Challenges of Implementing an mHealth Application for Personalized Physical Activity Counselling in Primary Health Care: A Qualitative Study

Enhancing the Implementation and Integration of mHealth Interventions in Resource-Limited Settings: A Scoping Review

Background . Although mobile health (mHealth) interventions have shown promise in improving health outcomes, most of them rarely translate to scale. Prevailing mHealth studies are largely small-sized, short-term and donor-funded pilot studies with limited evidence on their effectiveness. To facilitate scale-up, several frameworks have been proposed to enhance the generic implementation of health interventions. However, there is a lack of a specific focus on the implementation and integration of mHealth interventions in routine care in low-resource settings. Our scoping review aimed to synthesize and develop a framework that could guide the implementation and integration of mHealth interventions. Methods: We searched the PubMed, Google Scholar, and ScienceDirect databases for published theories, models, and frameworks related to the implementation and integration of clinical interventions from 1 st January 2000 to 31 st December 2023. The data processing was guided by a scoping review methodology proposed by Arksey and O'Malley. Studies were included if they were i) peer-reviewed and published between 2000 and 2023, ii) explicitly described a framework for clinical intervention implementation and integration, or iii) available in full text and published in English. We integrated different domains and constructs from the reviewed frameworks to develop a new framework for implementing and integrating mHealth interventions. Results: We identified eight eligible papers with eight frameworks composed of 102 implementation domains. None of the identified frameworks were specific to the integration of mHealth interventions in low-resource settings. Two constructs (skill impartation and intervention awareness) related to the training domain, four constructs (technical and logistical support, identifying committed staff, supervision, and redesigning) from the restructuring domain, two constructs (monetary incentives and nonmonetary incentives) from the incentivize domain, two constructs (organizational mandates and government mandates) from the mandate domain and two constructs (collaboration and routine workflows) from the integrate domain. Therefore, a new framework that outlines five main domains-train, restructure, incentivize, mandate, and integrate (TRIMI)-in relation to the integration and implementation of mHealth interventions in low-resource settings emerged. Conclusion: The TRIMI framework presents a realistic and realizable solution for the implementation and integration deficits of mHealth interventions in low-resource settings.

Physical Activity with Sports Scientist (PASS) programme to promote physical activity among patients with non-communicable diseases: a pragmatic randomised controlled trial protocol

Physical activity (PA) effectively prevents and treats non-communicable diseases in clinical settings. PA promotion needs to be more consistent, especially in busy primary care. Sports scientists have the potential to support PA promotion in primary care. The Physical Activity with Sports Scientist (PASS) programme is created to personalise PA promotion led by a sports scientist in a primary care clinic. A pragmatic randomised controlled trial with two parallel groups will be conducted at a family medicine clinic. Physically inactive participants aged 35-70 years who have type 2 diabetes mellitus, hypertension or dyslipidaemia will be invited. The control group (n=60) will receive usual care. The intervention group (n=60) will receive the PASS programme and usual care. The PASS programme will consist of a tailored PA prescription after the physician's consultation at the first visit and monthly phone follow-ups. The primary outcome is the proportion of participants who have achieved the PA goal defined as aerobic activity (≥150 min/week of moderate to vigorous-intensity PA), muscle-strengthening activity (≥2 days/week of moderate or greater intensity) and multicomponent PA (≥2 days/week of moderate or greater intensity). Secondary outcomes are body composition and physical fitness. The primary and secondary outcomes will be measured and compared between the control and intervention groups at visit 1 (month 0: baseline measurements), visit 2 (months 3-4: follow-up measurements), visit 3 (months 6-8: end-point measurements) and visit 4 (months 9-12: continuing measurements). The study protocol was registered with the Thai Clinical Trials Registry. Trial registration number: TCTR20240314001.

Implementation determinants of physical activity interventions in primary health care settings using the TICD framework: a systematic review

BACKGROUND

Translation into practice of effective physical activity interventions in primary care is difficult, due to a complex interaction of implementation determinants. We aimed to identify implementation barriers and facilitators of four primary care interventions: physical activity assessment, counselling, prescription, and referral.

METHODS

A systematic review of qualitative, quantitative and mixed-methods studies published since 2016 was conducted. The "Tailored Implementation for Chronic Diseases" (TICD) framework was adapted to extract and synthesize barriers and facilitators.

RESULTS

Sixty-two studies met the inclusion criteria. Barriers (n = 56) and facilitators (n = 55) were identified across seven domains, related to characteristics of the intervention, individual factors of the implementers and receivers, organizational factors, and political and social determinants. The five most frequently reported determinants were: professionals' knowledge and skills; intervention feasibility/compatibility with primary health care routine; interventions' cost and financial incentives; tools and materials; and professionals' cognitions and attitudes. "Social, political and legal factors" domain was the least reported. Physical activity counselling, prescription, and referral were influenced by determinants belonging to all the seven domains.

CONCLUSION

The implementation of physical activity interventions in primary care is influenced by a broader range of determinants. Barriers and facilitators related with health professionals, intervention characteristics, and available resources were the most frequently reported. A deep understanding of the local context, with particularly emphasis on these determinants, should be considered when preparing an intervention implementation, in order to contribute for designing tailored implementation strategies and optimize the interventions' effectiveness.

Improving Predictability and Effectiveness in Preventive Digital Health Interventions: Scoping Review

BACKGROUND

Lifestyle-related diseases caused by inadequate diet and physical activity cause premature death, loss of healthy life years, and increased health care costs. Randomized controlled trial (RCT) studies indicate that preventive digital health interventions (P-DHIs) can be effective in preventing these health problems, but the results of these studies are mixed. Adoption studies have identified multiple factors related to individuals and the context in which they live that complicate the transfer of positive results from RCT studies to practical use. Implementation studies have revealed barriers to the large-scale implementation of mobile health (mHealth) solutions in general. Consequently, there is no clear path to delivering predictable outcomes from P-DHIs and achieving effectiveness when scaling up interventions to reduce health problems in society.

OBJECTIVE

This research aimed to expand our understanding of how to increase the outcome predictability of P-DHIs by focusing on physical activity and diet behaviors and amplify our understanding of how to improve effectiveness in large-scale implementations.

METHODS

The research objective was pursued through a multidisciplinary scoping review. This scoping review used the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) as a guide. A comprehensive search of Web of Science and PubMed limited to English-language journal articles published before January 2022 was conducted. Google Scholar was used for hand searches. Information systems theory was used to identify key constructs influencing outcomes of IT in general. Public health and mHealth literature were used to identify factors influencing the adoption of, outcomes from, and implementation of P-DHIs. Finally, the P-DHI investment model was developed based on information systems constructs and factors from the public health and mHealth literature.

RESULTS

In total, 203 articles met the eligibility criteria. The included studies used a variety of methodologies, including literature reviews, interviews, surveys, and RCT studies. The P-DHI investment model suggests which constructs and related factors should be emphasized to increase the predictability of P-DHI outcomes and improve the effectiveness of large-scale implementations.

CONCLUSIONS

The research suggests that outcome predictability could be improved by including descriptions of the constructs and factors in the P-DHI investment model when reporting from empirical studies. Doing so would increase our understanding of when and why P-DHIs succeed or fail. The effectiveness of large-scale implementations may be improved by using the P-DHI investment model to evaluate potential difficulties and possibilities in implementing P-DHIs to create better environments for their use before investing in them and when designing and implementing them. The cost-effectiveness of large-scale implementations is unknown; implementations are far more complicated than just downloading and using apps, and there is uncertainty accompanying implementations given the lack of coordinated control over the constructs and factors that influence the outcome.

Barriers to and Facilitators of the Use of Digital Tools in Primary Care to Deliver Physical Activity Advice: Semistructured Interviews and Thematic Analysis

Background

Physical inactivity is a leading risk factor for many health conditions, including cardiovascular disease, diabetes, and cancer; therefore, increasing physical activity (PA) is a public health priority. Health care professionals (HCPs) in primary care are pivotal in addressing physical inactivity; however, few HCPs provide PA advice to patients. There can be obstacles to delivering PA advice, including lack of time, confidence, or knowledge. Digital technology has the potential to overcome obstacles and facilitate delivering PA advice. However, it is unknown if and how digital tools are used to deliver PA advice in primary care consultations and what factors influence their use.

Objective

We aimed to understand the use of digital tools to support primary care consultations and to identify the barriers to and facilitators of using these systems.

Methods

Overall, 25 semistructured interviews were conducted with primary care HCPs. Professionals were sampled based on profession (general practitioners, practice nurses, and health care assistants), prevalence of long-term conditions within their practice area, and rural-urban classification. The data were analyzed thematically to identify the influences on the use of digital tools. Themes were categorized using the COM-B (capability, opportunity, and motivation—behavior) model and the Theoretical Domains Framework to identify the barriers to and facilitators of using digital tools to support the delivery of PA advice in primary care consultations.

Results

The identified themes fell within 8 domains of the Theoretical Domains Framework. The most prominent influence (barrier or facilitator) within psychological capability was having the skills to use digital tools. Training in the use of digital tools was also mentioned several times. The most notable influences within physical opportunity were limited digital tools to prompt/support the provision of PA advice, time constraints, efficiency of digital tools, simplicity and ease of use of digital tools, and integration with existing systems. Other physical opportunity influences included lack of access to digital tools and technical support in the use of digital tools. Within social opportunity, a notable barrier was that digital tools reduce interpersonal communication with patients. Patient preference was also identified. Several important influences were within reflective motivation, including confidence to use digital tools, beliefs about the usefulness of digital tools, the belief that digital tools “are the way forward,” beliefs related to data privacy and security concerns, and perceptions about patient capabilities. About automatic motivation, influences included familiarity and availability regarding digital tools and the fact that digital tools prompt behavior.

Conclusions

A variety of influences were identified on the use of digital tools to support primary care consultations. These findings provide a foundation for designing a digital tool addressing barriers and leverages the facilitators to support PA advice provision within primary care to elicit patient behavior change and increase PA.

The viability of utilising phone-based text messages in data capture and reporting morbidities due to lymphatic Filariasis by community health workers: a qualitative study in Kilwa district, Tanzania

Background

Globally, there is recognition of the value of using mobile phones among health providers in improving health systems performance. However, in many Low- and Middle-income countries where there is shortage of health providers, Community Health Workers have assumed some responsibilities especially relating to identifying and reporting on health problems within their communities. Despite the known benefits of using mobile phone technology to deliver health services, there is limited information on the extent to which Community Health Workers are able to effectively use the technology in data collection and reporting. The aim of this study was to determine the feasibility of utilizing phone-based text messages on Lymphatic Filariasis morbidity surveillance by Community Health Workers.

Methods

This was a cross sectional study whose data was collected through key informant interviews and focused group discussions among community health workers, health providers and staff of neglected tropical diseases control program. Collected transcripts were analysed through Thematic content analysis as it allowed for the identification of data codes through inductive reasoning.

Results

The use of mobile phone-based text messages in data collection and reporting lymphatic filariasis morbidity cases by Community Health Workers was perceived by study participants to be a relevant tool and feasible due to the ease of use of the technology. The tool was reported by end-users to significantly increase their performance and efficiency was gained in terms of reduced paper work, increased the number of patients accessing health care services and the ability to report in real-time. All respondents were confident that Community Health Workers were the right persons to interact with communities in tracking and reporting morbidity cases using mobile technology.

Conclusion

Mobile phone-based text messages have proven to be effective in routine workflows such as, data collection and reporting on Lymphatic Filariasis morbidity cases, patient to provider communication, decision making and supportive supervision. Mobile phones have also improved efficiency and general performance of end users in terms of increased number of cases identified and efficiency gained in terms of reduced paper work and the ability to collect and report in real-time.