RESUMEN
Objective: To enhance the predictive power of the Fit between Individuals, Task and Technology (FITT) framework in mobile, individual consumer settings by restructuring the individual-task fit to prominently emphasise the task-skills fit. Design: A mixed study involving a quantitative survey of 679 potential patients (adopters) and a qualitative content analysis of ten semi-structured interviews with clinic assistants. Setting: For the survey, three combined random samples of potential patients from Atteridgeville, Bapong and Garankuwa (South Africa). Ten Unjani clinic assistants were also interviewed about their tasks, skills, and related properties and attributes using a semi-structured interview guide. Participants: Participants in the survey were potential patients over 18 years of age in the three sampled locations. In the qualitative study, interviewed participants were employed as clinic assistants in ten clinics within the Unjani Clinic Network. Main outcome measures: in the quantitative study, the statistical significance of the relationships between smartphone experience and health motivation on the one hand and the adopter's perceived self-efficacy on the other. In the qualitative study, the extent to which task properties, context, and the adopters' levels of education and training affect their perceived self-efficacy. Findings: There is a significant relationship between smartphone experience and perceived self-efficacy and a moderately significant relationship between health motivation and perceived self-efficacy. Furthermore, task properties, task context, and an adopter's level of education and training considerably influence their perceived self-efficacy on a given future assistive digital health technology (ADHT). Conclusion: Extending the FITT to the FISTT framework to explicitly include the task-skills fit may improve the explanatory and predictive power of the traditional FITT framework in mobile individual consumer settings.
RESUMEN
BACKGROUND: Despite all the excitement and hype generated regarding the expected transformative impact of digital technology on the healthcare industry, traditional healthcare systems around the world have largely remained unchanged and resultant improvements in developed countries are slower than anticipated. One area which was expected to significantly improve the quality of and access to primary healthcare services in particular is remote patient monitoring and management. Based on a combination of rapid advances in body sensors and information and communication technologies (ICT), it was hoped that remote patient management tools and systems (RPMTSs) would significantly reduce the care burden on traditional healthcare systems as well as health-related costs. However, the uptake or adoption of above systems has been extremely slow and their roll out has not yet properly taken off especially in developing countries where they ought to have made the greatest positive impact. AIM: The aim of the study was to assess whether or not recent, relevant literature would support the development of in-community, design, deployment and implementation framework based on three factors thought to be important drivers and levers of RPMTS's adoption and scalability. METHODS: A rapid, scoping review conducted on relevant articles obtained from PubMed, MEDLINE, PMC and Cochrane databases and grey literature on Google and published between 2012 and May 2020, by combining a number of relevant search terms and phrases. RESULTS: Most RPMTSs are targeted at and focused on a single disease, do not extensively involve patients and clinicians in their early planning and design phases, are not designed to best serve a specific catchment area and are mainly directed at post-hospital, disease management settings. This may be leading to a situation where patients, potential patients and clinicians simply do not make use of these tools, leading to low adoption and scalability thereof. CONCLUSION: The development of a user-centred, context-dependent, customizable design and deployment framework could potentially increase the adoption and scalability of RPMTSs, if such framework addressed a combination of diseases, prevalent in a given specific catchment area, especially in developing countries with limited financial resources.