Promised and Lottery Airtime Incentives to Improve Interactive Voice Response Survey Participation Among Adults in Bangladesh and Uganda: Randomized Controlled Trial.

BACKGROUND: Increased mobile phone penetration allows the interviewing of respondents using interactive voice response surveys in low- and middle-income countries. However, there has been little investigation of the best type of incentive to obtain data from a representative sample in these countries. OBJECTIVE: We assessed the effect of different airtime incentives options on cooperation and response rates of an interactive voice response survey in Bangladesh and Uganda. METHODS: The open-label randomized controlled trial had three arms: (1) no incentive (control), (2) promised airtime incentive of 50 Bangladeshi Taka (US $0.60; 1 BDT is approximately equivalent to US $0.012) or 5000 Ugandan Shilling (US $1.35; 1 UGX is approximately equivalent to US $0.00028), and (3) lottery incentive (500 BDT and 100,000 UGX), in which the odds of winning were 1:20. Fully automated random-digit dialing was used to sample eligible participants aged ≥18 years. The risk ratios (RRs) with 95% confidence intervals for primary outcomes of response and cooperation rates were obtained using log-binomial regression. RESULTS: Between June 14 and July 14, 2017, a total of 546,746 phone calls were made in Bangladesh, with 1165 complete interviews being conducted. Between March 26 and April 22, 2017, a total of 178,572 phone calls were made in Uganda, with 1248 complete interviews being conducted. Cooperation rates were significantly higher for the promised incentive (Bangladesh: 39.3%; RR 1.38, 95% CI 1.24-1.55, P<.001; Uganda: 59.9%; RR 1.47, 95% CI 1.33-1.62, P<.001) and the lottery incentive arms (Bangladesh: 36.6%; RR 1.28, 95% CI 1.15-1.45, P<.001; Uganda: 54.6%; RR 1.34, 95% CI 1.21-1.48, P<.001) than those for the control arm (Bangladesh: 28.4%; Uganda: 40.9%). Similarly, response rates were significantly higher for the promised incentive (Bangladesh: 26.5%%; RR 1.26, 95% CI 1.14-1.39, P<.001; Uganda: 41.2%; RR 1.27, 95% CI 1.16-1.39, P<.001) and lottery incentive arms (Bangladesh: 24.5%%; RR 1.17, 95% CI 1.06-1.29, P=.002; Uganda: 37.9%%; RR 1.17, 95% CI 1.06-1.29, P=.001) than those for the control arm (Bangladesh: 21.0%; Uganda: 32.4%). CONCLUSIONS: Promised or lottery airtime incentives improved survey participation and facilitated a large sample within a short period in 2 countries. TRIAL REGISTRATION: ClinicalTrials.gov NCT03773146; http://clinicaltrials.gov/ct2/show/NCT03773146.

Use of mobile applications and health technologies among dementia caregivers with chronic conditions: A cross-sectional study.

Objective: Almost 80% of people, who are caring for someone with dementia, have one or more chronic conditions and require self-management support. New technologies offer promising solutions; however, little is known about what technologies caregivers use for their health or in general. This study aimed to describe the prevalence of mobile application (app) and health-related technology use among caregivers who have chronic conditions and care for someone with dementia. Methods: A cross-sectional study was conducted with 122 caregivers recruited online and from communities in the Baltimore-metropolitan area. Data were collected with online surveys and computer-assisted telephone interviews. Descriptive and inferential statistics were used to analyze survey data. Results: Study participants were primarily female (95 of 122, 77.9%), middle-aged (average 53 years, standard deviation (SD) 17), well educated (average 16 years, SD 3.3), an adult child of the person with dementia (53 of 122, 43.4%), and had 4 chronic conditions on average (SD 2.6). Over 90% of caregivers used mobile apps (116 of 122), spending a range of 9 to 82 min on each app. Most caregivers reported using social media apps (96 of 116, 82.8%), weather apps (96 of 116, 82.8%), and/or music or entertainment apps (89 of 116, 76.7%). Among caregivers using each app type, more than half of caregivers used social media (66 of 96, 69%), games (49 of 74, 66%), weather (62 of 96, 65%), and/or music or entertainment apps (51 of 89, 57%) daily. Caregivers also used several technologies to support their own health-the most common being websites, mobile devices, and health-related mobile apps. Conclusion: This study supports the feasibility of using technologies to promote health behavior change and support self-management among caregivers.

How mHealth Can Contribute to Improving the Continuum of Care: A Scoping Review Approach to the Case of Human Immunodeficiency Virus in Sub-Saharan Africa.

Objectives: To determine mHealth's contribution to improving the continuum of care in sub-Saharan Africa towards achieving treatment targets for human immunodeficiency virus (HIV) endorsed by the 2016 Political Declaration on ending acquired immunodeficiency syndrome (AIDS). Methods: PubMed, Medline, Embase, Web of Science Core Collection and Cochrane databases; three observatories and four repositories were searched to identify and select relevant articles, projects and guidelines published from 1 January 2017, to 30 April 2021. Records focusing on the use of mHealth related to HIV treatment cascade or healthcare provider/patient relationship were considered. Results: From 574 identified records, 381 (206 scientific manuscripts and 175 mHealth projects) were considered. After screening, 36 articles (nine randomized control trials, five cohort studies, 19 qualitative studies, and three economic studies) and 23 projects were included. Conclusion: The cross-cutting benefits of mHealth that enhance patient empowerment have been identified. Important challenges such as gaps between research and implementation, lack of transdisciplinary collaboration, and lack of economic evidence were identified to support future mHealth research and accelerate the achievement of treatment targets for HIV.

Factors Associated With Intention to Adopt mHealth Apps Among Dementia Caregivers With a Chronic Condition: Cross-sectional, Correlational Study.

BACKGROUND: In the United States, nearly 80% of family caregivers of people with dementia have at least one chronic condition. Dementia caregivers experience high stress and burden that adversely affect their health and self-management. mHealth apps can improve health and self-management among dementia caregivers with a chronic condition. However, mHealth app adoption by dementia caregivers is low, and reasons for this are not well understood. OBJECTIVE: The purpose of this study is to explore factors associated with dementia caregivers' intention to adopt mHealth apps for chronic disease self-management. METHODS: We conducted a cross-sectional, correlational study and recruited a convenience sample of dementia caregivers. We created a survey using validated instruments and collected data through computer-assisted telephone interviews and web-based surveys. Before the COVID-19 pandemic, we recruited dementia caregivers through community-based strategies, such as attending community events. After nationwide closures due to the pandemic, the team focused on web-based recruitment. Multiple logistic regression analyses were used to test the relationships between the independent and dependent variables. RESULTS: Our sample of 117 caregivers had an average age of 53 (SD 17.4) years, 16 (SD 3.3) years of education, and 4 (SD 2.5) chronic conditions. The caregivers were predominantly women (92/117, 78.6%) and minorities (63/117, 53.8%), experienced some to extreme income difficulties (64/117, 54.7%), and were the child or child-in-law (53/117, 45.3%) of the person with dementia. In logistic regression models adjusting for the control variables, caregiver burden (odds ratio [OR] 1.3, 95% CI 0.57-2.8; P=.57), time spent caregiving per week (OR 1.7, 95% CI 0.77-3.9; P=.18), and burden of chronic disease and treatment (OR 2.3, 95% CI 0.91-5.7; P=.08) were not significantly associated with the intention to adopt mHealth apps. In the final multiple logistic regression model, only perceived usefulness (OR 23, 95% CI 5.6-97; P<.001) and the interaction term for caregivers' education and burden of chronic disease and treatment (OR 31, 95% CI 2.2-430; P=.01) were significantly associated with their intention to adopt mHealth apps. Perceived ease of use (OR 2.4, 95% CI 0.67-8.7; P=.18) and social influence (OR 1.8, 95% CI 0.58-5.7; P=.31) were not significantly associated with the intention to adopt mHealth apps. CONCLUSIONS: When designing mHealth app interventions for dementia caregivers with a chronic condition, it is important to consider caregivers' perceptions about how well mHealth apps can help their self-management and which app features would be most useful for self-management. Caregiving factors may not be relevant to caregivers' intention to adopt mHealth apps. This is promising because mHealth strategies may overcome barriers to caregivers' self-management. Future research should investigate reasons why caregivers with a low education level and low burden of chronic disease and treatment have significantly lower intention to adopt mHealth apps for self-management.

Impact of Public Health and Social Measures on the COVID-19 Pandemic in the United States and Other Countries: Descriptive Analysis.

BACKGROUND: The United States of America has the highest global number of COVID-19 cases and deaths, which may be due in part to delays and inconsistencies in implementing public health and social measures (PHSMs). OBJECTIVE: In this descriptive analysis, we analyzed the epidemiological evidence for the impact of PHSMs on COVID-19 transmission in the United States and compared these data to those for 10 other countries of varying income levels, population sizes, and geographies. METHODS: We compared PHSM implementation timing and stringency against COVID-19 daily case counts in the United States and against those in Canada, China, Ethiopia, Japan, Kazakhstan, New Zealand, Singapore, South Korea, Vietnam, and Zimbabwe from January 1 to November 25, 2020. We descriptively analyzed the impact of border closures, contact tracing, household confinement, mandated face masks, quarantine and isolation, school closures, limited gatherings, and states of emergency on COVID-19 case counts. We also compared the relationship between global socioeconomic indicators and national pandemic trajectories across the 11 countries. PHSMs and case count data were derived from various surveillance systems, including the Health Intervention Tracking for COVID-19 database, the World Health Organization PHSM database, and the European Centre for Disease Prevention and Control. RESULTS: Implementing a specific package of 4 PHSMs (quarantine and isolation, school closures, household confinement, and the limiting of social gatherings) early and stringently was observed to coincide with lower case counts and transmission durations in Vietnam, Zimbabwe, New Zealand, South Korea, Ethiopia, and Kazakhstan. In contrast, the United States implemented few PHSMs stringently or early and did not use this successful package. Across the 11 countries, national income positively correlated (r=0.624) with cumulative COVID-19 incidence. CONCLUSIONS: Our findings suggest that early implementation, consistent execution, adequate duration, and high adherence to PHSMs represent key factors of reducing the spread of COVID-19. Although national income may be related to COVID-19 progression, a country's wealth appears to be less important in controlling the pandemic and more important in taking rapid, centralized, and consistent public health action.

Analyzing the mobile "digital divide": changing determinants of household phone ownership over time in rural bangladesh.

BACKGROUND: We had a unique opportunity to examine demographic determinants of household mobile phone ownership in rural Bangladesh using socioeconomic data collected as part of a multiyear longitudinal cohort study of married women of reproductive age. OBJECTIVES: This paper explores how the demographics of household mobile phone owners have changed over time in a representative population of rural Bangladesh. METHODS: We present data collected between 2008 and 2011 on household mobile phone ownership and related characteristics including age, literacy, education, employment, electricity access, and household wealth among 35,306 individuals. Respondents were enrolled when found to be newly pregnant and contributed socioeconomic information once over the course of the time period serving as a "sample" of families within the population at that time. Univariate and multiple logistic regressions analyses were performed to identify the socioeconomic determinants of household phone ownership. RESULTS: Across 3 fiscal years, we found that reported household ownership of at least 1 working mobile phone grew from 29.85% in the first fiscal year to 56.07% in the third fiscal year. Illiteracy, unavailability of electricity, and low quartiles of wealth were identified as overall demographic constraints to mobile phone ownership. However, over time, these barriers became less evident and equity gaps among demographic status began to dissipate as access to mobile technology became more democratized. We saw a high growth rate in ownership among households in lower economic standing (illiterate, without electricity, low and lowest wealth index), likely a result of competitive pricing and innovative service packages that improve access to mobile phones as the mobile phone market matures. In contrast, as market saturation is rapidly attained in the most privileged demographics (literate, secondary schooling, electricity, high wealth index), members of the lower wealth quartiles seem to be following suit, with more of an exponential growth. CONCLUSIONS: Upward trends in household mobile phone ownership in vulnerable populations over time underline the potential to leverage this increasingly ubiquitous infrastructure to extend health and finance services across social and economic strata.