scholarly journals #StrongerTogether – Utilizing Health Behavior Change and Technology Acceptance Models to Predict Adoption of COVID-19 Contact Tracing Apps: A Cross-Sectional Survey (Preprint)

10.2196/25447 ◽  
2020 ◽  
Author(s):  
Samuel Tomczyk ◽  
Simon Barth ◽  
Silke Schmidt ◽  
Holger Muehlan
Keyword(s):  
Health Behavior ◽  
Behavior Change ◽  
Technology Acceptance ◽  
Health Behavior Change ◽  
Contact Tracing ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Technology Acceptance Models

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

scholarly journals Factors Associated with Initiation and Sustenance of Stress Management Behaviors in Veterinary Students: Testing of Multi-Theory Model (MTM)

2020 ◽  
Vol 17 (2) ◽  
pp. 631 ◽  
Author(s):  
Vinayak K. Nahar ◽  
Julia K. Wells ◽  
Robert E. Davis ◽  
Elizabeth C. Johnson ◽  
Jason W. Johnson ◽  
...  
Keyword(s):  
United States ◽  
Health Behavior ◽  
Behavior Change ◽  
Stress Management ◽  
Health Behavior Change ◽  
The United States ◽  
Theory Model ◽  
Veterinary Students ◽  
Cross Sectional ◽  
Management Behaviors

Veterinary students across the United States face the challenge of stress during school every day. When managed improperly, stress can become chronic and manifest in physical and emotional consequences. The purpose of this study was to examine the utility of the multi-theory model (MTM) of health behavior change in predicting the initiation and sustenance of stress management behaviors among veterinary students. A cross-sectional design was used to study the efficacy of the MTM in predicting initiation and sustenance of stress management behaviors among veterinary students at a private College of Veterinary Medicine in the Southeast United States. Researchers collected data using a 54-item valid and reliable survey. Only students who did not already engage in daily stress management behaviors were included in the study. After recruitment and exclusion, a total of 140 students remained and participated in the study. Hierarchical multiple regression revealed that, for initiation of stress management behaviors, 49.5% of the variance was explained by depression, academic classification, and behavioral confidence. Regarding sustenance of stress management behaviors, 50.4% of the variance was explained by perceived stress, depression, academic classification, and emotional transformation. MTM serves as a promising framework for predicting initiation and sustenance of health behavior change. Based on the results of this study, interventions aimed to promote stress management behaviors in veterinary students should focus on the MTM constructs of behavioral confidence and emotional transformation.

scholarly journals Conceptualization of college students’ COVID-19 related mask-wearing behaviors using the Multi-Theory Model of health behavior change

2021 ◽  
Vol 11 (2) ◽  
pp. 194-201
Author(s):  
Robert E. Davis ◽  
Manoj Sharma ◽  
Kayla E. Simon ◽  
Amanda H. Wilkerson
Keyword(s):  
Behavior Change ◽  
Face Mask ◽  
Health Behavior Change ◽  
Theory Model ◽  
Multivariate Techniques ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Southeastern Us ◽  
Significant Relationships ◽  
The Social

Background: Recommendations and policies, regarding the use of face coverings, have been instituted to control transmission of coronavirus disease 2019 (COVID-19). Understanding of psychosocial factors related to the use of face coverings within the context of COVID-19 is needed. This study aimed to conceptualize mask-wearing behavior among students using the Multi-theory Model (MTM) of behavior change. Methods: In October 2020, students (n = 595) enrolled in a large public southeastern US university were recruited to participate in a cross-sectional survey, using a valid and reliable instrument. Univariate, bivariate, and multivariate techniques described mask-wearing behavior and differentiated theoretical drivers of mask-wearing between individuals compliant and non-compliant with guidelines. Results: Compliant individuals reported significantly higher scores (P<0.05) for initiation and sustenance of mask-wearing, participatory dialogue, behavioral confidence, emotional transformation, practice for change, changes in the social environment, and significantly lower scores for disadvantage. Among multivariable models, all theoretical predictors exhibited significant relationships to their respective outcomes (initiation and sustenance). Specifically, MTM constructs explained approximately 35% of variance in initiation (R2 = 0.346, F(3,526) = 94.32, P<0.001) and 33% of variance in sustenance of mask wearing (R2 = 0.328, F(3,529) = 87.71, P<0.001) for compliant individuals. Behavioral confidence and emotional transformation exhibited the strongest relationships to initiation (ß = 0.403, P<0.001) and sustenance (ß = 0.450, P<0.001), respectively. Conclusion: Findings suggest a need to design educational programming based on the MTM to promote mask-wearing behavior among laggards who defy face mask guidelines, recommendations, and mandates.

Facilitating the Adoption of Digital Health Technologies by Older Adults to Support Their Health

2021 ◽  
pp. 164-179
Author(s):  
Maurita T. Harris ◽  
Wendy A. Rogers
Keyword(s):  
Older Adults ◽  
Health Behavior ◽  
Behavior Change ◽  
Technology Acceptance ◽  
Digital Health ◽  
Theoretical Models ◽  
Health Behavior Change ◽  
The United States ◽  
Positive Health ◽  
Health Technologies

With over 50% of older adults in the United States managing at least one chronic condition, it is crucial to understand how to promote their self-management of positive health behaviors. Health interventions through digital health technologies are becoming more commonplace. Theoretical models related to health behavior change and technology acceptance can guide the design of these healthcare tools and lead to adoption by older adults to support their health. This chapter provides an overview of health behavior change and technology acceptance models to inform the development of digital health technology for older adults. This chapter illustrates the application of these models by describing two design personas that represent human factors designers. This chapter discusses the lack of inclusion of technology adoption and other long-term concepts and the need for further exploration that could inform understanding of technology integration into everyday health activities.

scholarly journals Explaining Handwashing Behavior in a Sample of College Students during COVID-19 Pandemic Using the Multi-Theory Model (MTM) of Health Behavior Change: A Single Institutional Cross-Sectional Survey

Healthcare ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 55
Author(s):  
Manoj Sharma ◽  
Kavita Batra ◽  
Robert E. Davis ◽  
Amanda H. Wilkerson
Keyword(s):  
College Students ◽  
Health Behavior ◽  
Behavior Change ◽  
Pearson Correlation ◽  
Significant Proportion ◽  
Health Behavior Change ◽  
Theory Model ◽  
Fourth Generation ◽  
Cross Sectional ◽  
Behavior Change Interventions

Amidst the COVID-19 pandemic, handwashing offers a simple and effective hygienic measure for disease prevention. Reportedly, a significant proportion of college students did not follow handwashing recommendations provided by the Centers for Disease Control and Prevention (CDC) in the pre-COVID era. The purpose of this cross-sectional study was to explore and explain the handwashing behavior among college students during the COVID-19 pandemic using a contemporary fourth-generation multi-theory model (MTM) of health behavior change. Data were collected from 713 college students at a large public university in the Southern U.S. in October 2020 using a validated 36-item survey. Statistical analyses included independent samples t-tests, Pearson correlation, and hierarchical regression modeling. Among students not following handwashing recommendations, the constructs of participatory dialogue (β = 0.152; p < 0.05) and behavioral confidence (β = 0.474; p < 0.0001) were statistically significant and accounted for 27.2% of the variance in the likelihood of initiation of the behavior. Additionally, the constructs of emotional transformation (β = 0.330; p < 0.0001), practice for change (β = 0.296; p < 0.0001), and changes in the social environment (β = 0.180; p < 0.05) were statistically significant and accounted for 45.1% of the variance in the likelihood of sustaining handwashing behavior. This study highlights the applicability and usability of the MTM in designing and testing behavior change interventions and media messaging in campaigns targeting college students.

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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