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.

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 Analysing antecedence of an intelligent voice assistant use intention and behaviour

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 496
Author(s):  
Rusen N Tanribilir
Keyword(s):  
Technology Acceptance ◽  
Ordinary Least Squares ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Perceived Ease Of Use ◽  
Cross Sectional ◽  
Privacy Concerns ◽  
Perceived Needs ◽  
Technology Acceptance Models

Background: As the use of intelligent voice assistant applications becomes more prevalent, a growing body of studies are examining individuals' interactions with intelligent voice assistants. However, very limited research has focused on comparing the antecedents of both use and non-use behaviour of individuals, based on the technology acceptance models. To fill this gap, the present study investigated antecedents of intelligent voice assistance use and use intention in a cross-sectional setting. Additionally, to go one step beyond the existing literature on technology acceptance models and theories, a new construct termed perceived needs, as well as the moderating role of perceived privacy concerns and perceived awareness, are introduced. Method: A quantitative, cross-sectional research design was utilised using a nonprobability sampling strategy through the online networking platforms. Total of 277 (n = 155 users vs n = 122 non-users) international adults age between 20-74 years (79.6% female, 20.4 %  male) contributed to the study. Ordinary least squares (OLS) linear regression and Bivariate logistic regression analyses for non-users and users were conducted, respectively. Results: Both analyses revealed that peer influence and perceived needs related to the intention to use intelligent voice assistants for non-users, which applied to the current intelligent voice assistance users where privacy concerns were considered. Surprisingly, the key determinants of technology acceptance and use theories, such as perceived ease of use and perceived usefulness, did not hold for intelligent voice assistance usage. Conclusion: The current research contributed to the field by validating new constructs of perceived needs and the moderation role of perceived privacy concerns. However, in order to build on an existing body of knowledge, future studies should further examine the moderation role of perceived privacy concerns, perceived ease of use, and perceived usefulness in the same domain.

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.

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
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