scholarly journals Personalization Dimensions for MHealth to Improve Behavior Change: A Scoping Review

2020 ◽  
Author(s):  
Laëtitia Gosetto ◽  
Frédéric Ehrler ◽  
Gilles Falquet
Keyword(s):  
Literature Review ◽  
Health Behavior ◽  
Behavior Change ◽  
Social Norms ◽  
Scoping Review ◽  
Need For Cognition ◽  
Health Behavior Change ◽  
Popular Support ◽  
Information Dimension ◽  
The Way

Due to the large number of smartphone users, mHealth has become a popular support to foster users’ health behavior change Personalization is an important factor to increase the effectiveness of mHealth interventions. Based on a literature review, we have listed and categorized personalization concepts associated with behavior change in mHealth into 4 dimensions, users, system functionalities, information, and app properties. The users dimension refers to user-related characteristics such as personality, player profile, need for cognition and perception of social norms. The system functionalities contain the functionalities that can be found in applications such as reminders as well as gamification functionalities such as collectibles. The information dimension concerns the way information is transmitted, such as the source of the message must be expert or the type of feedback to be provided. Finally, there are app properties such as the aesthetics of the application. For the next part, it would be interesting to discover the links we can make between the dimensions.

Multiple Health Behavior Change for Weight Loss: A Scoping Review

2020 ◽  
Vol 44 (5) ◽  
pp. 559-571
Author(s):  
Megan S. Maisano ◽  
Eleanor T. Shonkoff ◽  
Sara C. Folta
Keyword(s):  
Weight Loss ◽  
Health Behavior ◽  
Behavior Change ◽  
Scoping Review ◽  
Transtheoretical Model ◽  
Cognitive Theory ◽  
Health Behavior Change ◽  
Risk Level ◽  
Multiple Health Behavior Change ◽  
Multiple Health

Objectives: In this scoping review, we examine the current state of literature on weight-related Multiple Health Behavior Change (MHBC). Specifically, we investigate: (1) MHBC versus single health behavior change (SHBC) interventions and (2) simultaneous versus sequential MHBC approaches. Secondarily, we explore (3) attributes that predict success in MHBC, and (4) the utilization of theoretical frameworks. Methods: We retrieved studies from PubMed, Web of Science, and Google Scholar within the 2000 to 2018 range. Results: MHBC interventions proved superior for long-term weight loss when compared to SHBC approaches. However, the literature is limited. Studies investigating simultaneous and sequential MHBC approaches are also limited and have mixed results. Predictive characteristics of MHBC include behavior adherence, risk level, stage of change, self-efficacy, social support, environmental barriers, and treatment approaches. Whereas evidence evaluating theory in MHBC programs remains scant, there is promising research on constructs from the Transtheoretical Model and Social Cognitive Theory. Conclusions: MHBC approaches may better support weight loss efforts. However, further research is needed to understand the effects of behavior change order and timing, predictive features of participants and interventions, and theoretical framework utilization in these weight-loss programs.

scholarly journals Utilizing Health Behavior Change and Technology Acceptance Models to Predict the Adoption of COVID-19 Contact Tracing Apps: Cross-sectional Survey Study (Preprint)

2020 ◽  
Author(s):  
Samuel Tomczyk ◽  
Simon Barth ◽  
Silke Schmidt ◽  
Holger Muehlan
Keyword(s):  
General Population ◽  
Health Behavior ◽  
Behavior Change ◽  
Social Norms ◽  
Technology Acceptance ◽  
Health Behavior Change ◽  
Contact Tracing ◽  
Cross Sectional ◽  
Privacy Concerns ◽  
Technology Acceptance Models

BACKGROUND To combat the global COVID-19 pandemic, contact tracing apps have been discussed as digital health solutions to track infection chains and provide appropriate information. However, observational studies point to low acceptance in most countries, and few studies have yet examined theory-based predictors of app use in the general population to guide health communication efforts. OBJECTIVE This study utilizes established health behavior change and technology acceptance models to predict adoption intentions and frequency of current app use. METHODS We conducted a cross-sectional online survey between May and July 2020 in a German convenience sample (N=349; mean age 35.62 years; n=226, 65.3% female). To inspect the incremental validity of model constructs as well as additional variables (privacy concerns, personalization), hierarchical regression models were applied, controlling for covariates. RESULTS The theory of planned behavior and the unified theory of acceptance and use of technology predicted adoption intentions (R<sup>2</sup>=56%-63%) and frequency of current app use (R<sup>2</sup>=33%-37%). A combined model only marginally increased the predictive value by about 5%, but lower privacy concerns and higher threat appraisals (ie, anticipatory anxiety) significantly predicted app use when included as additional variables. Moreover, the impact of perceived usefulness was positive for adoption intentions but negative for frequency of current app use. CONCLUSIONS This study identified several theory-based predictors of contact tracing app use. However, few constructs, such as social norms, have a consistent positive effect across models and outcomes. Further research is required to replicate these observations, and to examine the interconnectedness of these constructs and their impact throughout the pandemic. Nevertheless, the findings suggest that promulgating affirmative social norms and positive emotional effects of app use, as well as addressing health concerns, might be promising strategies to foster adoption intentions and app use in the general population. CLINICALTRIAL

Using Biological Feedback to Promote Health Behavior Change in Adults: Protocol for a Scoping Review (Preprint)

2021 ◽  
Author(s):  
Kelli Marie Richardson ◽  
Ahlam A Saleh ◽  
Michelle R Jospe ◽  
Yue Liao ◽  
Susan Schembre
Keyword(s):  
Health Behavior ◽  
Behavior Change ◽  
Scoping Review ◽  
Health Behavior Change ◽  
Controlled Trials ◽  
Cochrane Central Register ◽  
Biological Feedback ◽  
Design And Implementation ◽  
Behavior Change Interventions ◽  
Wide Range

BACKGROUND Many health conditions can be prevented, managed, or improved through behavioral interventions. Biological feedback, as a component of health behavior change interventions, is of particular interest given recent advances in wearable biosensing technology, digital health apps, and personalized health and wellness. Yet, there is a paucity of literature to guide the design and implementation of interventions that incorporate biological feedback to motivate health behavior change. OBJECTIVE The goal of this scoping review is to deeply explore the use of biological feedback as a component of health behavior change interventions that target adults. Objectives of the review include: (1) mapping the domains of research that incorporate biological feedback and (2) describing the operational characteristics of using biological feedback in the context of health behavior change. METHODS A comprehensive list of search terms was developed to capture studies from a wide range of domains. Studies to be included are randomized controlled trials targeting adults ≥18 years old that use biological feedback to change a health-related behavior, and are published as primary research articles, theses, or dissertations. The following electronic databases were searched: Ovid MEDLINE, Embase.com Embase, Cochrane Central Register of Controlled Trials, EBSCOhost PsycINFO, and ProQuest Dissertations & Theses Global. The screening and data extraction process will be guided by the Joanna Briggs Institute Manual for Evidence Synthesis and conducted by trained reviewers. RESULTS Database searches were completed in June 2021. A total of 50,459 unique records were returned after the removal of 48,634 duplicate records. The scoping review is planned for completion in 2022. CONCLUSIONS To our knowledge, this will be the first scoping review to map the literature that uses biological feedback as a component of health behavior change interventions targeting adults. Findings will be used to develop a framework to guide the design and implementation of future health behavior change interventions that incorporate biological feedback. CLINICALTRIAL 10.17605/OSF.IO/YP5WA

scholarly journals Digital Health Behavior Change Technology: Bibliometric and Scoping Review of Two Decades of Research

10.2196/13311 ◽  
2019 ◽  
Vol 7 (12) ◽  
pp. e13311 ◽  
Author(s):  
Fawad Taj ◽  
Michel C A Klein ◽  
Aart van Halteren
Keyword(s):  
Physical Activity ◽  
Health Behavior ◽  
Behavior Change ◽  
Scoping Review ◽  
Behavioral Change ◽  
Digital Technologies ◽  
Health Behavior Change ◽  
The United States ◽  
Behavior Change Techniques ◽  
Research Areas

Background Research on digital technology to change health behavior has increased enormously in recent decades. Due to the interdisciplinary nature of this topic, knowledge and technologies from different research areas are required. Up to now, it is not clear how the knowledge from those fields is combined in actual applications. A comprehensive analysis that systematically maps and explores the use of knowledge within this emerging interdisciplinary field is required. Objective This study aims to provide an overview of the research area around the design and development of digital technologies for health behavior change and to explore trends and patterns. Methods A bibliometric analysis is used to provide an overview of the field, and a scoping review is presented to identify the trends and possible gaps. The study is based on the publications related to persuasive technologies and health behavior change in the last 18 years, as indexed by the Web of Science and Scopus (317 and 314 articles, respectively). In the first part, regional and time-based publishing trends; research fields and keyword co-occurrence networks; influential journals; and collaboration network between influential authors, countries, and institutions are examined. In the second part, the behavioral domains, technological means and theoretical foundations are investigated via a scoping review. Results The literature reviewed shows a clear and emerging trend after 2001 in technology-based behavior change, which grew exponentially after the introduction of the smartphone around 2009. Authors from the United States, Europe, and Australia have the highest number of publications in the field. The three most active research areas are computer science, public and occupational health, and psychology. The keyword “mhealth” was the dominant term and predominantly used together with the term “physical activity” and “ehealth”. A total of three strong clusters of coauthors have been found. Nearly half of the total reported papers were published in three journals. The United States, the United Kingdom, and the Netherlands have the highest degree of author collaboration and a strong institutional network. Mobile phones were most often used as a technology platform, regardless of the targeted behavioral domain. Physical activity and healthy eating were the most frequently targeted behavioral domains. Most articles did not report about the behavior change techniques that were applied. Among the reported behavior change techniques, goal setting and self-management were the most frequently reported. Conclusions Closer cooperation and interaction between behavioral sciences and technological areas is needed, so that theoretical knowledge and new technological advancements are better connected in actual applications. Eventually, this could result in a larger societal impact, an increase of the effectiveness of digital technologies for health behavioral change, and more insight in the relationship between behavioral change strategies and persuasive technologies' effectiveness.

scholarly journals Using Biological Feedback to Promote Health Behavior Change in Adults: Protocol for a Scoping Review (Preprint)

10.2196/32579 ◽  
2021 ◽  
Author(s):  
Kelli Marie Richardson ◽  
Ahlam A Saleh ◽  
Michelle R Jospe ◽  
Yue Liao ◽  
Susan Schembre
Keyword(s):  
Health Behavior ◽  
Behavior Change ◽  
Scoping Review ◽  
Health Behavior Change ◽  
Biological Feedback

Digital Health Behavior Change Technology: Bibliometric and Scoping Review of Two Decades of Research (Preprint)

2019 ◽  
Author(s):  
Fawad Taj ◽  
Michel C A Klein ◽  
Aart van Halteren
Keyword(s):  
Physical Activity ◽  
Health Behavior ◽  
Behavior Change ◽  
Scoping Review ◽  
Behavioral Change ◽  
Digital Technologies ◽  
Health Behavior Change ◽  
The United States ◽  
Behavior Change Techniques ◽  
Research Areas

BACKGROUND Research on digital technology to change health behavior has increased enormously in recent decades. Due to the interdisciplinary nature of this topic, knowledge and technologies from different research areas are required. Up to now, it is not clear how the knowledge from those fields is combined in actual applications. A comprehensive analysis that systematically maps and explores the use of knowledge within this emerging interdisciplinary field is required. OBJECTIVE This study aims to provide an overview of the research area around the design and development of digital technologies for health behavior change and to explore trends and patterns. METHODS A bibliometric analysis is used to provide an overview of the field, and a scoping review is presented to identify the trends and possible gaps. The study is based on the publications related to persuasive technologies and health behavior change in the last 18 years, as indexed by the Web of Science and Scopus (317 and 314 articles, respectively). In the first part, regional and time-based publishing trends; research fields and keyword co-occurrence networks; influential journals; and collaboration network between influential authors, countries, and institutions are examined. In the second part, the behavioral domains, technological means and theoretical foundations are investigated via a scoping review. RESULTS The literature reviewed shows a clear and emerging trend after 2001 in technology-based behavior change, which grew exponentially after the introduction of the smartphone around 2009. Authors from the United States, Europe, and Australia have the highest number of publications in the field. The three most active research areas are computer science, public and occupational health, and psychology. The keyword “mhealth” was the dominant term and predominantly used together with the term “physical activity” and “ehealth”. A total of three strong clusters of coauthors have been found. Nearly half of the total reported papers were published in three journals. The United States, the United Kingdom, and the Netherlands have the highest degree of author collaboration and a strong institutional network. Mobile phones were most often used as a technology platform, regardless of the targeted behavioral domain. Physical activity and healthy eating were the most frequently targeted behavioral domains. Most articles did not report about the behavior change techniques that were applied. Among the reported behavior change techniques, goal setting and self-management were the most frequently reported. CONCLUSIONS Closer cooperation and interaction between behavioral sciences and technological areas is needed, so that theoretical knowledge and new technological advancements are better connected in actual applications. Eventually, this could result in a larger societal impact, an increase of the effectiveness of digital technologies for health behavioral change, and more insight in the relationship between behavioral change strategies and persuasive technologies' effectiveness.

scholarly journals Self-guided Change: The most common form of long-term, maintained health behavior change

2018 ◽  
Vol 5 (1) ◽  
pp. 205510291775157 ◽  
Author(s):  
F Michler Bishop
Keyword(s):  
Weight Loss ◽  
Health Behavior ◽  
Behavior Change ◽  
Scoping Review ◽  
Health Behavior Change ◽  
Significant Cost ◽  
Health Related Behaviors ◽  
Health Related ◽  
The One

Millions of people change risky, health-related behaviors and maintain those changes. However, they often take years to change, and their unhealthy behaviors may harm themselves and others and constitute a significant cost to society. A review—similar in nature to a scoping review—was done of the literature related to long-term health behavior change in six areas: alcohol, cocaine and heroin misuse, gambling, smoking, and overeating. Based on the limited research available, reasons for change and strategies for changing and for maintaining change were also reviewed. Fifty years of research clearly indicate that as people age, in the case of alcohol, heroin and cocaine misuse, smoking, and gambling, 80–90 percent moderate or stop their unhealthy behaviors. The one exception is overeating; only 20 percent maintain their weight loss. Most of these changes, when they occur, appear to be the result of self-guided change. More ways to accelerate self-guided, health-related behavior change need to be developed and disseminated.

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