The acknowledged potential of using mobile phones for improving healthcare in low-resource environments of developing countries has yet to translate into significant mHealth policy investment. The low uptake of mHealth in policy agendas may stem from a lack of evidence of the scalable, sustainable impact on health indicators. The mHealth literature in low- and middle-income countries reveals a burgeoning body of knowledge; yet, existing reviews suggest that the projects yield mixed results. This article adopts a stage-based approach to understand the varied contributions to mHealth research. The heuristic of inputs-mechanism-outputs is proposed as a tool to categorize mHealth studies. This review (63 articles comprising 53 studies) reveals that mHealth studies in developing countries tend to concentrate on specific stages, principally on pilot projects that adopt a deterministic approach to technological inputs (n = 32), namely introduction and implementation. Somewhat less studied were research designs that demonstrate evidence of outputs (n = 15), such as improvements in healthcare processes and public health indicators. The review finds a lack of emphasis on studies that provide theoretical understanding (n = 6) of adoption and appropriation of technological introduction that produces measurable health outcomes. As a result, there is a lack of dominant theory, or measures of outputs relevant to making policy decisions. Future work needs to aim for establishing theoretical and measurement standards, particularly from social scientific perspectives, in collaboration with researchers from the domains of information technology and public health. Priorities should be set for investments and guidance in evaluation disseminated by the scientific community to practitioners and policymakers.

Background With a growing focus on patient interaction with health management, mobile apps are increasingly used to deliver behavioral health interventions. The large variation in these mobile health apps—their target patient group, health behavior, and behavioral change strategies—has resulted in a large but incohesive body of literature. Objective This systematic review aimed to assess the effectiveness of mobile apps in improving health behaviors and outcomes and to examine the inclusion and effectiveness of behavior change techniques (BCTs) in mobile health apps. Methods PubMed, EMBASE, CINAHL, and Web of Science were systematically searched for articles published between 2014 and 2019 that evaluated mobile apps for health behavior change. Two authors independently screened and selected studies according to the eligibility criteria. Data were extracted and the risk of bias was assessed by one reviewer and validated by a second reviewer. Results A total of 52 randomized controlled trials met the inclusion criteria and were included in the analysis—37 studies focused on physical activity, diet, or a combination of both, 11 on drug and alcohol use, and 4 on mental health. Participant perceptions were generally positive—only one app was rated as less helpful and satisfactory than the control—and the studies that measured engagement and usability found relatively high study completion rates (mean 83%; n=18, N=39) and ease-of-use ratings (3 significantly better than control, 9/15 rated >70%). However, there was little evidence of changed behavior or health outcomes. Conclusions There was no strong evidence in support of the effectiveness of mobile apps in improving health behaviors or outcomes because few studies found significant differences between the app and control groups. Further research is needed to identify the BCTs that are most effective at promoting behavior change. Improved reporting is necessary to accurately evaluate the mobile health app effectiveness and risk of bias.

BackgroundMaternal, Newborn, and Child Health (MNCH) household survey data are collected mainly with pen-and-paper. Smartphone data collection may have advantages over pen-and-paper, but little evidence exists on how they compare.ObjectiveTo compare smartphone data collection versus the use of pen-and-paper for infant feeding practices of the MNCH household survey. We compared the two data collection methods for differences in data quality (data recording, data entry, open-ended answers, and interrater reliability), time consumption, costs, interviewers’ perceptions, and problems encountered.MethodsWe recruited mothers of infants aged 0 to 23 months in four village clinics in Zhaozhou Township, Zhao County, Hebei Province, China. We randomly assigned mothers to a smartphone or a pen-and-paper questionnaire group. A pair of interviewers simultaneously questioned mothers on infant feeding practices, each using the same method (either smartphone or pen-and-paper).ResultsWe enrolled 120 mothers, and all completed the study. Data recording errors were prevented in the smartphone questionnaire. In the 120 pen-and-paper questionnaires (60 mothers), we found 192 data recording errors in 55 questionnaires. There was no significant difference in recording variation between the groups for the questionnaire pairs (P = .32) or variables (P = .45). The smartphone questionnaires were automatically uploaded and no data entry errors occurred. We found that even after double data entry of the pen-and-paper questionnaires, 65.0% (78/120) of the questionnaires did not match and needed to be checked. The mean duration of an interview was 10.22 (SD 2.17) minutes for the smartphone method and 10.83 (SD 2.94) minutes for the pen-and-paper method, which was not significantly different between the methods (P = .19). The mean costs per questionnaire were higher for the smartphone questionnaire (¥143, equal to US $23 at the exchange rate on April 24, 2012) than for the pen-and-paper questionnaire (¥83, equal to US $13). The smartphone method was acceptable to interviewers, and after a pilot test we encountered only minor problems (eg, the system halted for a few seconds or it shut off), which did not result in data loss.ConclusionsThis is the first study showing that smartphones can be successfully used for household data collection on infant feeding in rural China. Using smartphones for data collection, compared with pen-and-paper, eliminated data recording and entry errors, had similar interrater reliability, and took an equal amount of time per interview. While the costs for the smartphone method were higher than the pen-and-paper method in our small-scale survey, the costs for both methods would be similar for a large-scale survey. Smartphone data collection should be further evaluated for other surveys and on a larger scale to deliver maximum benefits in China and elsewhere.

Problematic smartphone use is an emerging public health problem since the launch of the first smartphone 10 years ago. In this article, pathways to problematic use of smartphones, approaches to deal with this issue and their limitations are discussed. This includes problematic use of smartphones by people who self-identify that they or their family members use mobile devices in a problematic way. Extreme problematic use (e.g. relating to online gambling or heavy gaming) that severely disrupts people’s lives is a form of digital addiction is excluded from this discussion. Smartphone use can be problematic for some people due to the availability of constant connection, the addictiveness of applications (apps) combined with personal psychological factors. This is facilitated by characteristics of the technology, including easy access, the possibility of escaping daily life, being able to remain anonymous online, and the frequency of alerts and messages. While various non-technical interventions, such as digital detoxes, and digital interventions, including apps to limit use, have been developed to help people control their smartphone use, none of these has proven to work yet. An overview of currently available apps for problematic smartphone use is provided. Further work is needed on various aspects of problematic smartphone use, including the understanding of how smartphone use impacts on people’s lives, strengthening the definition of problematic smartphone use, and validation of its measurement, and more rigorous development and assessment of tools. We hope that these efforts will help people to use their smartphones in a healthy and effective way.

BackgroundPostnatal care is an important link in the continuum of care for maternal and child health. However, coverage and quality of postnatal care are poor in low- and middle-income countries. In 2009, the Chinese government set a policy providing free postnatal care services to all mothers and their newborns in China. Our study aimed at exploring coverage, quality of care, reasons for not receiving and barriers to providing postnatal care after introduction of this new policy.MethodsWe carried out a mixed method study in Zhao County, Hebei Province, China from July to August 2011. To quantify the coverage, quality of care and reasons for not using postnatal care, we conducted a household survey with 1601 caregivers of children younger than two years of age. We also conducted semi-structured interviews with 24 township maternal and child healthcare workers to evaluate their views on workload, in-service training and barriers to postnatal home visits.ResultsOf 1442 (90% of surveyed caregivers) women who completed the postnatal care survey module, 8% received a timely postnatal home visit (within one week after delivery) and 24% of women received postnatal care within 42 days after delivery. Among women who received postnatal care, 37% received counseling or guidance on infant feeding and 32% on cord care. 24% of women reported that the service provider checked jaundice of their newborns and 18% were consulted on danger signs and thermal care of their newborns. Of 991 mothers who did not seek postnatal care within 42 days after birth, 65% of them said that they did not knew about postnatal care and 24% of them thought it was unnecessary. Qualitative findings revealed that staff shortages and inconvenient transportation limited maternal and child healthcare workers in reaching out to women at home. In addition, maternal and child healthcare workers said that in-service training was inadequate and more training on postnatal care, hands-on practice, and supervision were needed.ConclusionsCoverage and quality of postnatal care were low in rural Hebei Province and far below the targets set by Chinese government. We identified barriers both from the supply and demand side.