Introduction Increasing smartphones access has allowed for increasing development and use of smart phone applications (apps). Mobile health interventions have previously relied on voice or text-based short message services (SMS), however, the increasing availability and ease of use of apps has allowed for significant growth of smartphone apps that can be used for health behaviour change. This review considers the current body of knowledge relating to the evaluation of apps for health behaviour change. The aim of this review is to investigate approaches to the evaluation of health apps to identify any current best practice approaches. Method A systematic review was conducted. Data were collected and analysed in September 2016. Thirty-eight articles were identified and have been included in this review. Results Articles were published between 2011– 2016, and 36 were reviews or evaluations of apps related to one or more health conditions, the remaining two reported on an investigation of the usability of health apps. Studies investigated apps relating to the following areas: alcohol, asthma, breastfeeding, cancer, depression, diabetes, general health and fitness, headaches, heart disease, HIV, hypertension, iron deficiency/anaemia, low vision, mindfulness, obesity, pain, physical activity, smoking, weight management and women’s health. Conclusion In order to harness the potential of mobile health apps for behaviour change and health, we need better ways to assess the quality and effectiveness of apps. This review is unable to suggest a single best practice approach to evaluate mobile health apps. Few measures identified in this review included sufficient information or evaluation, leading to potentially incomplete and inaccurate information for consumers seeking the best app for their situation. This is further complicated by a lack of regulation in health promotion generally.

Background: Electronic health (eHealth) has the potential to improve health outcomes. However, eHealth systems need to match the eHealth literacy needs of users to be equitably adopted. Socially disadvantaged groups have lower access and skills to use technologies and are at risk of being digitally marginalized, leading to the potential widening of health disparities. Objective: This systematic review aims to explore the role of eHealth literacy and user involvement in developing eHealth interventions targeted at socially disadvantaged groups. Methods: A systematic search was conducted across 10 databases for eHealth interventions targeted at older adults, ethnic minority groups, low-income groups, low-literacy groups, and rural communities. The eHealth Literacy Framework was used to examine the eHealth literacy components of reviewed interventions. The results were analyzed using narrative synthesis. Results: A total of 51 studies reporting on the results of 48 interventions were evaluated. Most studies were targeted at older adults and ethnic minorities, with only 2 studies focusing on low-literacy groups. eHealth literacy was not considered in the development of any of the studies, and no eHealth literacy assessment was conducted. User involvement in designing interventions was limited, and eHealth intervention developmental frameworks were rarely used. Strategies to assist users in engaging with technical systems were seldom included in the interventions, and accessibility features were limited. The results of the included studies also provided inconclusive evidence on the effectiveness of eHealth interventions. Conclusions: The findings highlight that eHealth literacy is generally overlooked in developing eHealth interventions targeted at socially disadvantaged groups, whereas evidence about the effectiveness of such interventions is limited. To ensure equal access and inclusiveness in the age of eHealth, eHealth literacy of disadvantaged groups needs to be addressed to help avoid a digital divide. This will assist the realization of recent technological advancements and, importantly, improve health equity.

Background: Cross-cultural research with patient-reported outcomes measures (PROMs) assumes that the PROM in the target language will measure the same construct in the same way as the PROM in the source language. Yet translation methods are rarely used to qualitatively maximise construct equivalence or to describe the intents of each item to support common understanding within translation teams. This study aimed to systematically investigate the utility of the Translation Integrity Procedure (TIP), in particular the use of item intent descriptions, to maximise construct equivalence during the translation process, and to demonstrate how documented data from the TIP contributes evidence to a validity argument for construct equivalence between translated and source language PROMs. Methods: Analysis of secondary data was conducted on routinely collected data in TIP Management Grids of translations (n = 9) of the Health Literacy Questionnaire (HLQ) that took place between August 2014 and August 2015: Arabic, Czech, French (Canada), French (France), Hindi, Indonesian, Slovak, Somali and Spanish (Argentina). Two researchers initially independently deductively coded the data to nine common types of translation errors. Round two of coding included an identified 10th code. Coded data were compared for discrepancies, and checked when needed with a third researcher for final code allocation. Results: Across the nine translations, 259 changes were made to provisional forward translations and were coded into 10 types of errors. Most frequently coded errors were Complex word or phrase (n = 99), Semantic (n = 54) and Grammar (n = 27). Errors coded least frequently were Cultural errors (n = 7) and Printed errors (n = 5). Conclusions: To advance PROM validation practice, this study investigated a documented translation method that includes the careful specification of descriptions of item intents. Assumptions that translated PROMs have construct equivalence between linguistic contexts can be incorrect due to errors in translation. Of particular concern was the use of high level complex words by translators, which, if undetected, could cause flawed interpretation of data from people with low literacy. Item intent descriptions can support translations to maximise construct equivalence, and documented translation data can contribute evidence to justify score interpretation and use of translated PROMS in new linguistic contexts.

Background: Web-based personal health records (PHRs) have the potential to improve the quality, accuracy, and timeliness of health care. However, the international uptake of web-based PHRs has been slow. Populations experiencing disadvantages are less likely to use web-based PHRs, potentially widening health inequities within and among countries. Objective: With limited understanding of the predictors of community uptake and use of web-based PHR, the aim of this study was to identify the predictors of awareness, engagement, and use of the Australian national web-based PHR, My Health Record (MyHR). Methods: A population-based survey of adult participants residing in regional Victoria, Australia, was conducted in 2018 using telephone interviews. Logistic regression, adjusted for age, was used to assess the relationship among digital health literacy, health literacy, and demographic characteristics, and the 3 dependent variables of MyHR: awareness, engagement, and use. Digital health literacy and health literacy were measured using multidimensional tools, using all 7 scales of the eHealth Literacy Questionnaire and 4 out of the 9 scales of the Health Literacy Questionnaire. Results: A total of 998 responses were analyzed. Many elements of digital health literacy were strongly associated with MyHR awareness, engagement, and use. A 1-unit increase in each of the 7 eHealth Literacy Questionnaire scales was associated with a 2- to 4-fold increase in the odds of using MyHR: using technology to process health information (odds ratio [OR] 4.14, 95% CI 2.34-7.31), understanding of health concepts and language (OR 2.25, 95% CI 1.08-4.69), ability to actively engage with digital services (OR 4.44, 95% CI 2.55-7.75), feel safe and in control (OR 2.36, 95% CI 1.43-3.88), motivated to engage with digital services (OR 4.24, 95% CI 2.36-7.61), access to digital services that work (OR 2.49, 95% CI 1.32-4.69), and digital services that suit individual needs (OR 3.48, 95% CI 1.97-6.15). The Health Literacy Questionnaire scales of health care support, actively managing health, and social support were also associated with a 1- to 2-fold increase in the odds of using MyHR. Using the internet to search for health information was another strong predictor; however, older people and those with less education were less likely to use MyHR. Conclusions: This study revealed strong and consistent patterns of association between digital health literacy and the use of a web-based PHR. The results indicate potential actions for promoting PHR uptake, including improving digital technology and skill experiences that may improve digital health literacy and willingness to engage in web-based PHR. Uptake may also be improved through more responsive digital services, strengthened health care, and better social support. A holistic approach, including targeted solutions, is needed to ensure that web-based PHR can realize its full potential to help reduce health inequities.

Background: The unequal access, challenges and outcomes related to using technology have created the digital divide, which leads to health inequalities. The aim of this study was to apply the Ophelia (Optimizing Health Literacy and Access) process, a widely used systematic approach to whole of community co-design, to the digital context to generate solutions to improve health and equity outcomes.Methods: This was a mixed method study. A cross-sectional survey was undertaken at 3 health organizations in Victoria, Australia using the eHealth Literacy Questionnaire (eHLQ) as a needs assessment tool. Cluster analysis was conducted to identify subgroups with varying eHealth literacy needs. These data, combined with semi-structured interviews with clients, were used to generate vignettes representing different eHealth literacy profiles. The vignettes were presented at co-design workshops with clients and health professionals to generate solutions for digital health services improvement. Expert validation and proof-of-concept testing was explored through mapping the process against Ophelia guiding principles.Results: The cluster analyses identified 8 to 9 clusters with different profiles of eHealth literacy needs, with 4 to 6 vignettes developed to represent the eHealth literacy strengths and weaknesses of clients at each of the 3 sites. A total of 32, 43, and 32 solutions across 10 strategies were co-created based on ideas grounded in local expertise and experiences. Apart from digital solutions, non-digital solutions were frequently recommended as a strategy to address eHealth literacy needs. Expert validation identified at least half of the ideas were very important and feasible, while most of the guiding principles of the Ophelia process were successfully applied.Conclusion: By harnessing collective creativity through co-design, the Ophelia process has been shown to assist the development of solutions with the potential to improve health and equity outcomes in the digital context. Implementation of the solutions is needed to provide further evidence of the impact of the process. The suggested inclusion of non-digital solutions revealed through the co-design process reminds health organizations and policymakers that solutions should be flexible enough to suit individual needs. As such, taking a co-design approach to digital health initiatives will assist in preventing the widening of health inequalities.