Dataset Information

Tailoring digital apps to support active ageing in a low income community.

ABSTRACT: Despite physical activity being one of the determinants of healthy aging, older people tend to become less active over the years. Maintaining physical activity levels during the life course is a motivational challenge. Digital tools have been used to change this pattern, such as smartphone applications to support physical activity; but there is a lack of in-depth research on the diversity of user's experiences, especially considering older users or non-users of information and communication technologies.Objective: Our goal was to identify requirements for designing a mobile app to encourage physical activity in a low-income community population of older people in Brazil (i.e. over 40 years old).

Method: We conducted a qualitative focus group study, involving by co-design of a physical activity application (Pacer)®. Seventeen volunteers were divided into 2 focus groups of physical active and insufficiently active, and 2 further 4 subgroups in each characterised by digital engagement. The following procedures were performed: (i) baseline assessments; (ii) a focus group with physically active older people and a focus group with insufficiently active older people (iii) design activities with both groups to re-design Pacer.

Results: Developing physical activity apps for older people should consider the following features: free application, simple interface, motivational messages using audio and visual information, sharing information among users, multimedia input and sharing and user customisation. In particular, we recommend that exercise apps in low-income communities be tailored to our four categories of users differing in baseline physical activity and digital engagement, to match the social and behavioural preferences we discovered.

SUBMITTER: Castro PC

PROVIDER: S-EPMC7728168 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Tailoring digital apps to support active ageing in a low income community.

Castro Paula Costa PC Romano Lua Bonadio LB Frohlich David D Lorenzi Lorena Jorge LJ Campos Lucas Bueno LB Paixão Andresa A Bet Patrícia P Deutekom Marije M Krose Ben B Dourado Victor Zuniga VZ Angélica de Oliveira Gomes Grace G

PloS one 20201210 12

Despite physical activity being one of the determinants of healthy aging, older people tend to become less active over the years. Maintaining physical activity levels during the life course is a motivational challenge. Digital tools have been used to change this pattern, such as smartphone applications to support physical activity; but there is a lack of in-depth research on the diversity of user's experiences, especially considering older users or non-users of information and communication tech ...[more]

PMID: 33301455

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Project description:Adherence to prescribed medication is suboptimal in 50% of the chronic population, resulting in negative medical and economic outcomes. With the widespread use of mobile phones worldwide, medication adherence apps for mobile phones become promising medication adherence aids thanks to simplicity, user-friendliness, and accessibility for the public. Yet, until today, there is insufficient evidence in favor of using mobile health (mHealth) apps to increase medication adherence. This study aims to develop a methodology for scientific and end-user (patient) mHealth evaluation (a) to identify medication adherence apps search terms, (b) to evaluate identified apps based on scientific criteria, and (c) to report best smartphone apps evaluated by patients. Search terms were identified via literature review and expertise. Firstly, an online questionnaire was developed to identify frequently used search terms by recruited patients. Related medication adherence apps were identified and selected using predefined inclusion criteria. Secondly, identified apps were evaluated thanks to a scientific evaluation method and a created online questionnaire for patient feedback. Recruited patients were invited to test and evaluate the selected apps. Out of 1,833 free-of-charge and 307 paid apps identified, only four free-of-charge and three paid apps remained included in the study after eligibility criteria. None of the selected app reached a high score. Looking at the overall scores, Medisafe (59%), MyTherapy (56%), and Meds on time (44%) received the highest scores in the scientific app evaluation. In the patient evaluation, Dosecast (3.83 out of five points), Medisafe (3.62), and SwissMeds (3.50) received the highest scores. None of the apps in this research has undergone a process for certification, for example, CE marking, through a notified body. Security and data protection aspects of existing apps highly contribute to these low evaluation scores through little information on patient's data processing and storage. This might be corrected through the introduction of General Data Protection Regulation (GDPR) in the European Economic Area (EEA) and more scrutiny through regulatory bodies in the EU/EEA and the USA. None of the applications should be recommended by healthcare providers. In addition, clinical studies with chronic patients are necessary to measure long-term app impacts.

Project description:IntroductionCOVID-19 has significantly affected community health workers' (CHWs) performance as they are expected to perform pandemic-related tasks along with routine essential healthcare services. A plausible way to optimise CHWs' functioning during this pandemic is to couple the efforts of CHWs with digital tools. So far, no systematic evidence is available on the use of digital health interventions to support CHWs in low-middle-income countries (LMICs) amid the COVID-19 pandemic. The article describes a protocol for a scoping review of primary research studies that aim to map evidence on the use of unique digital health interventions to support CHWs during COVID-19 in LMICs.Methods and analysisOur methodology has been adapted from scoping review guidelines provided by Arksey and O'Malley, Levac et al. and the Joanna Briggs Institute. Our search strategy has been developed for the following four main electronic databases: Excerpta Medica Database, Medical Literature Analysis and Retrieval System Online, Cochrane Central Register of Controlled Trials and Cumulated Index to Nursing and Allied Health Literature. Google Scholar and reference tracking will be used for supplementary searches. Each article will be screened against eligibility criteria by two independent researchers at the title and abstract and full-text level. The review will include studies that targeted digital health interventions at CHWs' level to provide support in delivering COVID-19-related and other essential healthcare services. A date limit of 31 December 2019 to the present date will be placed on the search and English language articles will be included.Ethics and disseminationFormal ethical approval is not required, as primary data will not be collected in this study. The results from our scoping review will provide valuable insight into the use of digital health interventions to optimise CHWs' functioning and will reveal current knowledge gaps in research. The results will be disseminated through journal publications and conference presentations.

Project description:BackgroundDigital therapeutic care apps provide a new effective and scalable approach for people with nonspecific low back pain (LBP). Digital therapeutic care apps are also driven by personalized decision-support interventions that support the user in self-managing LBP, and may induce prolonged behavior change to reduce the frequency and intensity of pain episodes. However, these therapeutic apps are associated with high attrition rates, and the initial prescription cost is higher than that of face-to-face physiotherapy. In Germany, digital therapeutic care apps are now being reimbursed by statutory health insurance; however, price targets and cost-driving factors for the formation of the reimbursement rate remain unexplored.ObjectiveThe aim of this study was to evaluate the cost-effectiveness of a digital therapeutic care app compared to treatment as usual (TAU) in Germany. We further aimed to explore under which circumstances the reimbursement rate could be modified to consider value-based pricing.MethodsWe developed a state-transition Markov model based on a best-practice analysis of prior LBP-related decision-analytic models, and evaluated the cost utility of a digital therapeutic care app compared to TAU in Germany. Based on a 3-year time horizon, we simulated the incremental cost and quality-adjusted life years (QALYs) for people with nonacute LBP from the societal perspective. In the deterministic sensitivity and scenario analyses, we focused on diverging attrition rates and app cost to assess our model's robustness and conditions for changing the reimbursement rate. All costs are reported in Euro (€1=US $1.12).ResultsOur base case results indicated that the digital therapeutic care strategy led to an incremental cost of €121.59, but also generated 0.0221 additional QALYs compared to the TAU strategy, with an estimated incremental cost-effectiveness ratio (ICER) of €5486 per QALY. The sensitivity analysis revealed that the reimbursement rate and the capability of digital therapeutic care to prevent reoccurring LBP episodes have a significant impact on the ICER. At the same time, the other parameters remained unaffected and thus supported the robustness of our model. In the scenario analysis, the different model time horizons and attrition rates strongly influenced the economic outcome. Reducing the cost of the app to €99 per 3 months or decreasing the app's attrition rate resulted in digital therapeutic care being significantly less costly with more generated QALYs, and is thus considered to be the dominant strategy over TAU.ConclusionsThe current reimbursement rate for a digital therapeutic care app in the statutory health insurance can be considered a cost-effective measure compared to TAU. The app's attrition rate and effect on the patient's prolonged behavior change essentially influence the settlement of an appropriate reimbursement rate. Future value-based pricing targets should focus on additional outcome parameters besides pain intensity and functional disability by including attrition rates and the app's long-term effect on quality of life.

Project description:ImportanceAddressing the social determinants of health has been difficult for health systems to operationalize.ObjectiveTo assess a standardized intervention, Individualized Management for Patient-Centered Targets (IMPaCT), delivered by community health workers (CHWs) across 3 health systems.Design, setting, and participantsThis 2-armed, single-blind, multicenter randomized clinical trial recruited patients from 3 primary care facilities in Philadelphia, Pennsylvania, between January 28, 2015, and March 28, 2016. Patients who resided in a high-poverty zip code, were uninsured or publicly insured, and who had a diagnosis for 2 or more chronic diseases were recruited, and patients were randomized to either the CHW intervention or the control arm (goal setting only). Follow-up assessments were conducted at 6 and 9 months after enrollment. Data were analyzed using an intention-to-treat approach from June 2017 to March 2018.InterventionParticipants set a chronic disease management goal with their primary care physician; those randomized to the CHW intervention received 6 months of tailored support.Main outcomes and measuresThe primary outcome was change in self-rated physical health. The secondary outcomes were self-rated mental health, chronic disease control, patient activation, patient-reported quality of primary care, and all-cause hospitalization.ResultsOf the 592 participants, 370 (62.5%) were female, with a mean (SD) age of 52.6 (11.1) years. Participants in both arms had similar improvements in self-rated physical health (mean [SD], 1.8 [11.2] vs 1.6 [9.9]; P = .89). Patients in the intervention group were more likely to report the highest quality of care (odds ratio [OR], 1.8; 95% CI, 1.4-2.4; risk difference [RD], 0.12; P < .001) and spent fewer total days in the hospital at 6 months (155 days vs 345 days; absolute event rate reduction, 69%) and 9 months (300 days vs 471 days; absolute event rate reduction, 65%). This reduction was driven by a shorter average length of stay (difference, -3.1 days; 95% CI, -6.33 to 0.22; P = .06) and a lower mean number of hospitalizations (difference, -0.3; 95% CI, -0.6 to 0.0; P = .07) among patients who were hospitalized. Patients in the intervention group had a lower odds of repeat hospitalizations (OR, 0.4; 95% CI, 0.2-0.9; RD, -0.24; P = .02), including 30-day readmissions (OR, 0.3; 95% CI, 0.1-0.9; RD, -0.17; P = .04).Conclusions and relevanceA standardized intervention did not improve self-rated health but did improve the patient-perceived quality of care while reducing hospitalizations, suggesting that health systems may use a standardized intervention to address the social determinants of health.Trial registrationClinicalTrials.gov identifier: NCT02347787.

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Tailoring digital apps to support active ageing in a low income community.

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Tailoring digital apps to support active ageing in a low income community.

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