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The adoption of mobile health (m-Health) applications (apps) has been widely studied, but its continuance has not. This study endeavors to address this gap by examining the factors that motivate the continued use of m-Health using consumers of sugar-related mobile apps in Australia as a case. To do so, this study extrapolates the technology acceptance model for technology adoption to explain the technology continuance of m-Health by adapting and extending its associated tenets informed by prior literature. This study also performs structural equation modeling on a sample of 306 usable responses from a randomly crowdsource online survey of sugar-related mobile app users in Australia. In doing so, this study finds that consumers' continuance intention of m-Health apps is driven primarily by the ease of using and social influence toward such apps. Upon further scrutiny, this study observes that the influence of usefulness and enjoyment of such apps on continuance intention is fully mediated and thus manifests indirectly through the usage habits shaped by the ease of m-Health app usage. The implications of the findings for theory and practice and the limitations of and future research directions from the study conclude the paper. [ABSTRACT FROM AUTHOR]

Addressing the needs of ethnically diverse multilingual people can be challenging in environments that are non-native to them. The consequences of this issue become more significant in healthcare contexts. Insights from the DrawCare study-an Australian study that explores the effectiveness of a web-based intervention for multilingual family carers of people with dementia-are presented illustrating the enabling role of digital health.

This study assesses smokers' perceptions, motivations, and intentions towards using an SMS-assisted smoking cessation intervention in Australia, France, and Mexico through an extended technology acceptance model with mediating variables. Data was collected through online surveys. Results show that perceived usefulness and vicarious innovativeness predict use intentions for all three countries. Perceived ease of use is significant only for Mexico. Subjective norms are significant only for Mexico and Australia. Perceived monetary value and perceived annoyance are significant mediating variables for all three countries, whereas perceived enjoyment is significant only for Mexico and Australia. These results contribute to theory and practice. [ABSTRACT FROM AUTHOR]

Pollen is a well-established trigger of asthma and allergic rhinitis, yet concentration-response relationships, lagged effects, and interactions with other environmental factors remain poorly understood. Smartphone technology offers an opportunity to address these challenges using large, multi-year datasets that capture individual symptoms and exposures in real time. We aimed to characterise associations between six pollen types and respiratory symptoms logged by users of the AirRater smartphone app in Tasmania, Australia. We analyzed 44,820 symptom reports logged by 2272 AirRater app users in Tasmania over four years (2015–2019). With these data we evaluated associations between daily respiratory symptoms and atmospheric pollen concentrations. We implemented Poisson regression models, using the case time series approach designed for app-sourced data. We assessed potentially non-linear and lagged associations with (a) total pollen and (b) six individual pollen taxa. We adjusted for seasonality and meteorology and tested for interactions with particulate air pollution (PM 2.5). We found evidence of non-linear associations between total pollen and respiratory symptoms for up to three days following exposure. For total pollen, the same-day relative risk (RR) increased to 1.31 (95% CI: 1.26–1.37) at a concentration of 50 grains/m3 before plateauing. Associations with individual pollen taxa were also non-linear with some diversity in shapes. For all pollen taxa the same-day RR was highest. The interaction between total pollen and PM 2.5 was positive, with risks associated with pollen significantly higher in the presence of high concentrations of PM 2.5. Our results support a non-linear response between airborne pollen and respiratory symptoms. The association was strongest on the day of exposure and synergistic with particulate air pollution. The associations found with Dodonaea and Myrtaceae highlight the need to further investigate the role of Australian native pollen types in allergic respiratory disease. [ABSTRACT FROM AUTHOR]

Asthma and allergic rhinitis (or hay fever) are ubiquitous, chronic health conditions that seasonally affect a sizeable proportion of the population. Both are commonly triggered or exacerbated by environmental conditions including aeroallergens, air quality and weather. Smartphone technology offers new opportunities to identify environmental drivers by allowing large-scale, real-time collection of day-to-day symptoms. As yet, however, few studies have explored the potential of this technology to provide useful epidemiological data on environment-symptom relationships. Here, we use data from the smartphone app 'AirRater' to examine relationships between asthma and allergic rhinitis symptoms and weather, air quality and pollen loads in Hobart, Tasmania, Australia. We draw on symptom data logged by app users over a three-year period and use time-series analysis to assess the relationship between symptoms and environmental co-variates. Symptoms are associated with particulate matter (IRR 1.06, 95% CI: 1.04–1.08), maximum temperature (IRR 1.28, 95% CI: 1.13–1.44) and pollen taxa including Betula (IRR 1.04, 95% CI: 1.02–1.07), Cupressaceae (IRR 1.02, 95% CI: 1.01–1.04), Myrtaceae (IRR 1.06, 95% CI: 1.02–1.10) and Poaceae (IRR 1.05, 95% CI: 1.01–1.09). The importance of these pollen taxa varies seasonally and more taxa are associated with allergic rhinitis (eye/nose) than asthma (lung) symptoms. Our results are congruent with established epidemiological evidence, while providing important local insights including the association between symptoms and Myrtaceae pollen. We conclude that smartphone-sourced data can be a useful tool in environmental epidemiology. • In Tasmania, Australia, the AirRater smartphone app collects respiratory symptoms. • Particulate matter is associated with app-user reported symptoms all year round. • Maximum temperature is associated with symptoms during the warmer months. • Australian native pollen taxa are seasonally associated with app-reported respiratory symptoms. [ABSTRACT FROM AUTHOR]

Background: This study compared the efficacy of two multi-component m-health interventions with a wait-list control group on body weight (primary outcome), and secondary outcomes of cardiovascular risk factors, lifestyle behaviours, and mental health., Methods: Three-arm randomised controlled trial (Enhanced: physical activity, diet, sleep, Traditional: physical activity, diet, Control) with assessments conducted at baseline, 6 and 12 months. Participants ( n = 116) were overweight or obese adults aged 19-65 (M = 44.5 [SD = 10.5]). The 6-month intervention was delivered via a smartphone app providing educational materials, goal-setting, self-monitoring and feedback, and also included one face-to-face dietary consultation, a Fitbit and scales. The trial was prospectively registered and conducted between May 2017 and September 2018. Group differences on primary and secondary outcomes were examined between the Pooled Intervention groups (Pooled Intervention = Enhanced and Traditional) and Control groups, and then between Enhanced and Traditional groups., Results: Nineteen participants (16.4%) formally withdrew from the trial. Compared with the Control group, average body weight of the Pooled Intervention group did not differ at 6 (between-group difference = -0.92, (95% CI -3.33, 1.48)) or 12 months (0.00, (95% CI -2.62, 2.62)). Compared with the Control group, the Pooled Intervention group significantly increased resistance training (OR = 7.83, (95% CI 1.08, 56.63)) and reduced energy intake at 6 months (-1037.03, (-2028.84, -45.22)), and improved insomnia symptoms at 12 months (-2.59, (-4.79, -0.39)). Compared with the Traditional group, the Enhanced group had increased waist circumferences (2.69, (0.20, 5.18)) and sedentary time at 6 months (105.66, (30.83, 180.48)), and improved bed time variability at 12 months (-1.08, (-1.86, -0.29)). No other significant differences were observed between groups., Conclusions: Relative to Controls, the Pooled Intervention groups did not differ on body weight but improved resistance training, and reduced energy intake and insomnia symptom severity. No additional weight loss was apparent when targeting improvements in physical activity, diet and sleep in combination compared with physical activity and diet.

Background: Scalable interventions that improve the nutritional quality of foods in children's lunchboxes have considerable potential to improve child public health nutrition. This study assessed the potential efficacy, feasibility and acceptability of an m-health intervention, 'SWAP IT', to improve the energy and nutritional quality of foods packed in children's lunchboxes. Methods: The study employed a 2X2 factorial cluster randomized-controlled trial design. Twelve primary schools in New South Wales, Australia were randomly allocated to one of four groups: (i) no intervention;(ii) physical activity intervention only;(iii) lunchbox intervention only; or(iv) physical activity and lunchbox intervention combined. The two intervention strategies were evaluated separately. This paper focuses on the effects of the lunchbox intervention only. The lunchbox intervention comprised four strategies: 1) school nutrition guidelines; 2) lunchbox lessons; 3) information pushed to parents via a school-communication app and 4) parent resources addressing barriers to packing healthy lunchboxes. Outcome measures were taken at baseline and immediately post-intervention (10 weeks) and included measures of effectiveness (mean energy (kJ) packed in lunchboxes, total energy and percentage energy from recommended foods consistent with Australian Dietary Guidelines), feasibility (of delivering intervention to schools, parent app engagement and behaviour change) and acceptability to school staff and parents. Linear mixed models were used to assess intervention efficacy. Results: Of the 1915 lunchbox observations, at follow-up there was no significant differences between intervention and control group in mean energy of foods packed within lunchboxes (− 118.39 kJ, CI = -307.08, 70.30, p = 0.22). There was a significant increase favouring the intervention in the secondary outcome of mean lunchbox energy from recommended foods (79.21 kJ, CI = 1.99, 156.43, p = 0.04), and a non-significant increase in percentage of lunchbox energy from recommended foods in intervention schools (4.57%, CI = -0.52, 9.66, p = 0.08). The views of the messages pushed via the app ranged from 387 to 1550 views per week (mean views =1025 per week). A large proportion (71%) of parents reported awareness of the intervention, making healthier swaps in the lunchbox (55%), and pushed content was helpful (84%). Conclusion: The study is the first RCT to assess the potential of a multi-component m-health lunchbox intervention. The intervention was feasible, acceptable and potentially effective in improving the nutritional quality of foods packed within children's lunchboxes. Trial registration: Australian Clinical Trials Registry ACTRN: ACTRN12616001228471. [ABSTRACT FROM AUTHOR]

Objective: Integrating mobile phone-based health (m-health) interventions into healthcare systems is one solution to improve access to services for the growing number of patients with chronic illness. Practical challenges such as poor recruitment and inadequate resource allocation can hamper the assessment of such interventions with clinical trial methodology. This paper highlights the challenges encountered during a pilot randomized controlled trial of an m-health medication adherence intervention and offers recommendations for future multi-site, non-drug clinical trials., Results: Eighteen patients were recruited to the study; eight were randomly allocated to the intervention arm. Intervention participants responded to their daily medication-reminder text messages, indicating that medication had been taken or not, and nurses were able to organize their calls around their workload. The trial closed prematurely primarily due to inadequate numbers of eligible patients; however, other potentially resolvable feasibility issues were identified. These included lack of infrastructure at study sites, poor screening data acquisition and management processes, and inexperience in conducting supportive care trials at participating sites. M-health intervention trials are designed to inform implementation of best supportive care practice. Adequate skills and infrastructure are research prerequisites that require careful consideration and sufficient investment for the successful execution of multi-site supportive care trials. Trial registration Australian and New Zealand Clinical Trials Register: ACTRN12612000635864.

Introduction: Adults with lower levels of health literacy are less likely to engage in health-promoting behaviours. Our trial evaluates the impacts and outcomes of a mobile health-enhanced preventive intervention in primary care for people who are overweight or obese., Methods and Analysis: A two-arm pragmatic practice-level cluster randomised trial will be conducted in 40 practices in low socioeconomic areas in Sydney and Adelaide, Australia. Forty patients aged 40-70 years with a body mass index ≥28 kg/m 2 will be enrolled per practice. The HeLP-general practitioner (GP) intervention includes a practice-level quality improvement intervention (medical record audit and feedback, staff training and practice facilitation visits) to support practices to implement the clinical intervention for patients. The clinical intervention involves a health check visit with a practice nurse based on the 5As framework (assess, advise, agree, assist and arrange), the use of a purpose-built patient-facing app, my snapp , and referral for telephone coaching. The primary outcomes are change in health literacy, lifestyle behaviours, weight, waist circumference and blood pressure. The study will also evaluate changes in quality of life and health service use to determine the cost-effectiveness of the intervention and examine the experiences of practices in implementing the programme., Ethics and Dissemination: The study has been approved by the University of New South Wales (UNSW) Human Research Ethics Committee (HC17474) and ratified by the University of Adelaide Human Research Ethics committee. There are no restrictions on publication, and findings of the study will be made available to the public via the Centre for Primary Health Care and Equity website and through conference presentations and research publications. Deidentified data and meta-data will be stored in a repository at UNSW and made available subject to ethics committee approval., Trial Registrationregistration Number: ACTRN12617001508369; Pre-results., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)