How Fitness Trackers Facilitate Health Behavior Change

2016 ◽  
Vol 60 (1) ◽  
pp. 1068-1072 ◽  
Author(s):  
Qinge Wu ◽  
Kelli Sum ◽  
Dan Nathan-Roberts
Keyword(s):  
Health Behavior ◽  
Behavior Change ◽  
Health Indicators ◽  
Health Behavior Change ◽  
Physical Activities ◽  
User Engagement ◽  
Feedback Information ◽  
Information Display ◽  
Fitness Trackers

Fitness trackers have broadened the healthcare ecosystem and made self-tracking everyday physical activities possible. Features like heart rate monitoring can help detect health ailments, yet there is little evidence that suggests tracking health indicators and physical activities leads to long-term health behavior change. This proceeding analyzes areas of Human Factors that could be used to increase long-term user engagement. Feedback, information display, and specific design principles and case studies are discussed.

The Disconnected Values Model: Intervention Strategies for Exercise Behavior Change

2008 ◽  
Vol 2 (4) ◽  
pp. 357-380 ◽  
Author(s):  
Mark H. Anshel
Keyword(s):  
Health Behavior ◽  
Behavior Change ◽  
Exercise Program ◽  
Health Behavior Change ◽  
Exercise Behavior ◽  
Future Research ◽  
Behavioral Strategies ◽  
Values And Beliefs ◽  
Long Term Consequences

This article proposes a new approach to health behavior change, the disconnected values (intervention) model (DVM). The DVM consists of predetermined cognitive-behavioral strategies for initiating and maintaining changes in health behavior, such as the implementation of an exercise program. The model consists of helping clients (a) examine the benefits, in contrast to the costs and long-term consequences, of the habit they most want to change; (b) identify their deepest values and beliefs (e.g., health, family, faith, integrity); (c) detect a “disconnect” between the negative habit and the identified values; and (d) conclude whether the disconnect is acceptable, given its costs and long-term consequences. The client’s conclusion that the disconnect is unacceptable creates incentive and commitment for health behavior change. The theoretical foundations of the DVM are explained, and its specific application for exercise behavior change is described. Three outcome studies also are reported, as well as a brief case study. Implications for practitioners and suggestions for future research are provided.

scholarly journals Long-Term Adherence to Health Behavior Change

2013 ◽  
Vol 7 (6) ◽  
pp. 395-404 ◽  
Author(s):  
Kathryn R. Middleton ◽  
Stephen D. Anton ◽  
Michal G. Perri
Keyword(s):  
Health Behavior ◽  
Behavior Change ◽  
Health Behavior Change

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.

Predictors of Health Behavior Change in School-Based Obesity Prevention

2008 ◽  
Author(s):  
Kara Harrington ◽  
Maureen E. Kenny ◽  
Deirdre Brogan ◽  
Lynn Y. Walsh
Keyword(s):  
Health Behavior ◽  
Behavior Change ◽  
Obesity Prevention ◽  
Health Behavior Change ◽  
School Based

A review of mHealth depression apps: Assessing app functions for the Self-Determination Theory (Preprint)

2020 ◽  
Author(s):  
Luke Brownlow
Keyword(s):  
Health Behavior ◽  
Behavior Change ◽  
Basic Needs ◽  
Health Behavior Change ◽  
Self Determination Theory ◽  
Healthcare Research ◽  
The Self ◽  
Self Determination ◽  
Ideal Tool ◽  
Google Play

BACKGROUND Smartphone applications (apps) are an ideal tool that is highly accessible to people who wish to begin self-treatment for depression. While many studies have performed content analyses on healthcare apps, few studies have reviewed these apps for adherence to behavior theory. Furthermore, apps for depression management are underrepresented in healthcare research. OBJECTIVE The objective of this study is to assess mHealth depression apps using SDT as a theoretical framework for meeting needs of autonomy, competence and, relatedness METHODS All depression healthcare apps available in Australia from the iTunes and Google Play app stores that met the inclusion criteria were analyzed. Each app was reviewed based on price options, store availability, download rates, and how in-app functions met the three basic needs for motivation towards health behavior change outlined in the Self-Determination Theory (SDT). RESULTS The analysis of the apps showed that most apps were free to download (69.9%) and addressed at least one of the three needs (81.4%) of SDT. However, few apps addressed all three of the basic needs through their functions (7.7%), and no apps hosted all functions expected to stimulate motivation for health behavior change. Furthermore, neither store availability, price option nor download rate were accurate predictors that apps hosted in-app functions expected to meet the basic needs. CONCLUSIONS The results suggest that some depression healthcare apps that meet the basic needs would effectively stimulate motivation (i.e., autonomy, competence, and relatedness). However, each individual app is limited in its number of functions that meet the basic needs. People who want access to more functions would need to download a suite of apps.

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