Title: Content Elements for Web-Based Health Promotion
Authors: Marwan Noman, Ah Choo Koo, Sim Hui Tee,
ABSTRACT:
This paper provides an analysis of the basic elements required for health promotion based on digital content. It covers the feedback from the respondents involved in a pilot study type; content interventions were examined among the respondents to analyze the most required content elements for health promotion programs for workplace community. These elements should be focused on to highlight the importance of content quality and interactivity features for health promoters using technology solutions to provide digital content. The findings of this research has attracted the interest of policy makers associates in Malaysia to engage with the research team to enhance the quality of content provided to the Malaysian society.
Title: A Study on Selected Demographic Characteristics and Mental Health of Young Adults in Public Higher Learning Institutions in Malaysia.
Authors: Noradilah Md Nordin, Mansor Abu Talib (Corresponding author), Siti Nor Yaacob, Mohamad Shatar Sabran
ABSTRACT:
Early adulthood is the transitional period between adolescence and adult life. As with other general young adult population, university students carry along several of life’s issues such as a personal and social adjustment, academic and career concerns, stress and other related psychosomatic issues which may lead to an unhealthy mental condition. These “life baggage” and stress must be managed well in order to prevent them from interfering with normal adult development and growth processes. The purpose of this study is to determine the association between several selected demographic characteristics and the mental health status of young adults studying in public Malaysian universities. A total of 1467 respondents were recruited using a multistage cluster sampling. General Health Questionnaire (GHQ-12 (Goldberg, 1978) was the research tool utilised to assess the undergraduates’ mental health status. Findings indicate that a majority of undergraduates exhibit a healthy mental state while a minority has some mental health concerns. One-way ANOVA tests showed that the mental health of undergraduates in this study differed in terms of ethnicity, year of study and academic field. In conclusion, these findings can assist student development personnel and academicians in enhancing their understanding of the current mental health status of undergraduate students and the demographic factors that relate to it.
Title: Acceptance and barriers to access of occupational e-mental health: cross-sectional findings from a health-risk population of employees
Authors: Severin Hennemann1 · Michael Witthöft · Matthias Bethge · Katja Spanier · Manfred E. Beutel ·Rüdiger Zwerenz
ABSTRACT:
Purpose Occupational e-mental-health (OEMH) may extend existing instruments for preservation or restoration of health and work ability. As a key precondition to efficient implementation, this study examined acceptance and person-centered barriers to potential uptake of OEMH for work-related distress in employees with an elevated risk of early retirement.
Methods Within the framework of the “Third German Sociomedical Panel of Employees”, 1829 employees with prior sickness absence payments filled out a self-administered questionnaire. Participants had a mean age of 49.93 years (SD = 4.06). 6.2% indicated prior use of eHealth interventions. Potential predictors of acceptance of OEMH were examined based on the “Unified Theory of Acceptance and Use of Technology” (UTAUT) extended by work ability, mental health, eHealth literacy and demographic characteristics.
Results 89.1% (n = 1579) showed low to moderate acceptance (M =2.20, SD = 1.05, range 1–5). A path analysis revealed significant, positive direct effects of UTAUT predictors on acceptance (performance expectancy: 0.48, SE = 0.02, p < 0.001; effort expectancy: 0.20, SE = 0.02, p < 0.001; social influence: 0.28, SE = 0.02, p < 0.001).Online time and frequency of online health information search were further positive direct predictors of acceptance. Model fit was good [χ2(7) = 12.91, p = 0.07, RMSEA = 0.02, CFI = 1.00, TLI = 0.99, SRMR = 0.01].
Conclusions Attitudes towards OEMH are rather disadvantageous in the studied risk group. Implementation of OEMH, therefore, requires a priori education including promotion of awareness, favorable attitudes regarding efficacy and usability in a collaborative approach.
Title: Determinant Factors of Public Acceptance of Stress Management Apps: Survey Study
Authors: Jennifer Apolinário-Hagen, PhD; Severin Hennemann, PhD; Lara Fritsche, PhD; Marie Drüge, PhD; Bernhard Breil, PhD
ABSTRACT:
Background: Chronic stress is a major public health concern. Mobile health (mHealth) apps can help promote coping skills in daily life and prevent stress-related issues. However, little is known about the determinant factors of public acceptance of stress management in relation to preferences for psychological services.
Objective: The aim of this survey study was to (1) assess determinant factors of public acceptance (behavioral use intention) of stress management apps based on an adapted and extended version of the Unified Theory of Acceptance and Use of Technology (UTAUT) model and (2) explore preferences for mHealth apps compared with other mental health services.
Methods: Using convenience sampling, participants completed a multiscale 54-item Web-based survey. Based on significant correlations with acceptance, hierarchical stepwise regression= analysis was performed within three blocks: (1) background and stress-related control variables, (2) beliefs and attitudes toward using mHealth, and (3) the core UTAUT determinants. The preference for mHealth apps in comparison with nine other mental health services (operationalized as readiness to use) was analyzed using paired t tests.
Results: Of 141 participants, nearly half (69/141, 48.9%) indicated prior mHealth use. Acceptance of stress coping apps was moderate (mean 3.10, SD 1.03, range 1-5). Hierarchical stepwise regression including four of 11 variables (R2=.62; P=.01, f2=1.63) identified positive attitudes toward using mHealth for stress coping (beta=0.69, P<.001, 46% R2 increase above block 1, f2=0.85), skepticism/perceived risks (beta=−0.14, P=.01, f2=0.16), and stress symptoms (beta=0.12, P=.03, f2=0.14) as significant predictors of acceptance. UTAUT determinants added no predictive contribution beyond attitudes (all P>.05, R2 increase of 1%), whereas post hoc analysis showed significant R2 increases of attitudes and skepticism/perceived risks beyond UTAUT determinants (all P<.001, R2 increase of 13%). The readiness to use apps was equivalent to or significantly higher than most service types, but lower than information websites.
Conclusions: Attitudes may be at least as predictive for the acceptance of stress management apps as for more elaborated outcome beliefs. Efforts aimed at improving the public adoption of mHealth could put more emphasis on the pleasant aspects of app use, address misconceptions, offer stress screening tools on health websites, and increase options to try high-quality apps.
Title: A confirmatory factor analysis of the behavioral intention to use smart wellness wearables in Malaysia
Authors: Naghmeh Niknejad · Ab Razak Che Hussin1· Imran Ghani · Fatemeh Ashraf Ganjouei
ABSTRACT:
Wearable technology refers to the next generation of the digital revolution that connects items with embedded sensors to the Internet so as to enhance the quality of human life. Wearables have shifted the focus of the healthcare sector toward prevention programs that empower individuals to be active and liable for their own health. Although the number of smart wearable users has grown significantly, there is still a lack of academic researches on what motivates and prevents the continued usage of these devices. Hence, the main objectives of this study are, namely: to explain the impediments and affecting factors in deciding to use smart wellness wearables from a user’s perspective; and to propose a unified model to explore the impact of these factors on an individual’s behavioral intentions. Accordingly, the “Unified Theory of Acceptance and Use of Technology 2” and the “Value-based Adoption Model” were integrated with two additional factors, namely perceived trust and perceived health increase. Following this, a survey was conducted among students and 100 reliable responses were received. As a result of this study, the Confirmatory Factor Analysis from the developed instrument is presented. The findings have confirmed the validity and reliability of the developed instrument. This paper also presents a theoretical understanding of the involved factors in the proposed model.
Title: What is eHealth (6)? Development of a Conceptual Model for eHealth: Qualitative Study with Key Informants
Author: Tim Shaw, BSc, PhD
ABSTRACT:
Background: Despite rapid growth in eHealth research, there remains a lack of consistency in defining and using terms related to eHealth. More widely cited definitions provide broad understanding of eHealth but lack sufficient conceptual clarity to operationalize eHealth and enable its implementation in health care practice, research, education, and policy. Definitions that are more detailed are often context or discipline specific, limiting ease of translation of these definitions across the breadth of eHealth perspectives and situations. A conceptual model of eHealth that adequately captures its complexity and potential overlaps is required. This model must also be sufficiently detailed to enable eHealth operationalization and hypothesis testing.
Objective: This study aimed to develop a conceptual practice-based model of eHealth to support health professionals in applying eHealth to their particular professional or discipline contexts.
Methods: We conducted semistructured interviews with key informants (N=25) from organizations involved in health care delivery, research, education, practice, governance, and policy to explore their erspectives on and experiences with eHealth. We used purposeful sampling for maximum diversity. Interviews were coded and thematically analyzed for emergent domains.
Results: Thematic analyses revealed 3 prominent but overlapping domains of eHealth: (1) health in our hands (using eHealth technologies to monitor, track, and inform health), (2) interacting for health (using digital technologies to enable health communication among practitioners and between health professionals and clients or patients), and (3) data enabling health (collecting, managing, and using health data). These domains formed a model of eHealth that addresses the need for clear definitions and a taxonomy of eHealth while acknowledging the fluidity of this area and the strengths of initiatives that span multiple eHealth domains.
Conclusions: This model extends current understanding of eHealth by providing clearly defined domains of eHealth while highlighting the benefits of using digital technologies in ways that cross several domains. It provides the depth of perspectives and examples of eHealth use that are lacking in previous research. On the basis of this model, we suggest that eHealth initiatives that are most impactful would include elements from all 3 domains.