The novel coronavirus (COVID-19) has enforced dramatic changes to daily living including economic and health impacts. Evidence for the impact of these changes on our physical and mental health and health behaviors is limited. We examined the associations between psychological distress and changes in selected health behaviors since the onset of COVID-19 in Australia. An online survey was distributed in April 2020 and included measures of depression, anxiety, stress, physical activity, sleep, alcohol intake and cigarette smoking. The survey was completed by 1491 adults (mean age 50.5 ± 14.9 years, 67% female). Negative change was reported for physical activity (48.9%), sleep (40.7%), alcohol (26.6%) and smoking (6.9%) since the onset of the COVID-19 pandemic. Significantly higher scores in one or more psychological distress states were found for females, and those not in a relationship, in the lowest income category, aged 18–45 years, or with a chronic illness. Negative changes in physical activity, sleep, smoking and alcohol intake were associated with higher depression, anxiety and stress symptoms. Health-promotion strategies directed at adopting or maintaining positive health-related behaviors should be utilized to address increases in psychological distress during the pandemic. Ongoing evaluation of the impact of lifestyle changes associated with the pandemic is needed.

Background: Health and fitness applications (apps) have gained popularity in interventions to improve diet, physical activity and sedentary behaviours but their efficacy is unclear. This systematic review examined the efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour in children and adults. Methods: Systematic literature searches were conducted in five databases to identify papers published between 2006 and 2016. Studies were included if they used a smartphone app in an intervention to improve diet, physical activity and/or sedentary behaviour for prevention. Interventions could be stand-alone interventions using an app only, or multi-component interventions including an app as one of several intervention components. Outcomes measured were changes in the health behaviours and related health outcomes (i.e., fitness, body weight, blood pressure, glucose, cholesterol, quality of life). Study inclusion and methodological quality were independently assessed by two reviewers. Results: Twenty-seven studies were included, most were randomised controlled trials (n = 19; 70%). Twenty-three studies targeted adults (17 showed significant health improvements) and four studies targeted children (two demonstrated significant health improvements). Twenty-one studies targeted physical activity (14 showed significant health improvements), 13 studies targeted diet (seven showed significant health improvements) and five studies targeted sedentary behaviour (two showed significant health improvements). More studies (n = 12; 63%) of those reporting significant effects detected between-group improvements in the health behaviour or related health outcomes, whilst fewer studies (n = 8; 42%) reported significant within-group improvements. A larger proportion of multi-component interventions (8 out of 13; 62%) showed significant between-group improvements compared to stand-alone app interventions (5 out of 14; 36%). Eleven studies reported app usage statistics, and three of them demonstrated that higher app usage was associated with improved health outcomes. Conclusions: This review provided modest evidence that app-based interventions to improve diet, physical activity and sedentary behaviours can be effective. Multi-component interventions appear to be more effective than standalone app interventions, however, this remains to be confirmed in controlled trials. Future research is needed on the optimal number and combination of app features, behaviour change techniques, and level of participant contact needed to maximise user engagement and intervention efficacy.

Engagement in electronic health (eHealth) and mobile health (mHealth) behavior change interventions is thought to be important for intervention effectiveness, though what constitutes engagement and how it enhances efficacy has been somewhat unclear in the literature. Recently published detailed definitions and conceptual models of engagement have helped to build consensus around a definition of engagement and improve our understanding of how engagement may influence effectiveness. This work has helped to establish a clearer research agenda. However, to test the hypotheses generated by the conceptual modules, we need to know how to measure engagement in a valid and reliable way. The aim of this viewpoint is to provide an overview of engagement measurement options that can be employed in eHealth and mHealth behavior change intervention evaluations, discuss methodological considerations, and provide direction for future research. To identify measures, we used snowball sampling, starting from systematic reviews of engagement research as well as those utilized in studies known to the authors. A wide range of methods to measure engagement were identified, including qualitative measures, self-report questionnaires, ecological momentary assessments, system usage data, sensor data, social media data, and psychophysiological measures. Each measurement method is appraised and examples are provided to illustrate possible use in eHealth and mHealth behavior change research. Recommendations for future research are provided, based on the limitations of current methods and the heavy reliance on system usage data as the sole assessment of engagement. The validation and adoption of a wider range of engagement measurements and their thoughtful application to the study of engagement are encouraged.

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Probiotic supplements have a positive impact on several health outcomes. However, the majority of published studies have focused on populations with specific health pathologies. Therefore, this study reviewed the current literature on the health effects of probiotic consumption in "healthy adults." The findings from this review may help guide consumers, researchers, and manufacturers regarding probiotic supplementation. Relevant literature published between 1990 and August 2017 was reviewed. Studies were included if they were experimental trials, included healthy adults, used live bacteria, and had accessible full-text articles published in English. Included studies were classified according to common foci that emerged. Forty-five studies were included in this review. Five foci emerged: gut microbiota changes (n = 15); immune system response (n = 16); lipid profile and cardiovascular disease risk (n = 14); gastrointestinal discomfort (n = 11); and female reproductive health (n = 4). Results suggest that probiotic supplementation in healthy adults can lead to transient improvement in gut microbiota concentration of supplement-specific bacteria. Evidence also supports the role of probiotics in improving immune system responses, stool consistency, bowel movement, and vaginal lactobacilli concentration. There is insufficient evidence to support the role of probiotics to improve blood lipid profile. Probiotic consumption can improve in the immune, gastrointestinal, and female reproductive health systems in healthy adults. However, this review failed to support the ability of probiotics to cause persistent changes in gut microbiota, or improve lipid profile in healthy adults. The feasibility of probiotics consumption to provide benefits in healthy adults requires further investigation.