen studies used offline promotion (n = 11) ( 43 – 46 , 54 – 57 , 60 , 62 – 64 , 66 , 70 – 72 , 74 , 84 ), online promotion (n = 8) ( 45 , 46 , 56 , 57 , 62 – 65 , 71 , 74 , 76 – 78 , 80 ) and word-of-mouth (n = 3) ( 56 , 57 , 69 , 71 ) promotional means to reach low SEP target populations. Promotion activities performed in collaboration with authorities such as healthcare professionals, well-known health services or municipalities were described ( 54 – 57 , 62 – 66 , 71 , 84 ). Some researchers collaborated with other parties to use their advertisement outlets to improve their reach, partners reported were: municipalities from low SEP areas ( 71 ), gyms located in low SEP areas ( 71 ), the national health institute ( 62 – 64 ), a smoking cessation app ( 62 – 64 ), health or social service programs ( 56 , 57 , 66 , 84 ) and, local community organizations ( 65 ). Furthermore, three studies reported the recruitment via family, friends or others ( 56 , 57 , 69 , 71 ). 4. Facilitation Facilitation of e-health use (n = 16) was reported in the forms of providing education and technical support (n = 11) and facilitation of devices (n = 9) ( 47 – 49 , 51 , 60 , 62 – 66 , 69 , 72 , 74 – 78 , 80 , 82 , 84 , 85 ). In few studies technical support was available upon participants’ request ( 62 – 64 , 75 ). In other studies support was part of the recruitment process; participants would get educated on the use of the device and e-health application at the start of the study ( 47 – 49 , 51 , 60 , 62 – 66 , 69 , 72 , 74 – 78 , 80 , 82 , 84 , 85 ). Garg et al. included a peer patient navigator who helped participants navigate online application forms for social support ( 47 ). Baggett et al. and Baker et al. delivered support in e-health use at home, saving traveling time and overcoming logistic barriers ( 69 , 80 ). Facilitation of devices (n = 9) was organized to enable e-health use ( 51 , 60 , 69 , 74 , 76 – 78 , 80 , 82 , 84 , 85 ). I-pads, phones or laptops (n = 7) and physical activity trackers (n = 2) were lend out for the duration of the study. 5. Incentives Incentivization (n = 15) was applied by offering financial means, a service, or a device ( 43 , 44 , 47 – 50 , 54 , 55 , 60 , 62 – 65 , 67 , 69 , 74 – 78 , 81 , 84 ). Financial incentives (n = 8) were provided in the forms of stipends or gift cards, the minimum amount of financial incentive was 6 $ ( 62 – 64 ) and the maximum was 415 $ ( 76 – 78 ) ( 50 , 62 – 65 , 67 , 74 – 78 , 81 ). Four studies applied a staggered financial incentive approach, whereby participants would receive financial compensation for completion of each survey or progressive use of the e-health application ( 62 – 64 , 74 – 78 ). Studies (n = 7) also offered other types of incentivization which are categorized as a service incentive ( 43 , 44 , 47 – 49 , 60 , 69 , 84 ). These incentives are not financial but provide a service or information. Services provided were: exercise program or gym membership ( 43 , 44 , 84 ), a local resource guide ( 81 ), free support for social needs ( 47 ), free food, childcare and healthcare ( 48 , 49 ), free Wi-Fi ( 60 ), and free healthcare ( 69 ). Bennett et al. and Griffin et al. provided devices for participants to keep: a cellular scale ( 54 , 55 , 67 ) and a physical activity tracking meter ( 67 ). Combinations of delivery strategy components The combination of the delivery strategies place and point of contact were most common in the identified literature (n = 26) ( 43 – 59 , 61 , 65 – 70 , 72 – 74 , 79 , 80 , 82 – 85 ). In case of the studies that employed two delivery strategies components, 7 of 9 studies combined place and point-of-contact strategy components ( 52 , 53 , 58 , 59 , 61 , 68 , 73 , 79 , 83 ). The other two studies employed point-of-contact and promotion, and point-of-contact and incentive strategy components ( 71 , 81 ). Delivery strategy components promotion, facilitation and incentive were employed in equal measures when studies used three or more delivery strategy components. McEntee et al. is the only study that does not deliver e-health through place nor point of contact strategies ( 76 – 78 ). This delivery strategy made use of promotion, facilitation and incentive strategies and used location specific online promotion activities in high and low SEP areas. Additionally, this study reported the highest maximal financial incentive of $ 415 ( 76 – 78 ). Point of contact strategies also combined with promotion strategies and incentive strategies Six studies (n = 6) ( 42 , 62 – 64 , 71 , 75 – 78 , 81 ) did not recruit participants via strategy component place. The majority of these studies (n = 5) recruited via point of contact combined with promotion and, incentivization strategy components ( 42 , 62 – 64 , 71 , 75 , 81 ). Five studies covered a greater area (municipalities to country-wide areas) ( 42 , 62 – 64 , 71 , 76 – 78 , 81 ) and four of these studies delivered e-health via authorities or well-known institutions ( 42 , 62 – 64 , 71 , 81 ). Collombon et al. recruited participants living in low SEP areas via written invitations sent out from the municipality office and via online advertorials spread via gyms that were located in low SEP areas ( 71 ). Alcaraz, Vereen & Burnham studied the reach of a well-known nation-wide social service to evaluate whether this institution was a suitable avenue for recruitment of people with socioeconomic disadvantages for health disparities research ( 81 ). Three studies provided a financial incentive ( 62 – 64 , 76 – 78 , 81 ). Oldham et al. and McEntee et al. used theoretical underpinnings to determine the financial incentivization strategies ( 62 – 64 , 76 – 78 ). Table 2. Overview of the stakeholders, means and components of the employed delivery strategies. Studies are sorted to the number of applied delivery strategy components. The grey shaded studies are the studies that proved significance (p < 0.05) in the evaluation of the delivery strategies’ reach of low SEP participants. The lilac shaded studies are the studies that used a scientific or experiential underpinning for designing the delivery strategies. The blue shaded studies are studies that both had a significant outcome in the evaluation of the delivery strategies’ reach for low SEP participants and used an underpinning for their delivery strategy design. Insert Table 2 here. Evaluation of delivery strategies’ reach and reach effectivity An overview of the twelve studies that evaluated the effectiveness of reach of the delivery strategies can be found in Table 3. Four studies presented descriptive statistics about the effectivity of reach ( 58 , 59 , 62 – 64 , 69 , 80 ). Eight studies conducted statistical analysis to determine whether delivery strategies were effective in reach ( 42 , 47 , 51 , 56 , 57 , 60 , 70 , 71 , 81 ). The majority of these studies (n = 7) showed statistical significance and provided evidence for reach effectivity ( 42 , 47 , 56 , 57 , 60 , 70 , 71 , 81 ). Studies were deemed significant if there was a p < 0.05 outcome for differences in reach between included conditions in the study. Delivery strategies containing the following delivery strategy components were evaluated: point of contact ( 42 , 47 , 51 , 58 , 59 , 80 ), promotion ( 56 , 57 , 62 – 64 , 70 , 71 , 81 ), place ( 56 , 57 , 60 , 69 ), and facilitation ( 51 ). Significant evidence was found in the delivery strategy components point-of-contact (n = 2) ( 42 , 47 ), place (n = 1) ( 56 , 57 ) and promotion (n = 4) ( 56 , 57 , 70 , 71 , 81 ). There were no evaluation studies that evaluated incentive delivery strategies. Elam et al. and Ehmer et al. both performed two evaluations ( 51 , 56 , 57 ). In Table 3 these evaluations are referred to as StudyID 7 and 7a, and, 10 and 10a ( 51 , 56 , 57 ). 1. Point of contact Five studies evaluated point of contact delivery strategies which concern the role of a healthcare professional and the organisation of their work processes ( 42 , 47 , 51 , 58 , 59 , 80 ). Staples et al. compared the reach of self-referral and physician-led referral to two similar online mental health treatment websites ( 42 ). The self-referral website was well-known among the public. Physicians were trained to identify low SEP status of patients and refer these patients to the website. Physician-led referral significantly reached more people with a lower education (X2 = 321.8, p < 0.001), less likely to be employed (X2 = 145.6, p < 0.001) and living in a disadvantaged area (X2 = 173.2, p < 0.001) compared to self-referral ( 42 ). Task allocation and organisation of personnel in healthcare contexts are relevant in reach of low SEP populations. Garg et al, Simione et al., and Baggett et al. compared differences in the e-health referrals ( 47 , 58 , 59 , 80 ). Garg et al. showed that clinics with social needs screening and extra personnel that support patients with digital health use showed significantly more referrals (OR 4.6 95CI 2.0-5.9) ( 47 ). Descriptive analysis from Simione et al. showed that medical assistants were more consistent and reached more patients compared to physicians (54% compared to 17% or 12%) in following up with an e-health referral ( 58 , 59 ). Baggett et al. compared a gatekeeper referral approach vs open and shared referral approach in three similar neonatal intensive care units. The clinic adopting the latter approach had 13 referrals/quarter, clinics adopting a gatekeepers approach had 4.2 and 3.4 referrals/quarter ( 80 ). 2. Place Elam et al., Levy et al., and Baker et al. evaluated place delivery strategies ( 56 , 57 , 60 , 69 ). Elam et al. showed that the free clinic recruited significantly more patients without a medical insurance compared to the federally qualified healthcare centre (FQHC) (47.8% vs. 7.8%, respectively; P < 0.0001) ( 56 , 57 ). Clinic phone call recruitment significantly recruited more patients in the FQHC (6.5% vs. 49.8%, respectively; P < 0.0001) ( 56 , 57 ). Community based strategies were significantly more effective in the free clinic: recruitment by a non-medical staff member (24.6% vs. 4.5%; P < 0.0001), a flyer outside the clinic (10.7% vs. 2.1%; P < 0.0001), or the clinics website or social media (7.3% vs. 0.7%; P < 0.0001) ( 56 , 57 ). Furthermore, the FQHC patients with diabetes were actively approached for a glaucoma screening. The authors noted that diabetes patients may be more motivated to attend the glaucoma screening and are more likely to have a public health insurance ( 56 , 57 ). Levy et al. and Baker et al. used multiple databases to identify low SEP individuals ( 69 ) or regions ( 60 ) and used a mobile health van to deploy e-health at home ( 69 ), or in the community ( 60 , 69 ). Results by Levy et al. showed that a mobile health van was more effective in reaching citizens living in low SEP neighbourhoods compared to a permanently located drive through location (25% vs 27%, p = 0.01) ( 60 ). After introducing the determination of mobile health vans locations based on real-time COVID-19 prevalence, socioeconomic status of the area and, disease burden, a significant positive trend in reaching low SEP populations (P > 0.001) was found ( 60 ). Baker et al. described that home visits with the mobile van was less successful in reaching Medicaid-insured citizens with a high risk of severe COVID complications than a permanent health facility location within the low SEP area ( 69 ). 3. Promotion Five studies evaluated the differences in the reach of low SEP participants between offline and online promotion strategies ( 56 , 57 , 62 – 64 , 70 , 71 , 81 ). Elam et al, Miller et al., and Alcaraz, Vereen & Burnham showed similar significant results; offline promotion strategies are more effective compared to online promotion strategies. Miller et al. showed that outreach via e-mail is significantly less effective for people with a high school degree (14%) compared to some college (35%) or college degree (38%) (P < 0.0001) ( 70 ). Alcaraz, Vereen & Burnham found that people with higher educational attainment (OR 2.17, CI95 1.67–2.82), higher income (OR 2.02, CI95 1.56–2.61) and who are not publicly insured (OR 0.75, IC95 0.62–0.90) were more often recruited via digital recruitment compared to telephone call recruitment ( 81 ). In the study from Elam et al. participants without medical insurance reported hearing about the program more often directly from a clinic doctor (23.9% vs. 2.8%; Holm-adjusted P < 0.0001) or nonmedical staff (34.4% vs. 16,7%; Holm-adjusted P = 0.0011) ( 56 , 57 ). Participants who had medical insurance significantly heard more often about the program via a friend, a flyer outside the clinic, the clinic website or social media or other ( 56 , 57 ). Collombon et al. aimed to recruit older low SEP citizens using the outreach avenues from the municipality and gyms located in low SEP areas ( 71 ). Significantly more low-educated participants were reached via personal invitation letters that were sent out by the municipality (N = 128/281, 45.6%) compared to the online newsletters and social media advertisements from gyms (N = 8/45, 17.8%) and regular social media advertisements (N = 9/71, 12.7%) (χ2 = 50.429, P < .001). Descriptive outcomes from Oldham et al. also show that promotion via well-known health institutes such as the British National Health System (NHS) website was more successful in reaching low SES participants compared to other promotion avenues ( 62 – 64 ). 4. Facilitation Ehmer et al. evaluated a facilitation delivery strategy ( 51 ). In this study no differences were found between the population’s public insurance status before and after implementation of safe spaces and devices at the clinic for mothers to enable access to their video consultation calls ( 51 ). Underpinning of delivery strategies Review of literature and consultations of stakeholders were used in studies (n = 10) for the design of implementation strategies or to identify and operationalize delivery strategies ( 48 , 49 , 56 – 59 , 62 – 66 , 71 , 76 – 78 , 80 , 82 ). Other studies (n = 23) did not report motivations for chosen delivery strategy designs. Scientific (n = 5) ( 48 , 49 , 71 , 76 – 78 , 82 ), experiential (n = 1) ( 65 ) or scientific and experiential (n = 4) ( 56 – 59 , 62 – 64 , 66 , 80 ) underpinnings were used. Researchers that used scientific publications for the design of delivery strategies consulted their own prior work (n = 6) ( 48 , 49 , 56 – 59 , 66 , 71 , 76 – 78 ), findings of other researchers (n = 6) ( 48 , 49 , 58 , 59 , 62 – 64 , 76 – 78 , 80 , 82 ) or theory (n = 2) ( 58 , 59 , 76 – 78 ). The literature and experiential knowledge from stakeholders were used for the design of implementation strategies and operationalization of delivery strategies. Several researchers (n = 4) consulted literature and involved stakeholders to improve the implementation strategy design ( 56 – 59 , 65 , 66 , 80 ). In these studies, the literature and stakeholders had influence on a tactical level, informing researchers’ methods for implementation of e-health interventions in specific contexts. Elam et al. and Thomas et al. had a permanent community advisory board that would advise the research team on recruitment and retainment strategies ( 56 , 57 , 66 ). Simione et al. were the only researchers using an implementation theory ( 58 , 59 ). The Consolidated Framework for Implementation Research (CFIR) ( 86 ) guided the researchers on how to engage stakeholders (families, healthcare professionals, and hospital leadership) and tailor the implementation strategies to suit the intervention context ( 58 , 59 ). Baggett et al. designed e-health referral processes and the according implementation strategies with healthcare professionals in three neonatal intensive care units ( 80 ). The use of dissemination and implementation literature was mentioned but not specified ( 80 ). Literature and stakeholders were used for identification and operationalization of delivery strategies in all the studies that reported a scientific and/or experiential underpinning (n = 10) ( 48 , 49 , 56 – 59 , 62 – 66 , 71 , 76 – 78 , 80 , 82 ). Literature and stakeholders were involved on a operational level, informing the researchers how to execute their delivery strategies. Researchers reviewed literature that described delivery strategies for similar interventions ( 58 , 59 , 62 – 64 , 80 , 82 ) or articles that discussed researchers’ learnings regarding delivery strategies for people with a low SEP ( 48 , 49 , 76 – 78 ). Collombon et al., Vaughan et al. and McEntee et al. reviewed their prior work to other interventions to determine the best outreach strategies for people with a low SEP ( 48 , 49 , 71 , 76 – 78 ). Stakeholders and literature were consulted for the content of promotional activities ( 56 , 57 , 62 – 66 , 71 ). Co-development of advertorials with target population or target population representatives was done to overcome language and cultural barriers. Literature was used to inform incentivization delivery strategies ( 48 , 49 , 62 – 64 , 76 – 78 ). McEntee et al. referred to the behavioural choice theory ( 87 ) to inform financial incentivization strategies ( 76 – 78 ). Researchers’ reflections upon delivery strategies Only authors (n = 10) that evaluated delivery strategies provided additional reflections upon delivery strategies ( 47 , 56 – 59 , 62 – 64 , 69 – 71 , 80 , 81 ). Five authors reflected on the importance of the integration of e-health in the practice and culture healthcare organizations ( 47 , 58 , 59 , 70 , 80 ). It was noted that clear task allocation for referral, stakeholder engagement within the healthcare organization, training of healthcare professionals, championship by designated employees, and technical and work process integration was deemed important for successful delivery of e-health ( 47 , 58 , 59 , 70 , 80 ). Other studies underlined the role of non-medical professionals in healthcare contexts ( 47 , 56 , 57 ). Garg et al. concluded that the presence of social workers who supported patients in e-health use increased the number of referrals to e-health and support by physicians ( 47 ). Elam et al. reflected upon the different reach effectivity outcomes between a free clinic and a FQHC while employing similar promotion strategies. Free clinics is the only clinic type that serve illegal citizens or American citizens who have a green card for less than five years, whereas FQHCs serve citizens who are eligible for a public health care insurance ( 56 , 57 ). Patients in free clinics were recruited more often via non-medical staff such as translators who explained the intervention to people with limited English language skills ( 56 , 57 ). Several authors reflected upon culturally-, skill- or need adapted, personal, and prolonged delivery strategy approaches ( 56 , 57 , 62 – 64 , 69 – 71 , 81 ). Elam et al, Miller et al., and Oldham et al. mentioned the importance of the use of culturally and language adapted ( 56 , 57 , 70 ) and literacy skill adapted ( 62 – 64 ) promotional and information materials in their research. Alcaraz et al. suggested that profiling of socio-economic groups’ needs and channel use in social service and other recruitment settings could improve recruitment strategies ( 79 ). Baker et al. and Collombon et al. noted reflections concerning the personal approaches employed during e-health delivery ( 69 , 71 ). Baker et al. observed that attempts to organize at-home appointments during COVID-19 pandemic scared potential participants as they were afraid of contracting COVID-19 and allowing unfamiliar people at home ( 69 ). Collombon et al. found that personal invitation letters sent out by the municipality contributed to higher participation rates, additionally recruitment via family and friends was reported, which was a recruitment strategy that evolved during the study ( 71 ). Collombon et al. suggested that both recruitment strategies should be investigated further. Baker et al. and Oldham et al. noted cumulation of participant recruitment due to long periods of promotional activity ( 62 – 64 , 69 ). Oldham et al. advises the use of multiple recruitment methods, including targeted approaches for underrecruited groups and monitoring of the demographic composition during the recruitment phase ( 62 – 64 ). Additionally, Oldham et al. stated that people with a low SEP via general practitioners was promising but limited in their study due to COVID-19 lockdowns ( 62 – 64 ). Table 3. Overview of the studies (n = 12) that evaluated delivery strategies. Outcomes of evaluations are categorized upon the delivery strategy components. Studies were deemed significant if there was a p < 0.05 outcome for differences in reach. between included conditions in the study. Elam et al. and Ehmer et al. both performed two evaluations, these evaluations are referred to as StudyID 7 and 7a, and, 10 and 10a. Insert Table 3 here a Statistics Index of Relative Socio-economic Disadvantage Discussion This review presented an overview of e-health delivery strategies aimed at engaging individuals with a low socioeconomic position (SEP). We used an a priori adjusted version of the marketing mix model to define the mechanisms of delivery strategies ( 34 ). The adjusted model defines five delivery strategy components: place, point of contact, promotion, facilitation and incentive. Almost all delivery strategies identified in this review consisted of more than one delivery strategy component. Place and point of contact were the most often used and combined delivery strategy components. Those studies that evaluated their delivery strategies revealed that place, point-of-contact and, promotion strategy components can have a significant effect on reach effectivity. E-health delivery in settings commonly accessed by people with a low SEP, offline promotion and recruitment through trusted authorities, proved to be more effective compared to, respectively, delivery in less familiar settings, online promotion and recruitment through organizations and people with less authority or self-recruitment. Evidence and researchers’ reflections also suggests that adoption of e-health and e-health delivery strategies by healthcare professionals and organisations are relevant in reaching people with a low SEP. Nevertheless, the evidence available is insufficient and too scattered to state solid conclusions. Additionally, most studies were e-health intervention studies, implying that delivery strategies were used for recruitment in a research context, which is different from e-health delivery in a real life context. Our results show that delivery strategies often consist of multiple components, of which place and point-of-contact delivery strategy components are employed and combined most often. The location, person and medium through which e-health delivery takes place is important for strategies to be effective. The importance of the delivery of health interventions in contexts and by people that are familiar for people with a low SEP is also found in other studies ( 20 , 23 , 88 , 89 ). Bonevski’s (2014) literature review finds that in clinical trials low SEP participants were often sampled via location or network targeted sampling or through community organizations ( 88 ). For recruitment, researcher – community partnerships and health professional support for the study were often employed in recruitment ( 88 ). A literature review by Al-Dhahir et al. focused on the barriers and facilitators of eHealth-based lifestyle intervention programs for people with a low SEP. Al-Dhahir described that personal e-health delivery was most promising in reaching people with a low SEP ( 20 ). Successful delivery of e-health to people with a low SEP involves understanding and tailoring delivery strategies to the context of people with low SEP. The lack of real-world evaluations limits understanding of the feasibility and effectiveness of e-health delivery strategies. Most findings in this review are based on RCTs, which differ significantly from real-world contexts in terms of implementation and delivery ( 90 ). Limited digital health skills and limited access to devices are main barriers in e-health access and use and is often associated with people with a low SEP ( 8 , 91 – 95 ). Understanding how to deliver e-health to people with limited digital health skills and limited access to devices is crucial for equitable access to digital health. E-health evaluation studies often address barriers such as limited material access or digital skills, however this does not always reflect real-world feasibility. Some studies exclude individuals with low digital literacy or limited access to devices, preventing insight into whether the delivery strategies are effective for this population. Others provide devices and technical support to facilitate participation, but this may inflate the apparent effectiveness of delivery strategies, as such support might not be feasible outside of funded trials. RCTs with larger budgets are more likely to overcome recruitment challenges and avoid early termination ( 96 ). These studies are more likely to be published, potentially skewing the evidence base toward strategies that are resource-intensive and less generalizable. This creates a biased understanding of what works in both trial and real-world settings. Gitlin and Czaja argue that findings from real-world contexts are essential to inform future intervention research, enhancing the ecological validity of outcomes ( 97 ). Future research should therefore assess the reach and retention of implemented e-health applications and enabling services, to better understand which delivery strategies are effective, for whom, and under what conditions. These insights can guide both future research and practical implementation efforts. Effectivity of e-health delivery strategies was studied via reported effectivity, scientific and experiential underpinnings and researchers’ reflections upon delivery strategies. The results point towards the importance of the implementation of e-health in health organisations. Other scholars describe that adoption of e-health by professionals and organizations is crucial for patients’ access to e-health ( 98 – 100 ). According to Schiffelaar et al. (2025) a digital health transition in hospitals requires cultural, practical, political, and financial alignment throughout the organization, high-qualitative technical solutions that integrate within technical infrastructures and opportunities for staff and patients to access resources and training for e-health access and use ( 99 ). The Nonadoption, Abandonment, Scale-up, Spread and Sustainability (NASSS) framework by Greenhalgh et al. and the Consolidated Framework for Implementation Research (CFIR) by Damschroder et al. describe the importance of the context of direct end-users and the organizations’ capacity and readiness to implement, change, and innovate for successful and sustainable implementation of interventions ( 86 , 100 ). Design thinking methods such as co-creation, prototyping and human-centred design are often used in digital health intervention research with the aim to involve end-users and the context to improve the intervention ( 101 ). However, Bodell et al. finds that researchers involve stakeholders to address health outcomes and user-friendliness of interventions but fail to involve stakeholders in later phases of implementation; the embedding in the organizational context and in patients’ lives ( 101 ). Bodell’s findings align with the results in our review; five studies consulted stakeholders and one study consulted implementation theory for the design of delivery strategies. Future research should consider involvement of direct end-users, that include patients, staff, caregivers and healthcare professionals, and organizations in the design of delivery strategies. The majority of the studies were conducted in the United States (US). The US healthcare system has specific safety-net clinics or not-for-profit clinics that only serve those who live in disadvantaged circumstances ( 102 , 103 ). The high poverty rate and the limited access to healthcare in the US cause people with a low SEP to frequent these clinics, providing a model setting for the delivery of e-health ( 102 – 104 ). The learning from these findings is that delivery of e-health to people with low SEP in specific low SEP (healthcare) contexts can be effective. This setting is, however, unique for the US healthcare system and results might be less generalizable to other countries and other healthcare systems. This poses the question whether other countries can identify similar places or adhere to other methods to reach people with a low SEP. Insights in how e-health is effectively delivered to people with low SEP in other countries and other healthcare systems is needed to inform research and practice in e-health delivery in other settings. This literature review has strengths and limitations. A strength of this study was that we searched multiple databases to ensure the identification of all potential relevant articles. Furthermore, the results of this study allowed for a detailed overview of the delivery strategies used specifically to reach people with a low SEP. Additionally, articles were screened and selected by the primary author and two secondary reviewers independently to minimise selection bias. A limitation of this study was the absence of grey literature. We expect that different delivery strategies have been tested in practice but have not been published in scientific literature, bearing findings that were not discussed or documented in scientific literature. Additionally, the critical appraisal showed risk for selection bias. Critical appraisals are constructed to appraise evaluation studies that evaluate medication treatments in which blinded approaches for both patient and administrator are highly valued and feasible via placebo medications. Blinded approaches are not feasible in e-health evaluation studies; therefore, critical appraisal scores are less high. Implications and future research This literature review reveals a knowledge gap in what the mechanisms of delivery strategies are and how these strategies can support e-health introduction for people with a low SEP in real world contexts. Although the current literature provides valuable insights, the evidence available is insufficient to create a solid understanding, and by extension theory, about the mechanisms of delivery strategies. There are too few studies that have evaluated delivery strategies and studies evaluated different delivery strategies in a variety of contexts, study designs and e-health interventions. Additionally, there are no or very few studies that evaluated delivery strategies that had facilitation or incentive components; even though, almost half of delivery strategies employed these components. There was only one paper describing delivery of e-health enabling services. Other research underlines the importance of providing resources for low SEP populations to enable participation ( 105 , 106 ), which provides an argument to study the reach of facilitation and incentive e-health delivery strategies and evaluate the reach of e-health enabling services. Future research should aim to create a greater understanding of mechanisms of e-health delivery strategies in real world settings. Successful e-health interventions consist of an effective and accessible application and an inclusive implementation strategy. Adjustments of delivery strategies to the context of people with a low SEP requires effort but is vital for recruitment and retention ( 23 , 28 , 88 , 107 ). Andersen (1995) argues that the adaptability of populations’ abilities to access healthcare are low and that healthcare services should be designed and implemented in differentiated ways to realize equitable access for different groups ( 107 ). Additionally, e-health implementation strategies need to consider the professional and organizational context. Bodell et al. argue that the field of e-health implementation should draw upon both positivist and constructivist epistemologies ( 101 ). Health science traditionally adopts a positivist approach, aiming to assess the effects of interventions through systematic, rigorous methods that seek to minimize contextual influences or bias. In contrast, implementation science is grounded in a constructivist perspective, focusing on understanding how context shapes both the implementation process and the effectiveness of interventions ( 101 ). Successful e-health interventions require the integration of knowledge from both paradigms. Future e-health intervention research should therefore conceptualize implementation as an integral part of the intervention itself and place greater emphasis on understanding the influence of end-user, professional, and organizational contexts. Results show limited use of scientific and experiential underpinnings, and few reflections upon employed delivery strategies. Although there is emphasis on equitable recruitment of people with a low SEP in health research, multiple literature reviews found that authors report too little about delivery strategies ( 88 , 89 , 104 , 108 ). Similarly to our literature scholars found that authors lack in report about the design of delivery strategies, lack in performing statistical analysis and scarcely share reflections upon whether the delivery strategy was successful ( 88 , 89 , 104 , 108 , 109 ). All papers that evaluated an e-health delivery strategy were published after 2020, this might indicate that e-health delivery and reach is becoming an increasingly relevant topic within the field of digital health. To maximize future knowledge synthesis, future research should adhere to systematic reporting and evaluations concerning delivery strategies to create a stronger knowledge base. Conclusion There remains a significant knowledge gap regarding which delivery strategies are most effective in reaching individuals with low socio-economic positions (SEP) via e-health interventions in real-world contexts. Among the various components of delivery strategies, place and point-of-contact are the most frequently employed and combined. The majority of the literature focuses on e-health delivery strategies within clinical trial settings, with limited reporting on the use of scientific or experiential knowledge in the design of these strategies. Existing evaluation studies provide some evidence supporting the effectiveness of place, point-of-contact, and promotion strategies in reaching low SEP populations. Still, this evidence is insufficient and too scattered to state solid conclusions in terms of reach effectivity. Despite these limitations, the current body of evidence offers a valuable foundation for further exploration and evaluation of delivery strategies. We are at the beginning of opening up a new area of research. The success of equitable e-health interventions depends on the effectiveness of e-health applications and inclusive and context-sensitive implementation strategies - including delivery strategies. Given the tremendous pace at which healthcare access and use is becoming dependent on e-health, there is a great urgency to develop this area of research. Researchers are encouraged to view implementation as an integral component of the intervention and should consider how the contexts of end users, healthcare professionals, and organizations shape the delivery and uptake of e-health interventions. Future research should aim to understand the mechanisms by which e-health delivery strategies can effectively engage people with low SEP across diverse healthcare systems and real-world conditions. Abbreviations RCT Randomized Controlled Trial USA United States of America UK United Kingdom EHR Electronic Health Record FQHC Federally Qualified Healthcare Centre BMI Body Mass Index SEP Socioeconomic Position NICU Neonatal Intensive Care Unit LMBS Lucille Margot Bartha Standaar JM Jippe Miedema LS Lieke Steendam Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials Included papers, the extracted data, critical appraisal and a list of all the articles that were included for full-text screening can be found in the Supplementary File 1, 2 and 3. Competing interests The researchers report no conflict of interest. Funding The Ministry of Public Health, Wellbeing and Sport funded this research. Funders were not involved and did not have influence on the research design and outcome. Authors' contributions LMBS contributed to the conception, the design of the literature review, the analysis and interpretation of data and the writing of the paper. RvdV, RDF and LHDvT contributed to the conception and the design of the literature review and provided extensive feedback. KL provided extensive feedback. All authors approve of the submitted version. 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J Autism Dev Disord. 2024;54(6):2307–21. Treweek S, Pitkethly M, Cook J, Fraser C, Mitchell E, Sullivan F et al. Strategies to improve recruitment to randomised trials. Cochrane Database Syst Reviews. 2018(2). Tables Tables 1 to 3 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1.xlsx Table2.xlsx Table3.xlsx Supplementaryfile1.xlsx Supplementaryfile2.xlsx Supplementaryfile3.xlsx Appendix1SearchQueries.xlsx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 13 May, 2026 Reviews received at journal 11 May, 2026 Reviewers agreed at journal 02 May, 2026 Reviews received at journal 22 Apr, 2026 Reviewers agreed at journal 13 Apr, 2026 Reviewers invited by journal 04 Feb, 2026 Editor invited by journal 27 Jan, 2026 Editor assigned by journal 24 Jan, 2026 Submission checks completed at journal 24 Jan, 2026 First submitted to journal 21 Jan, 2026 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. 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04:22:37","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":50603,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8659891/v1/a20746d254fb46272b1e80c3.xlsx"},{"id":101753566,"identity":"c4aa611c-e0ec-4794-bdbd-5856fc6675d1","added_by":"auto","created_at":"2026-02-03 10:40:14","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":14836,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix1SearchQueries.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8659891/v1/d732035c689d41325f6b0f91.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"A systematic literature review to identify delivery strategies of digital health for low SEP populations","fulltext":[{"header":"Background","content":"\u003cp\u003eAs digital health becomes increasingly integrated into healthcare systems, concerns about equitable access and utilization are raised (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Digital health, or e-health, is the use of information and communications technologies in health care to manage illnesses and health risks and to promote wellbeing (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). E-health includes the use of wearable devices, mobile health, telehealth, health information technology, and telemedicine (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Although access to digital devices and the internet is increasing, less frequent and diverse use of e-health is observed among people with a lower socio-economic position (SEP) (\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEquitable delivery of e-health has proven to be difficult (\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Previous research shows that people with low SEP have diverse barriers in access and use of e-health (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). These needs include improvement of digital health skills, language skills, knowledge about the healthcare system, and awareness about e-health and its potential value (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Scaioli et al. (2024) found that the lack of awareness about the existence and value of a patient portal is associated with low SEP (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Researchers underline the role of organizations in realizing inclusive implementation strategies and accessible e-health applications to facilitate equitable access to e-health (\u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). O\u0026rsquo;Connor et al. (2016) describes that awareness, implementation strategies, support and promotion are crucial for engagement with digital health (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Although research indicates what factors are important in the reach of people with a low SEP (\u003cspan additionalcitationids=\"CR17 CR18 CR19\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), there is limited clarity on what strategies exist to deliver e-health to people with a low SEP.\u003c/p\u003e \u003cp\u003eSuccessful approaches in reaching people with a low SEP is studied in other health fields (\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Evidence shows that tailored delivery strategies and community engagement approaches are effective in reaching people with a low SEP (\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). A literature review by O\u0026rsquo;Mara-Eves (2015) found that delivery of public health interventions for disadvantaged groups via community engagement approaches were effective to improve health outcomes (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Approaches in which community peers were involved in the delivery of the public health intervention were particularly effective compared to interventions that empower the community or interventions that involved members in the design of the intervention (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). However, there is limited knowledge about what strategies successfully reach and introduce e-health to people with a low SEP (\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSuccessful access and use of e-health requires inclusive implementation strategies. Implementation is defined by Palinkas \u0026amp; Soydan (2012, p.10) as: \u0026ldquo;\u003cem\u003ea purposefully designed set of actions for the application of a purposefully designed program or intervention to cause change\u003c/em\u003e\u0026rdquo; (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). The design and execution of e-health delivery strategies is one of the aspects of implementation. Insights into what e-health delivery strategies are employed and whether these are effective for people with a low SEP is vital for realizing equitable access to e-health in the real world context (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). The aim of this literature review is to provide insight into what e-health delivery strategies have been used to reach people with a low SEP. Secondly, it aims to gain insight in the effectivity in reach of these delivery strategies. Furthermore, this literature review focuses on whether the identified delivery strategies were derived from experiential knowledge or earlier scientific research. Such underpinnings might provide insight into why and how delivery strategies do or do not work. In this literature review, an e-health delivery strategy is defined as: a strategy employed to facilitate the use of e-health or e-health enabling services. This literature review is registered in the Prospero database under the registration number: CRD42024572294.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSearch strategy\u003c/h2\u003e \u003cp\u003eFive databases were searched on 07-06-2024 electronically to identify relevant literature: Embase.com, Pubmed, PsycINFO, Web of Science and Sociological Abstracts. The key search terms were built around the concepts: (low) socio-economic populations, e-health and delivery strategies of products and services. A complete overview of the search terms can be found in Appendix 1. Search terms were constructed in consultation with two librarians.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Design\u003c/h3\u003e\n\u003cp\u003eThe PRISMA guidelines (2020) were used to structure this literature review and to ensure a systematic and rigorous analysis (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). The PRISMA checklist can be found in Appendix 2. The software package Rayyan was used as a tool for manual detection and removal of duplicates and screening. There was no use of AI technology. One researcher (LMBS) and two reviewers (JM and LS) were involved in the screening process. All involved had at least a bachelor degree in a health related field and were experienced in conducting research. Screening based upon title and abstract, and full-text screening were done independently. In the title and abstract screening phase, LMBS screened all articles and JM screened 3012/5127 (59%) articles. In the full-text screening phase, LMBS and LS both screened all papers. In both screening phases the researchers held regular meetings to discuss conflicts and find consensus. When consensus between the first and second reviewer could not be reached during the screening phase, a third researcher (LvT or RvdV) was consulted to resolve the conflict. The data extraction form was developed and pilot tested by LMBS. RvdV, LvT and LS reviewed the data extraction form and provided suggestions for improvement. LMBS extracted the data from all the papers, LS extracted the data from 20% of the papers. Conflicts in data extraction were resolved between LMBS and LS. LS conducted the critical appraisal of all included articles, JM appraised 11/35 (31%) of the included papers. Conflicts in the critical appraisal were resolved by LMBS by rereading the articles.\u003c/p\u003e\n\u003ch3\u003eEligibility\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003ePopulation\u003c/h2\u003e \u003cp\u003eStudies were included when the delivery strategy was aimed at a low SEP population. To allow us to gain broader insight into SEP, three indicators were included: education, income and the socio-economic status of the living area. Education, income and socio-economic status of the living area are classic SEP indicators (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). It was expected that most research that described or evaluated e-health delivery strategies used one of these indicators to address SEP. Studies either had eligibility criteria that reflected a low SEP by one of the three previously mentioned SEP indicators or the study was held in a low SEP setting. If the study was conducted in a low SEP setting, demographics needed to provide insight into either education, income or neighborhood status of the study sample to confirm that the intervention was targeted to people with a low SEP. Income could also be derived from insurance status, type of employment such as blue-collar or white-collar jobs, or, attendance to specific clinics when eligibility to access these services requires a low income.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eIntervention\u003c/h3\u003e\n\u003cp\u003eThe papers revolved around an e-health application or e-health enabling service. An e-health application was defined as follows: \u003cem\u003e\u0026ldquo;The use of information and communications technology (ICT) in support of health and health related fields, including health care services, health surveillance, health literature, and health education, knowledge and research.\u0026rdquo;\u003c/em\u003e (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Additionally, SMS based interventions were also included as SMS involves the use of a mobile phone. Included articles concerned both digital health care applications and digital public health applications (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Digital health care applications aim for individual improvement of health, for example a diabetes management application or a patient portal, whereas digital public health applications aim to improve health on a population level, such as an COVID-19 tracking application or public health website (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSupport services are services that are tailored to enable people to adopt e-health. These services can either enable the individuals from vulnerable groups to gain access and use to e-health or improve the inclusivity of surroundings and services to be able to service vulnerable groups better. Examples of services that enable vulnerable individuals are: skills education, access to devices or increasing awareness around e-health.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDelivery strategy \u0026amp; delivery strategy components\u003c/h2\u003e \u003cp\u003eThe papers described a delivery strategy which was employed to facilitate the use of e-health or e-health enabling services. A delivery strategy can consist of one or multiple components that contribute to the reach of an e-health application or e-health enabling service. This literature review defined five delivery strategy components: place, point of contact, facilitation promotion and, incentive. The definitions of the delivery strategy components were derived from the marketing mix model described by McCarthy (1964) (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). The marketing mix model described the 4 P\u0026rsquo;s: product, price, place and promotion (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). As this review\u0026rsquo;s focus is to understand how low SEP populations are reached and how e-health is delivered, there was no focus on the product itself. McCarthy\u0026rsquo;s concept of \u0026lsquo;place\u0026rsquo; encompassed place, the point-of-contact and facilitation. In our review those three elements of \u0026lsquo;place\u0026rsquo; are discussed separately. McCarthy\u0026rsquo;s concept of price was interpreted as \u0026lsquo;incentive\u0026rsquo; in this review, as digital health is often offered for free or as part of users\u0026rsquo; healthcare plans. Digital health use is, therefore, often stimulated via other means rather than the price of the product. The delivery strategy components were used a priori as a tool to categorize the actions executed as part of delivery strategies.\u003c/p\u003e \u003cp\u003ePlace: the location where people can access the product. This includes the physical location but also the accessibility of the location in terms of opening hours and accessibility via (public) transport. Online products don\u0026rsquo;t have a \u0026ldquo;place\u0026rdquo; as online services are not bound to a location or opening hours. Example of an intended delivery strategy: a mobile health clinic in the center of a low socioeconomic neighborhood that provides information and support for use of e-health.\u003c/p\u003e \u003cp\u003ePoint of contact: Organizations and people that provide information, goods and services to facilitate the delivery of the product. Point of contact can be particularly important when the person involved is someone with specific authority or skill, for example health care professionals or the municipality.\u003c/p\u003e \u003cp\u003ePromotion: All the activities that are intended to convey the message about the product or the place, point of contact or facilitation of the product. The following are considered promotion activities: online and offline advertisement, promotional items, promotional events, and, face-to-face selling.\u003c/p\u003e \u003cp\u003eFacilitation: The provided information, goods and support that enable use of the product. Examples can be: an helpdesk that aids potential clients to use an e-health application or facilitation of devices and data plans.\u003c/p\u003e \u003cp\u003eIncentive: the efforts done to stimulate potential users to use e-health or the e-health enabling service. Incentives can be financial, time-based, leisure, material or mental. Examples are: free health check, free gym membership or, coupons for a grocery store.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eInclusion criteria\u003c/h3\u003e\n\u003cp\u003eThe following inclusion criteria had to be met to be included in the review. The papers described the delivery strategy, the description had to include who performed the delivery, what the delivery strategy entailed and how the delivery strategy was performed. The study objective concerned the evaluation of an e-health application, e-health enabling service or, e-health delivery strategy with the aim to serve people with a low SEP. Demographics reported SEP by education, income or socio-economic status of the living area of the target population. Included study designs were: randomized controlled trail (RCT), quasi-experimental studies, mixed-method studies and observational study designs. Papers were required to be peer-reviewed and published on 01-01-2014 and onwards and written in the English or Dutch language. The research took place within Western societies, namely: Countries in Europe, the United States of America, Canada, Australia or New-Zealand.\u003c/p\u003e\n\u003ch3\u003eExclusion criteria\u003c/h3\u003e\n\u003cp\u003eQualitative and meta study designs were excluded. Papers that were protocols or pilot studies for future RCTs were excluded as these strategies were not executed on a full scale.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eData extraction\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003eOverview of strategies\u003c/h2\u003e \u003cp\u003eFor all papers the following data were extracted and presented in Supplementary file 1. In case papers referred to other published work for more information about the data of interest, this literature was used to gain more insight. Additional references were noted in the tables and appendices.\u003c/p\u003e \u003cp\u003eBibliographic information: title, first author, year of publication, doi;\u003c/p\u003e \u003cp\u003eE-health or e-health enabling service: e-health application or e-health enabling service, type of e-health (web application, mobile application, electronic health record, video communication, wearable, domotics, robotics, medical integration networks, general integration networks, business intelligence and big data solutions and telehealth) (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e) and, description primary health outcome;\u003c/p\u003e \u003cp\u003eContext of study: type of study, delivery strategy (described/evaluated), country of study and, description of the research setting;\u003c/p\u003e \u003cp\u003eIntervention: description of the delivery strategy, category of stakeholders involved in the delivery strategy (research, healthcare, education, social services, community, commercial, citizens), description of roles of the stakeholders, components of delivery strategy (X if applicable): place, point of contact, promotion, facilitation and incentive; authors reflections upon delivery strategies;\u003c/p\u003e \u003cp\u003ePopulation: SEP selection criteria (individual, clinic or area characteristics), description of target population, description of inclusion criteria, description of exclusion criteria, information available of SEP variables of study participants (education, income, neighborhood), number of participants at baseline and, demographic data on socio-economic variables.\u003c/p\u003e \u003cp\u003eThe types of e-health are derived from an e-health application overview created by Krijgsman \u0026amp; Klein-Wolterink (2012) (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). The category \u0026lsquo;telehealth\u0026rsquo; was added and represented all text-message based interventions. If the paper described and evaluated the reach or described scientific or experiential underpinnings of the delivery strategy, additional data was extracted.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eReach\u003c/h2\u003e \u003cp\u003eReach was defined by the number of people reached by the delivery strategy. Reach effectivity was measured by studies if the results showed a comparative analysis of the number of people reached between delivery strategies, between contexts that employed similar de strategies or between time points. Evidence for reach effectivity was found when the comparative analysis between delivery strategies was significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Data that described the reach per delivery strategy component or provided evidence for reach effectivity was extracted. Included data points for evaluation of delivery strategies: statistical analyses used, description of outcome measurements, the aim of the evaluation study, description outcome, exact outcome, and outcome significant (yes/no).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eScientific and experiential underpinning of delivery strategies\u003c/h2\u003e \u003cp\u003eData describing scientific or experiential underpinnings were systematically extracted from the articles. Scientific underpinning refers to theories or findings about the design of delivery strategies that were published in scientific literature. Experiential underpinnings refer to knowledge derived from experience from researchers or other stakeholders that was used to design the delivery strategy. Experiential underpinnings might be published in scientific literature, especially if stakeholders were involved during the design of the RCT or other prior conducted research. If this is the case, the underpinning is considered both scientific and experiential. Included data points for scientific or experiential underpinnings: scientific or experiential underpinning used (yes/no, if yes, experiential/scientific/experiential and scientific), description scientific or experiential underpinning, and sources scientific underpinning ((type of scientific underpinning: theory (name theory), scientific publications, prior research author), (focus: implementation, delivery, incentivization, or advertisement), doi or citation).\u003c/p\u003e \u003cp\u003eReport on reach effectivity, and used scientific and experiential underpinnings for delivery strategies might be susceptible to missing values as it\u0026rsquo;s not common practice to discuss these findings in evaluation studies. Researchers might have the data to evaluate reach effectivity but did not include these results. All researchers used a delivery strategy to conduct their research and it is possible that researchers made decisions based upon knowledge or experience that was not described in the paper. When these data points were missing, the assumptions were made respectively: no evaluation of reach effectivity was performed, and no scientific or experiential underpinnings were used.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eData synthesis\u003c/h2\u003e \u003cp\u003eFirst, papers were described upon study characteristics: type of study, setting, target group, type of e-health application, target health outcome and, how studies aimed to recruit a low SEP population, either via individual, clinic or area characteristics. Overview of papers\u0026rsquo; characteristics are presented in Table\u0026nbsp;1. Secondly, an overview was created of the delivery strategy components and presented in Table\u0026nbsp;2. An overview of the stakeholders involved in the delivery strategy, the delivery strategy components and, theoretical and experiential underpinnings were described. Thirdly, the communalities and irregularities within each delivery strategy were assessed. Assessment was done via grouping studies by context, stakeholders involved and, the mechanisms of the delivery strategies used, including reported reach effectivity derived from the evaluation studies. Fourthly, the results were assessed across components by reviewing the occurrence of components, the combinations of components and whether studies that used scientific or experiential underpinnings had characteristics in common. Fifthly, an overview of the studies that described or evaluated reach was described and presented in Table\u0026nbsp;3.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eQuality Appraisal\u003c/h2\u003e \u003cp\u003eJoanna Briggs Institute (JBI) Critical appraisal tools for RCT, cross-sectional studies, quasi-experimental studies and cohort studies were applied to review the quality of the literature, see Supplementary file 2 for the critical appraisal including scores per question (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). Studies were scored by counting the number of questions that were answered with yes divided by the total number of questions. Longitudinal studies were appraised using the checklist for analytical cross sectional studies (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). Most studies included reported but did not evaluate e-health delivery strategies. The quality appraisal of these studies evaluate the aim of the study as is, which was the effect of the e-health intervention itself and not the delivery strategy. Articles that had a score of 75% or more were deemed of high quality. Articles were not excluded based upon quality appraisal.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eStudy selection\u003c/h2\u003e \u003cp\u003eThe screening process is described in detail in the PRISMA flowchart in Fig.\u0026nbsp;1. The search term yielded 7361 articles. After duplicate removal, 5127 articles were included. LMBS and JM screened 3014 (59%) articles on title and abstract independently. Cohen\u0026rsquo;s kappa was 0.56 which is considered a moderate agreement, percentage of agreement was 96% (2903/3014) (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Thereafter, LMBS screened all remaining articles which resulted in 202 articles that were considered for full text screening. Additionally, LMBS screened three literature reviews (\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e) that were identified during the title and abstract screening. This yielded 7 more articles. LMBS and LS independently screened the full text of all 209 articles. A list of all the full-text screened articles can be found in Supplementary file 3. After screening on the eligibility criteria 35 articles were included. Cohen's kappa was 0.64, which is considered a substantial agreement, percentage of agreement was 89% (186/209) (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). The 35 included articles described 33 research projects.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eCritical appraisal\u003c/h2\u003e \u003cp\u003eCritical appraisal revealed that 14 studies had a quality score of 75% or higher, these studies were considered to be of high quality. Risk for bias related to selection and administration was identified in many studies (n\u0026thinsp;=\u0026thinsp;19), all considering the blinding of participants or administrators. Furthermore, studies (n\u0026thinsp;=\u0026thinsp;12) failed to identify and manage confounding factors. A detailed overview can be found in Supplementary file 2.\u003c/p\u003e \u003cp\u003eInsert Fig.\u0026nbsp;1 here\u003c/p\u003e \u003cp\u003eFigure 1. PRISMA Flowchart\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eGeneral study characteristics\u003c/h2\u003e \u003cp\u003eThe search strategy resulted in the inclusion of 35 papers that described 33 research projects (\u003cspan additionalcitationids=\"CR43 CR44 CR45 CR46 CR47 CR48 CR49 CR50 CR51 CR52 CR53 CR54 CR55 CR56 CR57 CR58 CR59 CR60 CR61 CR62 CR63 CR64 CR65 CR66 CR67 CR68 CR69 CR70 CR71 CR72 CR73 CR74 CR75 CR76 CR77 CR78 CR79 CR80 CR81 CR82 CR83 CR84\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e). An overview of the characteristics of the papers can be found in Table\u0026nbsp;1. Table\u0026nbsp;1 presents a subset of the following data: type of study, e-health type, primary health outcome, description target population, SEP selection criteria. Majority of the included papers were RCT\u0026rsquo;s (n\u0026thinsp;=\u0026thinsp;19) (\u003cspan additionalcitationids=\"CR44 CR45 CR46 CR47 CR48 CR49\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan additionalcitationids=\"CR53 CR54\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan additionalcitationids=\"CR74 CR75 CR76 CR77 CR78\" citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan additionalcitationids=\"CR84\" citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e). Furthermore, the following study designs were identified: cross sectional (n\u0026thinsp;=\u0026thinsp;8) (\u003cspan additionalcitationids=\"CR59\" citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan additionalcitationids=\"CR81\" citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e), longitudinal (n\u0026thinsp;=\u0026thinsp;4) (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e), cohort (n\u0026thinsp;=\u0026thinsp;2) (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e), and quasi-experimental (n\u0026thinsp;=\u0026thinsp;2) (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e). Eight papers (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan additionalcitationids=\"CR57 CR58\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e) concerned secondary analyses from RCT studies. Twelve papers (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan additionalcitationids=\"CR57 CR58 CR59\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan additionalcitationids=\"CR70\" citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e) evaluated the reach of the applied delivery strategy. Other papers (n\u0026thinsp;=\u0026thinsp;23) only described the delivery strategy as part of the research design. Most studies were conducted in the United States (US) (n\u0026thinsp;=\u0026thinsp;29), other countries were Australia (n\u0026thinsp;=\u0026thinsp;3) (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e), the UK (n\u0026thinsp;=\u0026thinsp;2) (\u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e) and the Netherlands (n\u0026thinsp;=\u0026thinsp;1) (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e). Most studies were published between 2020\u0026ndash;2024 (n\u0026thinsp;=\u0026thinsp;25) (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan additionalcitationids=\"CR47 CR48 CR49 CR50\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan additionalcitationids=\"CR57 CR58 CR59 CR60 CR61 CR62 CR63 CR64\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan additionalcitationids=\"CR69 CR70 CR71 CR72 CR73 CR74 CR75\" citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan additionalcitationids=\"CR79 CR80\" citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e) .\u003c/p\u003e \u003cp\u003eThe majority of papers (n\u0026thinsp;=\u0026thinsp;34) focused on an e-health application. Different types of e-health were studied: mobile applications (n\u0026thinsp;=\u0026thinsp;10), web applications (n\u0026thinsp;=\u0026thinsp;9), wearables (n\u0026thinsp;=\u0026thinsp;6), telehealth (n\u0026thinsp;=\u0026thinsp;11), video communication (n\u0026thinsp;=\u0026thinsp;6) and electronic health records (n\u0026thinsp;=\u0026thinsp;4). Alcaraz, Vereen \u0026amp; Burnham evaluated the reach from an e-health enabling service (n\u0026thinsp;=\u0026thinsp;1): a national-wide information and referral system, that aimed to connect people with a low SEP with resources to meet their basic human needs (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e). Papers focused on the management of disease (n\u0026thinsp;=\u0026thinsp;15): diabetes, COVID19, asthma, dementia, glaucoma, and children\u0026rsquo;s development. Twelve papers concerned behaviour-related health topics, with the focus on weight, physical activity, and alcohol consumption. Five papers focused on healthcare processes: patient screening to identify needs and family history, and access to care. Three papers focused on mental health related conditions.\u003c/p\u003e \u003cp\u003eThe papers\u0026rsquo; range in number of participants was n\u0026thinsp;=\u0026thinsp;33\u0026ndash;32.523 (mean: 2.259) (\u003cspan additionalcitationids=\"CR43 CR44 CR45 CR46 CR47 CR48 CR49 CR50 CR51 CR52 CR53 CR54 CR55 CR56 CR57 CR58 CR59 CR60 CR61 CR62 CR63 CR64 CR65 CR66 CR67 CR68 CR69 CR70 CR71 CR72 CR73 CR74 CR75 CR76 CR77 CR78 CR79 CR80 CR81 CR82 CR83 CR84\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e). Target populations were mainly adults except for two papers which included: all residents including children (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e) and adolescents and their parents (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e). Some papers focused on specific adult groups: parents (n\u0026thinsp;=\u0026thinsp;11), adults from ethnic minority populations (n\u0026thinsp;=\u0026thinsp;5), and older adults (n\u0026thinsp;=\u0026thinsp;2) or pregnant women (n\u0026thinsp;=\u0026thinsp;1). Staples et al. and McEntee et al. recruited adults with a high and low SEP (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e). Danila et al. recruited older adults and adults with a low SEP (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e). Eight papers enacted individual-bound low SEP eligibility criteria or recruited participants in low SEP-bound contexts (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan additionalcitationids=\"CR46 CR47 CR48\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan additionalcitationids=\"CR76 CR77\" citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e). Other papers (n\u0026thinsp;=\u0026thinsp;27) recruited participants in low SEP contexts: clinics that predominantly serve low SEP populations or areas where predominantly low SEP populations live or visit. Twelve papers had in- or exclusion criteria based upon having digital skills or having access to devices and text- or data plans (\u003cspan additionalcitationids=\"CR53 CR54\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63 CR64\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan additionalcitationids=\"CR71 CR72\" citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e). Nelson et al. offered training to use the intervention as part of their recruitment procedure, where participants that could not successfully use the intervention after training were excluded (\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable\u0026nbsp;1.\u003c/b\u003e Summary of paper characteristics (N\u0026thinsp;=\u0026thinsp;35).\u003c/p\u003e \u003cp\u003eInsert Table\u0026nbsp;1 here.\u003c/p\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003e Only the data concerning the United Kingdom population was included in this literature review\u003c/p\u003e \u003cp\u003e \u003csup\u003eb\u003c/sup\u003e RCT: Randomized Controlled Trial\u003c/p\u003e \u003cp\u003e \u003csup\u003ec\u003c/sup\u003e USA: United States of America\u003c/p\u003e \u003cp\u003e \u003csup\u003ed\u003c/sup\u003e UK: United Kingdom\u003c/p\u003e \u003cp\u003e \u003csup\u003ee\u003c/sup\u003e EHR: Electronic Health Record\u003c/p\u003e \u003cp\u003e \u003csup\u003ef\u003c/sup\u003e FQHC: Federally Qualified Healthcare Centre\u003c/p\u003e \u003cp\u003e \u003csup\u003eg\u003c/sup\u003e BMI: Body Mass Index\u003c/p\u003e \u003cp\u003e \u003csup\u003eh\u003c/sup\u003e SEP: Socioeconomic Position\u003c/p\u003e \u003cp\u003e \u003csup\u003ei\u003c/sup\u003e NICU: Neonatal Intensive Care Unit\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eDescription and evaluation of delivery strategies\u003c/h2\u003e \u003cp\u003eAn overview of the delivery strategies is presented in Table\u0026nbsp;2. From here onwards, the results are described per research project (n\u0026thinsp;=\u0026thinsp;33) and are referred to as study. First, a general description of the delivery strategies are discussed which include: the occurrence of delivery strategies and the stakeholders involved. After the general overview, a description of each delivery strategy component is presented. Followed by a description of the combinations of delivery strategy components. Finally, the studies that evaluated the reach effectivity of delivery strategies are presented.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eGeneral overview\u003c/h2\u003e \u003cp\u003eDelivery strategies consisted mostly of three (n\u0026thinsp;=\u0026thinsp;10), four (n\u0026thinsp;=\u0026thinsp;10) or two (n\u0026thinsp;=\u0026thinsp;9) delivery strategy components. Less frequent were delivery strategies with five (n\u0026thinsp;=\u0026thinsp;3) or one (n\u0026thinsp;=\u0026thinsp;1) delivery strategy components. Delivery strategies were often organized with stakeholders. Healthcare organisations (n\u0026thinsp;=\u0026thinsp;26) were often involved in the execution of delivery strategies. Furthermore, collaborations with community partners (n\u0026thinsp;=\u0026thinsp;6), citizens (n\u0026thinsp;=\u0026thinsp;2), commercial parties (n\u0026thinsp;=\u0026thinsp;3), social services (n\u0026thinsp;=\u0026thinsp;2), government (n\u0026thinsp;=\u0026thinsp;3) and education (n\u0026thinsp;=\u0026thinsp;1) were also described.\u003c/p\u003e \u003cp\u003e \u003cem\u003e1. Point of contact\u003c/em\u003e \u003c/p\u003e \u003cp\u003ePoint of contact was used in 31 studies (\u003cspan additionalcitationids=\"CR43 CR44 CR45 CR46 CR47 CR48 CR49 CR50 CR51 CR52 CR53 CR54 CR55 CR56 CR57 CR58\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan additionalcitationids=\"CR62 CR63 CR64 CR65 CR66 CR67 CR68 CR69 CR70 CR71 CR72 CR73 CR74\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan additionalcitationids=\"CR80 CR81 CR82 CR83 CR84\" citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e). Literature shows that research staff, healthcare professionals or healthcare organisation staff were often the person that introduced participants to the e-health application or e-health enabling service (n\u0026thinsp;=\u0026thinsp;29) (\u003cspan additionalcitationids=\"CR43 CR44 CR45 CR46 CR47 CR48 CR49 CR50 CR51 CR52 CR53 CR54 CR55 CR56 CR57 CR58\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan additionalcitationids=\"CR62 CR63\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan additionalcitationids=\"CR68 CR69 CR70 CR71 CR72 CR73 CR74\" citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan additionalcitationids=\"CR80 CR81 CR82 CR83 CR84\" citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e) Community organisations, governmental bodies, social services and key figures were also used for e-health delivery (\u003cspan additionalcitationids=\"CR55 CR56\" citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63 CR64 CR65\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e). Invitation letters in the study from Bennett et al. were signed by the head of the healthcare clinic, a key figure in the area, for a personal approach (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). Personal recruitment occurred via in-person recruitment (n\u0026thinsp;=\u0026thinsp;10), phone call recruitment (n\u0026thinsp;=\u0026thinsp;10), referrals (n\u0026thinsp;=\u0026thinsp;9), invitation letters (n\u0026thinsp;=\u0026thinsp;9), e-mail recruitment (n\u0026thinsp;=\u0026thinsp;4) or text message recruitment (n\u0026thinsp;=\u0026thinsp;1).\u003c/p\u003e \u003cp\u003e \u003cem\u003e2. Place\u003c/em\u003e \u003c/p\u003e \u003cp\u003eTwenty-seven studies deployed their delivery strategies at places that were commonly visited by people with a low SEP (\u003cspan additionalcitationids=\"CR44 CR45 CR46 CR47 CR48 CR49 CR50 CR51 CR52 CR53 CR54 CR55 CR56 CR57 CR58 CR59 CR60\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan additionalcitationids=\"CR66 CR67 CR68 CR69\" citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan additionalcitationids=\"CR73\" citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan additionalcitationids=\"CR80 CR81 CR82 CR83 CR84\" citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e). Two studies recruited participants online and used location targeted social media advertisements to reach low SEP participants (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e), locations were determined via geographical deprivation indexes.\u003c/p\u003e \u003cp\u003eFifteen studies executed the delivery of e-health within specific healthcare organizations that have to treat patients regardless of their insurance status, which attracts low SEP populations (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan additionalcitationids=\"CR48 CR49 CR50 CR51 CR52 CR53 CR54 CR55 CR56 CR57 CR58\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e). Studies reported conducting research in American safety-net hospitals, community healthcare centres, federally qualified healthcare centres, free clinics and private non-profit clinics. Three studies recruited participants during healthcare that is only available for people with a public health insurance, such as during Women, Infants and Children appointments (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e). Fourteen studies delivered e-health in the following settings that were located in low SEP areas: healthcare clinics (n\u0026thinsp;=\u0026thinsp;10) (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan additionalcitationids=\"CR59 CR60\" citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e), social service organizations (n\u0026thinsp;=\u0026thinsp;2) (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e), schools (n\u0026thinsp;=\u0026thinsp;1) (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e), and church (n\u0026thinsp;=\u0026thinsp;1) (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e). Several studies used geographical deprivation data to first select low SEP areas before identifying study sites within the selected areas (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e). Kling et al. reviewed patient data to identify the number of low SEP participants to determine that clinics were located in a low SEP area (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003e3. Promotion\u003c/em\u003e \u003c/p\u003e \u003cp\u003eFifteen studies used offline promotion (n\u0026thinsp;=\u0026thinsp;11) (\u003cspan additionalcitationids=\"CR44 CR45\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan additionalcitationids=\"CR55 CR56\" citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan additionalcitationids=\"CR71\" citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e), online promotion (n\u0026thinsp;=\u0026thinsp;8) (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63 CR64\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e) and word-of-mouth (n\u0026thinsp;=\u0026thinsp;3) (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e) promotional means to reach low SEP target populations. Promotion activities performed in collaboration with authorities such as healthcare professionals, well-known health services or municipalities were described (\u003cspan additionalcitationids=\"CR55 CR56\" citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63 CR64 CR65\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e). Some researchers collaborated with other parties to use their advertisement outlets to improve their reach, partners reported were: municipalities from low SEP areas (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e), gyms located in low SEP areas (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e), the national health institute (\u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e), a smoking cessation app (\u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e), health or social service programs (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e) and, local community organizations (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e). Furthermore, three studies reported the recruitment via family, friends or others (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003e4. Facilitation\u003c/em\u003e \u003c/p\u003e \u003cp\u003eFacilitation of e-health use (n\u0026thinsp;=\u0026thinsp;16) was reported in the forms of providing education and technical support (n\u0026thinsp;=\u0026thinsp;11) and facilitation of devices (n\u0026thinsp;=\u0026thinsp;9) (\u003cspan additionalcitationids=\"CR48\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63 CR64 CR65\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan additionalcitationids=\"CR75 CR76 CR77\" citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e, \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e). In few studies technical support was available upon participants\u0026rsquo; request (\u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e). In other studies support was part of the recruitment process; participants would get educated on the use of the device and e-health application at the start of the study (\u003cspan additionalcitationids=\"CR48\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63 CR64 CR65\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan additionalcitationids=\"CR75 CR76 CR77\" citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e, \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e). Garg et al. included a peer patient navigator who helped participants navigate online application forms for social support (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). Baggett et al. and Baker et al. delivered support in e-health use at home, saving traveling time and overcoming logistic barriers (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e). Facilitation of devices (n\u0026thinsp;=\u0026thinsp;9) was organized to enable e-health use (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e, \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e). I-pads, phones or laptops (n\u0026thinsp;=\u0026thinsp;7) and physical activity trackers (n\u0026thinsp;=\u0026thinsp;2) were lend out for the duration of the study.\u003c/p\u003e \u003cp\u003e \u003cem\u003e5. Incentives\u003c/em\u003e \u003c/p\u003e \u003cp\u003eIncentivization (n\u0026thinsp;=\u0026thinsp;15) was applied by offering financial means, a service, or a device (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan additionalcitationids=\"CR48 CR49\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63 CR64\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan additionalcitationids=\"CR75 CR76 CR77\" citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e). Financial incentives (n\u0026thinsp;=\u0026thinsp;8) were provided in the forms of stipends or gift cards, the minimum amount of financial incentive was 6\u003cspan\u003e$\u003c/span\u003e (\u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e) and the maximum was 415\u003cspan\u003e$\u003c/span\u003e (\u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e) (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63 CR64\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan additionalcitationids=\"CR75 CR76 CR77\" citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e). Four studies applied a staggered financial incentive approach, whereby participants would receive financial compensation for completion of each survey or progressive use of the e-health application (\u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan additionalcitationids=\"CR75 CR76 CR77\" citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eStudies (n\u0026thinsp;=\u0026thinsp;7) also offered other types of incentivization which are categorized as a service incentive (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan additionalcitationids=\"CR48\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e). These incentives are not financial but provide a service or information. Services provided were: exercise program or gym membership (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e), a local resource guide (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e), free support for social needs (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e), free food, childcare and healthcare (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e), free Wi-Fi (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e), and free healthcare (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e). Bennett et al. and Griffin et al. provided devices for participants to keep: a cellular scale (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e) and a physical activity tracking meter (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eCombinations of delivery strategy components\u003c/h2\u003e \u003cp\u003eThe combination of the delivery strategies place and point of contact were most common in the identified literature (n\u0026thinsp;=\u0026thinsp;26) (\u003cspan additionalcitationids=\"CR44 CR45 CR46 CR47 CR48 CR49 CR50 CR51 CR52 CR53 CR54 CR55 CR56 CR57 CR58\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan additionalcitationids=\"CR66 CR67 CR68 CR69\" citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan additionalcitationids=\"CR73\" citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e, \u003cspan additionalcitationids=\"CR83 CR84\" citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e). In case of the studies that employed two delivery strategies components, 7 of 9 studies combined place and point-of-contact strategy components (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e). The other two studies employed point-of-contact and promotion, and point-of-contact and incentive strategy components (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e). Delivery strategy components promotion, facilitation and incentive were employed in equal measures when studies used three or more delivery strategy components. McEntee et al. is the only study that does not deliver e-health through place nor point of contact strategies (\u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e). This delivery strategy made use of promotion, facilitation and incentive strategies and used location specific online promotion activities in high and low SEP areas. Additionally, this study reported the highest maximal financial incentive of \u003cspan\u003e$\u003c/span\u003e415 (\u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003ePoint of contact strategies also combined with promotion strategies and incentive strategies\u003c/h2\u003e \u003cp\u003eSix studies (n\u0026thinsp;=\u0026thinsp;6) (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan additionalcitationids=\"CR76 CR77\" citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e) did not recruit participants via strategy component place. The majority of these studies (n\u0026thinsp;=\u0026thinsp;5) recruited via point of contact combined with promotion and, incentivization strategy components (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e). Five studies covered a greater area (municipalities to country-wide areas) (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e) and four of these studies delivered e-health via authorities or well-known institutions (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e). Collombon et al. recruited participants living in low SEP areas via written invitations sent out from the municipality office and via online advertorials spread via gyms that were located in low SEP areas (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e). Alcaraz, Vereen \u0026amp; Burnham studied the reach of a well-known nation-wide social service to evaluate whether this institution was a suitable avenue for recruitment of people with socioeconomic disadvantages for health disparities research (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e). Three studies provided a financial incentive (\u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e). Oldham et al. and McEntee et al. used theoretical underpinnings to determine the financial incentivization strategies (\u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e\u003cb\u003eTable\u0026nbsp;2.\u003c/b\u003e Overview of the stakeholders, means and components of the employed delivery strategies. Studies are sorted to the number of applied delivery strategy components. The grey shaded studies are the studies that proved significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the evaluation of the delivery strategies\u0026rsquo; reach of low SEP participants. The lilac shaded studies are the studies that used a scientific or experiential underpinning for designing the delivery strategies. The blue shaded studies are studies that both had a significant outcome in the evaluation of the delivery strategies\u0026rsquo; reach for low SEP participants and used an underpinning for their delivery strategy design.\u003c/p\u003e \u003cp\u003eInsert Table\u0026nbsp;2 here.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eEvaluation of delivery strategies\u0026rsquo; reach and reach effectivity\u003c/h2\u003e \u003cp\u003eAn overview of the twelve studies that evaluated the effectiveness of reach of the delivery strategies can be found in Table\u0026nbsp;3. Four studies presented descriptive statistics about the effectivity of reach (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e). Eight studies conducted statistical analysis to determine whether delivery strategies were effective in reach (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e). The majority of these studies (n\u0026thinsp;=\u0026thinsp;7) showed statistical significance and provided evidence for reach effectivity (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e). Studies were deemed significant if there was a p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 outcome for differences in reach between included conditions in the study. Delivery strategies containing the following delivery strategy components were evaluated: point of contact (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e), promotion (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e), place (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e), and facilitation (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). Significant evidence was found in the delivery strategy components point-of-contact (n\u0026thinsp;=\u0026thinsp;2) (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e), place (n\u0026thinsp;=\u0026thinsp;1) (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e) and promotion (n\u0026thinsp;=\u0026thinsp;4) (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e). There were no evaluation studies that evaluated incentive delivery strategies. Elam et al. and Ehmer et al. both performed two evaluations (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). In Table\u0026nbsp;3 these evaluations are referred to as StudyID 7 and 7a, and, 10 and 10a (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003e1. Point of contact\u003c/em\u003e \u003c/p\u003e \u003cp\u003eFive studies evaluated point of contact delivery strategies which concern the role of a healthcare professional and the organisation of their work processes (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e). Staples et al. compared the reach of self-referral and physician-led referral to two similar online mental health treatment websites (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). The self-referral website was well-known among the public. Physicians were trained to identify low SEP status of patients and refer these patients to the website. Physician-led referral significantly reached more people with a lower education (X2\u0026thinsp;=\u0026thinsp;321.8, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), less likely to be employed (X2\u0026thinsp;=\u0026thinsp;145.6, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and living in a disadvantaged area (X2\u0026thinsp;=\u0026thinsp;173.2, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to self-referral (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTask allocation and organisation of personnel in healthcare contexts are relevant in reach of low SEP populations. Garg et al, Simione et al., and Baggett et al. compared differences in the e-health referrals (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e). Garg et al. showed that clinics with social needs screening and extra personnel that support patients with digital health use showed significantly more referrals (OR 4.6 95CI 2.0-5.9) (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). Descriptive analysis from Simione et al. showed that medical assistants were more consistent and reached more patients compared to physicians (54% compared to 17% or 12%) in following up with an e-health referral (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e). Baggett et al. compared a gatekeeper referral approach vs open and shared referral approach in three similar neonatal intensive care units. The clinic adopting the latter approach had 13 referrals/quarter, clinics adopting a gatekeepers approach had 4.2 and 3.4 referrals/quarter (\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003e2. Place\u003c/em\u003e \u003c/p\u003e \u003cp\u003eElam et al., Levy et al., and Baker et al. evaluated place delivery strategies (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e). Elam et al. showed that the free clinic recruited significantly more patients without a medical insurance compared to the federally qualified healthcare centre (FQHC) (47.8% vs. 7.8%, respectively; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Clinic phone call recruitment significantly recruited more patients in the FQHC (6.5% vs. 49.8%, respectively; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Community based strategies were significantly more effective in the free clinic: recruitment by a non-medical staff member (24.6% vs. 4.5%; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), a flyer outside the clinic (10.7% vs. 2.1%; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), or the clinics website or social media (7.3% vs. 0.7%; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Furthermore, the FQHC patients with diabetes were actively approached for a glaucoma screening. The authors noted that diabetes patients may be more motivated to attend the glaucoma screening and are more likely to have a public health insurance (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLevy et al. and Baker et al. used multiple databases to identify low SEP individuals (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e) or regions (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e) and used a mobile health van to deploy e-health at home (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e), or in the community (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e). Results by Levy et al. showed that a mobile health van was more effective in reaching citizens living in low SEP neighbourhoods compared to a permanently located drive through location (25% vs 27%, p\u0026thinsp;=\u0026thinsp;0.01) (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e). After introducing the determination of mobile health vans locations based on real-time COVID-19 prevalence, socioeconomic status of the area and, disease burden, a significant positive trend in reaching low SEP populations (P\u0026thinsp;\u0026gt;\u0026thinsp;0.001) was found (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e). Baker et al. described that home visits with the mobile van was less successful in reaching Medicaid-insured citizens with a high risk of severe COVID complications than a permanent health facility location within the low SEP area (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003e3. Promotion\u003c/em\u003e \u003c/p\u003e \u003cp\u003eFive studies evaluated the differences in the reach of low SEP participants between offline and online promotion strategies (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e). Elam et al, Miller et al., and Alcaraz, Vereen \u0026amp; Burnham showed similar significant results; offline promotion strategies are more effective compared to online promotion strategies. Miller et al. showed that outreach via e-mail is significantly less effective for people with a high school degree (14%) compared to some college (35%) or college degree (38%) (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e). Alcaraz, Vereen \u0026amp; Burnham found that people with higher educational attainment (OR 2.17, CI95 1.67\u0026ndash;2.82), higher income (OR 2.02, CI95 1.56\u0026ndash;2.61) and who are not publicly insured (OR 0.75, IC95 0.62\u0026ndash;0.90) were more often recruited via digital recruitment compared to telephone call recruitment (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e). In the study from Elam et al. participants without medical insurance reported hearing about the program more often directly from a clinic doctor (23.9% vs. 2.8%; Holm-adjusted P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) or nonmedical staff (34.4% vs. 16,7%; Holm-adjusted P\u0026thinsp;=\u0026thinsp;0.0011) (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Participants who had medical insurance significantly heard more often about the program via a friend, a flyer outside the clinic, the clinic website or social media or other (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCollombon et al. aimed to recruit older low SEP citizens using the outreach avenues from the municipality and gyms located in low SEP areas (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e). Significantly more low-educated participants were reached via personal invitation letters that were sent out by the municipality (N\u0026thinsp;=\u0026thinsp;128/281, 45.6%) compared to the online newsletters and social media advertisements from gyms (N\u0026thinsp;=\u0026thinsp;8/45, 17.8%) and regular social media advertisements (N\u0026thinsp;=\u0026thinsp;9/71, 12.7%) (χ2\u0026thinsp;=\u0026thinsp;50.429, P \u0026lt; .001). Descriptive outcomes from Oldham et al. also show that promotion via well-known health institutes such as the British National Health System (NHS) website was more successful in reaching low SES participants compared to other promotion avenues (\u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003e4. Facilitation\u003c/em\u003e \u003c/p\u003e \u003cp\u003eEhmer et al. evaluated a facilitation delivery strategy (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). In this study no differences were found between the population\u0026rsquo;s public insurance status before and after implementation of safe spaces and devices at the clinic for mothers to enable access to their video consultation calls (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eUnderpinning of delivery strategies\u003c/h2\u003e \u003cp\u003eReview of literature and consultations of stakeholders were used in studies (n\u0026thinsp;=\u0026thinsp;10) for the design of implementation strategies or to identify and operationalize delivery strategies (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan additionalcitationids=\"CR57 CR58\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63 CR64 CR65\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e). Other studies (n\u0026thinsp;=\u0026thinsp;23) did not report motivations for chosen delivery strategy designs. Scientific (n\u0026thinsp;=\u0026thinsp;5) (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e), experiential (n\u0026thinsp;=\u0026thinsp;1) (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e) or scientific and experiential (n\u0026thinsp;=\u0026thinsp;4) (\u003cspan additionalcitationids=\"CR57 CR58\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e) underpinnings were used. Researchers that used scientific publications for the design of delivery strategies consulted their own prior work (n\u0026thinsp;=\u0026thinsp;6) (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan additionalcitationids=\"CR57 CR58\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e), findings of other researchers (n\u0026thinsp;=\u0026thinsp;6) (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e) or theory (n\u0026thinsp;=\u0026thinsp;2) (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e). The literature and experiential knowledge from stakeholders were used for the design of implementation strategies and operationalization of delivery strategies.\u003c/p\u003e \u003cp\u003eSeveral researchers (n\u0026thinsp;=\u0026thinsp;4) consulted literature and involved stakeholders to improve the implementation strategy design (\u003cspan additionalcitationids=\"CR57 CR58\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e). In these studies, the literature and stakeholders had influence on a tactical level, informing researchers\u0026rsquo; methods for implementation of e-health interventions in specific contexts. Elam et al. and Thomas et al. had a permanent community advisory board that would advise the research team on recruitment and retainment strategies (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e). Simione et al. were the only researchers using an implementation theory (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e). The Consolidated Framework for Implementation Research (CFIR) (\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e) guided the researchers on how to engage stakeholders (families, healthcare professionals, and hospital leadership) and tailor the implementation strategies to suit the intervention context (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e). Baggett et al. designed e-health referral processes and the according implementation strategies with healthcare professionals in three neonatal intensive care units (\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e). The use of dissemination and implementation literature was mentioned but not specified (\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLiterature and stakeholders were used for identification and operationalization of delivery strategies in all the studies that reported a scientific and/or experiential underpinning (n\u0026thinsp;=\u0026thinsp;10) (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan additionalcitationids=\"CR57 CR58\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63 CR64 CR65\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e). Literature and stakeholders were involved on a operational level, informing the researchers how to execute their delivery strategies. Researchers reviewed literature that described delivery strategies for similar interventions (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e) or articles that discussed researchers\u0026rsquo; learnings regarding delivery strategies for people with a low SEP (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e). Collombon et al., Vaughan et al. and McEntee et al. reviewed their prior work to other interventions to determine the best outreach strategies for people with a low SEP (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e). Stakeholders and literature were consulted for the content of promotional activities (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63 CR64 CR65\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e). Co-development of advertorials with target population or target population representatives was done to overcome language and cultural barriers. Literature was used to inform incentivization delivery strategies (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e). McEntee et al. referred to the behavioural choice theory (\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e) to inform financial incentivization strategies (\u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eResearchers\u0026rsquo; reflections upon delivery strategies\u003c/h2\u003e \u003cp\u003eOnly authors (n\u0026thinsp;=\u0026thinsp;10) that evaluated delivery strategies provided additional reflections upon delivery strategies (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan additionalcitationids=\"CR57 CR58\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan additionalcitationids=\"CR70\" citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e). Five authors reflected on the importance of the integration of e-health in the practice and culture healthcare organizations (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e). It was noted that clear task allocation for referral, stakeholder engagement within the healthcare organization, training of healthcare professionals, championship by designated employees, and technical and work process integration was deemed important for successful delivery of e-health (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e). Other studies underlined the role of non-medical professionals in healthcare contexts (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Garg et al. concluded that the presence of social workers who supported patients in e-health use increased the number of referrals to e-health and support by physicians (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). Elam et al. reflected upon the different reach effectivity outcomes between a free clinic and a FQHC while employing similar promotion strategies. Free clinics is the only clinic type that serve illegal citizens or American citizens who have a green card for less than five years, whereas FQHCs serve citizens who are eligible for a public health care insurance (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Patients in free clinics were recruited more often via non-medical staff such as translators who explained the intervention to people with limited English language skills (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSeveral authors reflected upon culturally-, skill- or need adapted, personal, and prolonged delivery strategy approaches (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan additionalcitationids=\"CR70\" citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e). Elam et al, Miller et al., and Oldham et al. mentioned the importance of the use of culturally and language adapted (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e) and literacy skill adapted (\u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e) promotional and information materials in their research. Alcaraz et al. suggested that profiling of socio-economic groups\u0026rsquo; needs and channel use in social service and other recruitment settings could improve recruitment strategies (\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e). Baker et al. and Collombon et al. noted reflections concerning the personal approaches employed during e-health delivery (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e). Baker et al. observed that attempts to organize at-home appointments during COVID-19 pandemic scared potential participants as they were afraid of contracting COVID-19 and allowing unfamiliar people at home (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e). Collombon et al. found that personal invitation letters sent out by the municipality contributed to higher participation rates, additionally recruitment via family and friends was reported, which was a recruitment strategy that evolved during the study (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e). Collombon et al. suggested that both recruitment strategies should be investigated further. Baker et al. and Oldham et al. noted cumulation of participant recruitment due to long periods of promotional activity (\u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e). Oldham et al. advises the use of multiple recruitment methods, including targeted approaches for underrecruited groups and monitoring of the demographic composition during the recruitment phase (\u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e). Additionally, Oldham et al. stated that people with a low SEP via general practitioners was promising but limited in their study due to COVID-19 lockdowns (\u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable\u0026nbsp;3.\u003c/b\u003e Overview of the studies (n\u0026thinsp;=\u0026thinsp;12) that evaluated delivery strategies. Outcomes of evaluations are categorized upon the delivery strategy components. Studies were deemed significant if there was a p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 outcome for differences in reach. between included conditions in the study. Elam et al. and Ehmer et al. both performed two evaluations, these evaluations are referred to as StudyID 7 and 7a, and, 10 and 10a.\u003c/p\u003e \u003cp\u003eInsert Table\u0026nbsp;3 here\u003c/p\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003eStatistics Index of Relative Socio-economic Disadvantage\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e This review presented an overview of e-health delivery strategies aimed at engaging individuals with a low socioeconomic position (SEP). We used an a priori adjusted version of the marketing mix model to define the mechanisms of delivery strategies (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). The adjusted model defines five delivery strategy components: place, point of contact, promotion, facilitation and incentive. Almost all delivery strategies identified in this review consisted of more than one delivery strategy component. Place and point of contact were the most often used and combined delivery strategy components. Those studies that evaluated their delivery strategies revealed that place, point-of-contact and, promotion strategy components can have a significant effect on reach effectivity. E-health delivery in settings commonly accessed by people with a low SEP, offline promotion and recruitment through trusted authorities, proved to be more effective compared to, respectively, delivery in less familiar settings, online promotion and recruitment through organizations and people with less authority or self-recruitment. Evidence and researchers\u0026rsquo; reflections also suggests that adoption of e-health and e-health delivery strategies by healthcare professionals and organisations are relevant in reaching people with a low SEP. Nevertheless, the evidence available is insufficient and too scattered to state solid conclusions. Additionally, most studies were e-health intervention studies, implying that delivery strategies were used for recruitment in a research context, which is different from e-health delivery in a real life context.\u003c/p\u003e \u003cp\u003eOur results show that delivery strategies often consist of multiple components, of which place and point-of-contact delivery strategy components are employed and combined most often. The location, person and medium through which e-health delivery takes place is important for strategies to be effective. The importance of the delivery of health interventions in contexts and by people that are familiar for people with a low SEP is also found in other studies (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e, \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e). Bonevski\u0026rsquo;s (2014) literature review finds that in clinical trials low SEP participants were often sampled via location or network targeted sampling or through community organizations (\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e). For recruitment, researcher \u0026ndash; community partnerships and health professional support for the study were often employed in recruitment (\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e). A literature review by Al-Dhahir et al. focused on the barriers and facilitators of eHealth-based lifestyle intervention programs for people with a low SEP. Al-Dhahir described that personal e-health delivery was most promising in reaching people with a low SEP (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Successful delivery of e-health to people with a low SEP involves understanding and tailoring delivery strategies to the context of people with low SEP.\u003c/p\u003e \u003cp\u003eThe lack of real-world evaluations limits understanding of the feasibility and effectiveness of e-health delivery strategies. Most findings in this review are based on RCTs, which differ significantly from real-world contexts in terms of implementation and delivery (\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e). Limited digital health skills and limited access to devices are main barriers in e-health access and use and is often associated with people with a low SEP (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan additionalcitationids=\"CR92 CR93 CR94\" citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e). Understanding how to deliver e-health to people with limited digital health skills and limited access to devices is crucial for equitable access to digital health. E-health evaluation studies often address barriers such as limited material access or digital skills, however this does not always reflect real-world feasibility. Some studies exclude individuals with low digital literacy or limited access to devices, preventing insight into whether the delivery strategies are effective for this population. Others provide devices and technical support to facilitate participation, but this may inflate the apparent effectiveness of delivery strategies, as such support might not be feasible outside of funded trials. RCTs with larger budgets are more likely to overcome recruitment challenges and avoid early termination (\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e). These studies are more likely to be published, potentially skewing the evidence base toward strategies that are resource-intensive and less generalizable. This creates a biased understanding of what works in both trial and real-world settings. Gitlin and Czaja argue that findings from real-world contexts are essential to inform future intervention research, enhancing the ecological validity of outcomes (\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e). Future research should therefore assess the reach and retention of implemented e-health applications and enabling services, to better understand which delivery strategies are effective, for whom, and under what conditions. These insights can guide both future research and practical implementation efforts.\u003c/p\u003e \u003cp\u003eEffectivity of e-health delivery strategies was studied via reported effectivity, scientific and experiential underpinnings and researchers\u0026rsquo; reflections upon delivery strategies. The results point towards the importance of the implementation of e-health in health organisations. Other scholars describe that adoption of e-health by professionals and organizations is crucial for patients\u0026rsquo; access to e-health (\u003cspan additionalcitationids=\"CR99\" citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e). According to Schiffelaar et al. (2025) a digital health transition in hospitals requires cultural, practical, political, and financial alignment throughout the organization, high-qualitative technical solutions that integrate within technical infrastructures and opportunities for staff and patients to access resources and training for e-health access and use (\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e). The Nonadoption, Abandonment, Scale-up, Spread and Sustainability (NASSS) framework by Greenhalgh et al. and the Consolidated Framework for Implementation Research (CFIR) by Damschroder et al. describe the importance of the context of direct end-users and the organizations\u0026rsquo; capacity and readiness to implement, change, and innovate for successful and sustainable implementation of interventions (\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e, \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e). Design thinking methods such as co-creation, prototyping and human-centred design are often used in digital health intervention research with the aim to involve end-users and the context to improve the intervention (\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e). However, Bodell et al. finds that researchers involve stakeholders to address health outcomes and user-friendliness of interventions but fail to involve stakeholders in later phases of implementation; the embedding in the organizational context and in patients\u0026rsquo; lives (\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e). Bodell\u0026rsquo;s findings align with the results in our review; five studies consulted stakeholders and one study consulted implementation theory for the design of delivery strategies. Future research should consider involvement of direct end-users, that include patients, staff, caregivers and healthcare professionals, and organizations in the design of delivery strategies.\u003c/p\u003e \u003cp\u003eThe majority of the studies were conducted in the United States (US). The US healthcare system has specific safety-net clinics or not-for-profit clinics that only serve those who live in disadvantaged circumstances (\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e, \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e). The high poverty rate and the limited access to healthcare in the US cause people with a low SEP to frequent these clinics, providing a model setting for the delivery of e-health (\u003cspan additionalcitationids=\"CR103\" citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e). The learning from these findings is that delivery of e-health to people with low SEP in specific low SEP (healthcare) contexts can be effective. This setting is, however, unique for the US healthcare system and results might be less generalizable to other countries and other healthcare systems. This poses the question whether other countries can identify similar places or adhere to other methods to reach people with a low SEP. Insights in how e-health is effectively delivered to people with low SEP in other countries and other healthcare systems is needed to inform research and practice in e-health delivery in other settings.\u003c/p\u003e \u003cp\u003eThis literature review has strengths and limitations. A strength of this study was that we searched multiple databases to ensure the identification of all potential relevant articles. Furthermore, the results of this study allowed for a detailed overview of the delivery strategies used specifically to reach people with a low SEP. Additionally, articles were screened and selected by the primary author and two secondary reviewers independently to minimise selection bias. A limitation of this study was the absence of grey literature. We expect that different delivery strategies have been tested in practice but have not been published in scientific literature, bearing findings that were not discussed or documented in scientific literature. Additionally, the critical appraisal showed risk for selection bias. Critical appraisals are constructed to appraise evaluation studies that evaluate medication treatments in which blinded approaches for both patient and administrator are highly valued and feasible via placebo medications. Blinded approaches are not feasible in e-health evaluation studies; therefore, critical appraisal scores are less high.\u003c/p\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003eImplications and future research\u003c/h2\u003e \u003cp\u003eThis literature review reveals a knowledge gap in what the mechanisms of delivery strategies are and how these strategies can support e-health introduction for people with a low SEP in real world contexts. Although the current literature provides valuable insights, the evidence available is insufficient to create a solid understanding, and by extension theory, about the mechanisms of delivery strategies. There are too few studies that have evaluated delivery strategies and studies evaluated different delivery strategies in a variety of contexts, study designs and e-health interventions. Additionally, there are no or very few studies that evaluated delivery strategies that had facilitation or incentive components; even though, almost half of delivery strategies employed these components. There was only one paper describing delivery of e-health enabling services. Other research underlines the importance of providing resources for low SEP populations to enable participation (\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e, \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e), which provides an argument to study the reach of facilitation and incentive e-health delivery strategies and evaluate the reach of e-health enabling services. Future research should aim to create a greater understanding of mechanisms of e-health delivery strategies in real world settings.\u003c/p\u003e \u003cp\u003eSuccessful e-health interventions consist of an effective and accessible application and an inclusive implementation strategy. Adjustments of delivery strategies to the context of people with a low SEP requires effort but is vital for recruitment and retention (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e, \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e). Andersen (1995) argues that the adaptability of populations\u0026rsquo; abilities to access healthcare are low and that healthcare services should be designed and implemented in differentiated ways to realize equitable access for different groups (\u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e). Additionally, e-health implementation strategies need to consider the professional and organizational context. Bodell et al. argue that the field of e-health implementation should draw upon both positivist and constructivist epistemologies (\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e). Health science traditionally adopts a positivist approach, aiming to assess the effects of interventions through systematic, rigorous methods that seek to minimize contextual influences or bias. In contrast, implementation science is grounded in a constructivist perspective, focusing on understanding how context shapes both the implementation process and the effectiveness of interventions (\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e). Successful e-health interventions require the integration of knowledge from both paradigms. Future e-health intervention research should therefore conceptualize implementation as an integral part of the intervention itself and place greater emphasis on understanding the influence of end-user, professional, and organizational contexts.\u003c/p\u003e \u003cp\u003eResults show limited use of scientific and experiential underpinnings, and few reflections upon employed delivery strategies. Although there is emphasis on equitable recruitment of people with a low SEP in health research, multiple literature reviews found that authors report too little about delivery strategies (\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e, \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e, \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e, \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e). Similarly to our literature scholars found that authors lack in report about the design of delivery strategies, lack in performing statistical analysis and scarcely share reflections upon whether the delivery strategy was successful (\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e, \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e, \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e, \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e, \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e109\u003c/span\u003e). All papers that evaluated an e-health delivery strategy were published after 2020, this might indicate that e-health delivery and reach is becoming an increasingly relevant topic within the field of digital health. To maximize future knowledge synthesis, future research should adhere to systematic reporting and evaluations concerning delivery strategies to create a stronger knowledge base.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThere remains a significant knowledge gap regarding which delivery strategies are most effective in reaching individuals with low socio-economic positions (SEP) via e-health interventions in real-world contexts. Among the various components of delivery strategies, place and point-of-contact are the most frequently employed and combined. The majority of the literature focuses on e-health delivery strategies within clinical trial settings, with limited reporting on the use of scientific or experiential knowledge in the design of these strategies. Existing evaluation studies provide some evidence supporting the effectiveness of place, point-of-contact, and promotion strategies in reaching low SEP populations. Still, this evidence is insufficient and too scattered to state solid conclusions in terms of reach effectivity. Despite these limitations, the current body of evidence offers a valuable foundation for further exploration and evaluation of delivery strategies. We are at the beginning of opening up a new area of research. The success of equitable e-health interventions depends on the effectiveness of e-health applications and inclusive and context-sensitive implementation strategies - including delivery strategies. Given the tremendous pace at which healthcare access and use is becoming dependent on e-health, there is a great urgency to develop this area of research. Researchers are encouraged to view implementation as an integral component of the intervention and should consider how the contexts of end users, healthcare professionals, and organizations shape the delivery and uptake of e-health interventions. Future research should aim to understand the mechanisms by which e-health delivery strategies can effectively engage people with low SEP across diverse healthcare systems and real-world conditions.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRCT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRandomized Controlled Trial\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUSA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUnited States of America\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUK\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUnited Kingdom\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEHR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eElectronic Health Record\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFQHC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFederally Qualified Healthcare Centre\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBody Mass Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSEP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSocioeconomic Position\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNICU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNeonatal Intensive Care Unit\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLMBS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLucille Margot Bartha Standaar\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eJM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eJippe Miedema\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLieke Steendam\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eIncluded papers, the extracted data, critical appraisal and a list of all the articles that were included for full-text screening can be found in the Supplementary File 1, 2 and 3.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe researchers report no conflict of interest.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThe Ministry of Public Health, Wellbeing and Sport funded this research. Funders were not involved and did not have influence on the research design and outcome.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions\u003c/p\u003e\n\u003cp\u003eLMBS contributed to the conception, the design of the literature review, the analysis and interpretation of data and the writing of the paper. RvdV, RDF and LHDvT contributed to the conception and the design of the literature review and provided extensive feedback. KL provided extensive feedback. All authors approve of the submitted version.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eWe want to express much gratitude for Lieke Steendam and Jippe Miedema for their valuable contributions and efforts in their role as second reviewer during title and abstract, and full-text screening. Furthermore, we are thankful for Eva Alblas and Myrah Wouterse for sharing their opinions and feedback during the finalization of this publication.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLatulippe K, Hamel C, Giroux D. Social Health Inequalities and eHealth: A Literature Review With Qualitative Synthesis of Theoretical and Empirical Studies. J Med Internet Res. 2017;19(4):e136.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAzzopardi-Muscat N, Sorensen K. Towards an equitable digital public health era: promoting equity through a health literacy perspective. Eur J Public Health. 2019;29(Supplement3):13\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRonquillo Y, Meyers A, Korvek SJ. Digital Health. StatPearls. Treasure Island (FL): StatPearls Publishing; 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcCloud RF, Okechukwu CA, Sorensen G, Viswanath K. 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Cochrane Database Syst Reviews. 2018(2).\u003c/span\u003e\u003c/li\u003e \u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 3 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"e-health, health promotion, health marketing, socioeconomic, outreach, health equity, implementation","lastPublishedDoi":"10.21203/rs.3.rs-8659891/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8659891/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInclusive implementation, tailored delivery of e-health applications, and support in e-health use could help overcome the digital divide between people with a low and a high socio-economic position (SEP). However, limited knowledge is available on how e-health and support is best delivered to people with a low SEP and whether these strategies are based upon scientific or experiential knowledge. This literature review aims to (1) provide an overview of strategies to deliver e-health to people with a low SEP, (2) offer insight into the effectivity in reach of people with a low SEP by these e-health delivery strategies, and (3) identify scientific and experiential underpinnings for e-health delivery strategies’ design.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis systematic review followed the PRISMA 2022 guidelines. A systematic search was conducted using five databases: PsycINFO, Web of Science, Embase, PubMed and Sociological Abstracts. Search terms were built around the following key-concepts: socio-economic position, e-health and delivery strategy. Delivery strategies were categorized according to five delivery strategy components: place, point-of-contact, promotion, facilitation and incentive.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe search strategy yielded 5141 papers. The included papers (n = 35) described 33 studies. Place and point-of-contact strategies were most often applied and combined in e-health delivery. Some evidence for reach effectivity exists for the following strategies: e-health delivery at locations visited by target groups, delivery via authorities and via offline promotion. In health organization contexts, how and which healthcare professional delivers e-health is relevant for effective reach. Applied underpinnings for delivery strategy design included stakeholder involvement for implementation strategy design, and identification and operationalization of delivery strategies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis literature review identified a gap in the existing knowledge concerning effective strategies for the delivery of e-health delivery to people with a low SEP. Results show that almost all strategies used multiple delivery strategy components of which place and point-of-contact were most common. The evidence regarding the reach effectiveness of delivery strategies is insufficient and too scattered to support definitive conclusions. Nonetheless, it offers valuable insights into potential effective approaches. Researchers report little on theoretical or experiential underpinnings used for the design of e-health delivery strategies, nor are real world evaluations often conducted.\u003c/p\u003e\n\u003cp\u003eRegistration: PROSPERO: CRD42024572294\u003c/p\u003e","manuscriptTitle":"A systematic literature review to identify delivery strategies of digital health for low SEP populations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-02 04:22:31","doi":"10.21203/rs.3.rs-8659891/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-13T11:48:44+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-11T06:21:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"230102064409455213838445247208180589298","date":"2026-05-02T22:36:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-22T17:21:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"105758519958829114095899895325798569269","date":"2026-04-13T08:32:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-05T02:24:32+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-27T12:11:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-24T07:52:09+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-24T07:49:07+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2026-01-21T12:26:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"233fb589-82c9-4028-bf62-466cc2a1ebe6","owner":[],"postedDate":"February 2nd, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-13T11:48:44+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-11T06:21:30+00:00","index":105,"fulltext":""},{"type":"reviewerAgreed","content":"230102064409455213838445247208180589298","date":"2026-05-02T22:36:27+00:00","index":101,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T11:57:01+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-02 04:22:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8659891","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8659891","identity":"rs-8659891","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}