A systematic review of digital interventions for improving the diet and physical activity behaviors of adolescents

Many adolescents have poor diet and physical activity behaviors, which can lead to the development of noncommunicable diseases in later life. Digital platforms offer inexpensive means of delivering health interventions, but little is known about their effectiveness. This systematic review was conducted to synthesize evidence on the effectiveness of digital interventions to improve diet quality and increase physical activity in adolescents, to effective intervention components and to assess the cost-effectiveness of these interventions. Following a systematic search, abstracts were assessed against inclusion criteria, and data extraction and quality assessment were performed for included studies. Data were analyzed to identify key features that are associated with significant improvement in behavior. A total of 27 studies met inclusion criteria. Most (n = 15) were Web site interventions. Other delivery methods were text messages, games, multicomponent interventions, emails, and social media. Significant behavior change was often seen when interventions included education, goal setting, self-monitoring, and parental involvement. None of the publications reported cost-effectiveness. Due to heterogeneity of studies, meta-analysis was not feasible.It is possible to effect significant health behavior change in adolescents through digital interventions that incorporate education, goal setting, self-monitoring, and parental involvement. Most of the evidence relates to Web sites and further research into alternate media is needed, and longer term outcomes should be evaluated. There is a paucity of data on the cost-effectiveness of digital health interventions, and future trials should report these data

Comparing usage of a web and app stress management intervention : an observational study

Choices in the design and delivery of digital health behaviour interventions may have a direct influence on subsequent usage and engagement. Few studies have been able to make direct, detailed comparisons of differences in usage between interventions that are delivered via web or app. This study compared the usage of two versions of a digital stress management intervention, one delivered via a website (Healthy Paths) and the other delivered via an app (Healthy Mind). Design modifications were introduced within Healthy Mind to take account of reported differences in how individuals engage with websites compared to apps and mobile phones. Data were collected as part of an observational study nested within a broader exploratory trial of Healthy Mind. Objective usage of Healthy Paths and Healthy Mind were automatically recorded, including frequency and duration of logins, access to specific components within the intervention and order of page/screen visits. Usage was compared for a two week period following initial registration. In total, 381 participants completed the registration process for Healthy Paths (web) and 162 participants completed the registration process for Healthy Mind (app). App users logged in twice as often (Mdn = 2.00) as web users (Mdn = 1.00), U = 13,059.50, p ≤ 0.001, but spent half as much time (Mdn = 5.23 min) on the intervention compared to web users (Mdn = 10.52 min), U = 19,740.00, p ≤ 0.001. Visual exploration of usage patterns over time revealed that a significantly higher proportion of app users (n = 126, 82.35%) accessed both types of support available within the intervention (i.e. awareness and change-focused tools) compared to web users (n = 92, 40.17%), χ2(1, n = 382) = 66.60, p < 0.001. This study suggests that the digital platform used to deliver an intervention (i.e. web versus app) and specific design choices (e.g. navigation, length and volume of content) may be associated with differences in how the intervention content is used. Broad summative usage data (e.g. total time spent on the intervention) may mask important differences in how an intervention is used by different user groups if it is not complemented by more fine-grained analyses of usage patterns over time. Trial registration number: ISRCTN67177737

Understanding and Promoting Effective Engagement With Digital Behavior Change Interventions.

This is the author accepted manuscript. The final version is available from Elsevier via https://doi.org/10.1016/j.amepre.2016.06.015This paper is one in a series developed through a process of expert consensus to provide an overview of questions of current importance in research into engagement with digital behavior change interventions, identifying guidance based on research to date and priority topics for future research. The first part of this paper critically reflects on current approaches to conceptualizing and measuring engagement. Next, issues relevant to promoting effective engagement are discussed, including how best to tailor to individual needs and combine digital and human support. A key conclusion with regard to conceptualizing engagement is that it is important to understand the relationship between engagement with the digital intervention and the desired behavior change. This paper argues that it may be more valuable to establish and promote "effective engagement," rather than simply more engagement, with "effective engagement" defined empirically as sufficient engagement with the intervention to achieve intended outcomes. Appraisal of the value and limitations of methods of assessing different aspects of engagement highlights the need to identify valid and efficient combinations of measures to develop and test multidimensional models of engagement. The final section of the paper reflects on how interventions can be designed to fit the user and their specific needs and context. Despite many unresolved questions posed by novel and rapidly changing technologies, there is widespread consensus that successful intervention design demands a user-centered and iterative approach to development, using mixed methods and in-depth qualitative research to progressively refine the intervention to meet user requirements.This paper is one of the outputs of two workshops, one supported by the Medical Research Council (MRC)/National Institute for Health Research (NIHR) Methodology Research Programme (PI Susan Michie) and the Robert Wood Johnson Foundation (PI Kevin Patrick), and the other by the National Science Foundation (PI Donna Spruitj-Metz, proposal # 1539846)

A Framework for Analyzing and Measuring Usage and Engagement Data (AMUsED) in Digital Interventions:Viewpoint

Trials of digital interventions can yield extensive, in-depth usage data, yet usage analyses tend to focus on broad descriptive summaries of how an intervention has been used by the whole sample. This paper proposes a novel framework to guide systematic, fine-grained usage analyses that better enables understanding of how an intervention works, when, and for whom. The framework comprises three stages to assist in the following: (1) familiarization with the intervention and its relationship to the captured data, (2) identification of meaningful measures of usage and specifying research questions to guide systematic analyses of usage data, and (3) preparation of datasheets and consideration of available analytical methods with which to examine the data. The framework can be applied to inform data capture during the development of a digital intervention and/or in the analysis of data after the completion of an evaluation trial. We will demonstrate how the framework shaped preparation and aided efficient data capture for a digital intervention to lower transmission of cold and flu viruses in the home, as well as how it informed a systematic, in-depth analysis of usage data collected from a separate digital intervention designed to promote self-management of colds and flu. The Analyzing and Measuring Usage and Engagement Data (AMUsED) framework guides systematic and efficient in-depth usage analyses that will support standardized reporting with transparent and replicable findings. These detailed findings may also enable examination of what constitutes effective engagement with particular interventions

Eliciting and prioritising determinants of improved care in multimorbidity: A modified online Delphi study

BACKGROUND: Multimorbidity is a major challenge to health and social care systems around the world. There is limited research exploring the wider contextual determinants that are important to improving care for this cohort. In this study, we aimed to elicit and prioritise determinants of improved care in people with multiple conditions. METHODS: A three-round online Delphi study was conducted in England with health and social care professionals, data scientists, researchers, people living with multimorbidity and their carers. RESULTS: Our findings suggest a care system which is still predominantly single condition focused. 'Person-centred and holistic care' and 'coordinated and joined up care', were highly rated determinants in relation to improved care for multimorbidity. We further identified a range of non-medical determinants that are important to providing holistic care for this cohort. CONCLUSIONS: Further progress towards a holistic and patient-centred model is needed to ensure that care more effectively addresses the complex range of medical and non-medical needs of people living with multimorbidity. This requires a move from a single condition focused biomedical model to a person-based biopsychosocial approach, which has yet to be achieved

Insomnia in breast cancer : a prospective observational study

STUDY OBJECTIVES: Insomnia in cancer patients is prevalent, persistent and confers risk for physical and psychological disorder. We must better understand how insomnia develops in cancer patients and explore the main contributors to its chronicity so that insomnia management protocols can be integrated more effectively within cancer care. This study monitors the etiology of insomnia in breast cancer patients and identifies risk factors for its persistence. METHODS: 173 females with newly diagnosed, non-metastatic breast cancer were tracked from diagnosis for 12-months. Participants completed monthly sleep assessments using the Insomnia Severity Index (ISI) and 3-monthly health-related quality-of-life assessments using the European Organisation for Research and Treatment of Cancer - Breast (EORTC QLQ-C30-BR23) scale. Clinical data on disease status and treatment regimens were also assessed. RESULTS: Prior to diagnosis, 25% of participants reported sleep disturbance, including 8% with insomnia syndrome (IS). Prevalence increased at cancer diagnosis to 46% (18% IS) and remained stable thereafter at around 50% (21% IS). We also explored sleep status transitions. The most common pattern was to remain a good sleeper (34%-49%) or to persist with insomnia (23%-46%). 77% of good sleepers developed insomnia during the 12-month period and 54% went into insomnia remission. Chemotherapy (odds ratio=0·08, 95% ci 0·02-0·29, p<·001) and pre-diagnosis ISI scores (odds ratio=1·13/unit increase in pre-diagnosis sleep score, 95% ci 1·05-1·21, p=·001) were identified as the main risk factors for persistent insomnia. CONCLUSIONS: These data advance our understanding of insomnia etiology in cancer patients and help identify those who should be prioritised for insomnia management protocols

Harnessing Placebo Effects in Primary Care: Using the Person-Based Approach to Develop an Online Intervention to Enhance Practitioners' Communication of Clinical Empathy and Realistic Optimism During Consultations.

Background: Empathic communication and positive messages are important components of "placebo" effects and can improve patient outcomes, including pain. Communicating empathy and optimism to patients within consultations may also enhance the effects of verum, i.e., non-placebo, treatments. This is particularly relevant for osteoarthritis, which is common, costly and difficult to manage. Digital interventions can be effective tools for changing practitioner behavior. This paper describes the systematic planning, development and optimization of an online intervention-"Empathico"-to help primary healthcare practitioners enhance their communication of clinical empathy and realistic optimism during consultations. Methods: The Person-Based Approach to intervention development was used. This entailed integrating insights from placebo and behavior change theory and evidence, and conducting primary and secondary qualitative research. Systematic literature reviews identified barriers, facilitators, and promising methods for enhancing clinical empathy and realistic optimism. Qualitative studies explored practitioners' and patients' perspectives, initially on the communication of clinical empathy and realistic optimism and subsequently on different iterations of the Empathico intervention. Insights from the literature reviews, qualitative studies and public contributor input were integrated into a logic model, behavioral analysis and principles that guided intervention development and optimization. Results: The Empathico intervention comprises 7 sections: Introduction, Empathy, Optimism, Application of Empathico for Osteoarthritis, Reflection on my Consultations, Setting Goals and Further Resources. Iterative refinement of Empathico, using feedback from patients and practitioners, resulted in highly positive feedback and helped to (1) contextualize evidence-based recommendations from placebo studies within the complexities of primary healthcare consultations and (2) ensure the intervention addressed practitioners' and patients' concerns and priorities. Conclusions: We have developed an evidence-based, theoretically-grounded intervention that should enable practitioners to better harness placebo effects of communication in consultations. The extensive use of qualitative research throughout the development and optimization process ensured that Empathico is highly acceptable and meaningful to practitioners. This means that practitioners are more likely to engage with Empathico and make changes to enhance their communication of clinical empathy and realistic optimism in clinical practice. Empathico is now ready to be evaluated in a large-scale randomized trial to explore its impact on patient outcomes