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Fulltext A Web-Based Intervention for Social Media Addiction Disorder Management in Higher Education: Quantitative Survey Study

Dogan H, Norman H, Alrobai A, Jiang N, Nordin N, Adnan A

J Med Internet Res, 2019 10 02;21(10):e14834.
PMID: 31579018 DOI: 10.2196/14834

BACKGROUND: Social media addiction disorder has recently become a major concern and has been reported to have negative impacts on postgraduate studies, particularly addiction to Facebook. Although previous studies have investigated the effects of Facebook addiction disorder in learning settings, there still has been a lack of studies investigating the relationship between online intervention features for Facebook addiction focusing on postgraduate studies.
OBJECTIVE: In an attempt to understand this relationship, this study aimed to carry out an investigation on online intervention features for effective management of Facebook addiction in higher education.
METHODS: This study was conducted quantitatively using surveys and partial least square-structural equational modeling. The study involved 200 postgraduates in a Facebook support group for postgraduates. The Bergen Facebook Addiction test was used to assess postgraduates' Facebook addiction level, whereas online intervention features were used to assess postgraduates' perceptions of online intervention features for Facebook addiction, which are as follows: (1) self-monitoring features, (2) manual control features, (3) notification features, (4) automatic control features, and (5) reward features.
RESULTS: The study discovered six Facebook addiction factors (relapse, conflict, salience, tolerance, withdrawal, and mood modification) and five intervention features (notification, auto-control, reward, manual control, and self-monitoring) that could be used in the management of Facebook addiction in postgraduate education. The study also revealed that relapse is the most important factor and mood modification is the least important factor. Furthermore, findings indicated that notification was the most important intervention feature, whereas self-monitoring was the least important feature.
CONCLUSIONS: The study's findings (addiction factors and intervention features) could assist future developers and educators in the development of online intervention tools for Facebook addiction management in postgraduate education.

Matched MeSH terms: Social Media/statistics & numerical data*
Fulltext Translating Evidence Into Practice via Social Media: A Mixed-Methods Study

Maloney S, Tunnecliff J, Morgan P, Gaida JE, Clearihan L, Sadasivan S, et al.

J Med Internet Res, 2015 Oct 26;17(10):e242.
PMID: 26503129 DOI: 10.2196/jmir.4763

BACKGROUND: Approximately 80% of research evidence relevant to clinical practice never reaches the clinicians delivering patient care. A key barrier for the translation of evidence into practice is the limited time and skills clinicians have to find and appraise emerging evidence. Social media may provide a bridge between health researchers and health service providers.
OBJECTIVE: The aim of this study was to determine the efficacy of social media as an educational medium to effectively translate emerging research evidence into clinical practice.
METHODS: The study used a mixed-methods approach. Evidence-based practice points were delivered via social media platforms. The primary outcomes of attitude, knowledge, and behavior change were assessed using a preintervention/postintervention evaluation, with qualitative data gathered to contextualize the findings.
RESULTS: Data were obtained from 317 clinicians from multiple health disciplines, predominantly from the United Kingdom, Australia, the United States, India, and Malaysia. The participants reported an overall improvement in attitudes toward social media for professional development (Psocial media had changed the way they practice, or intended to practice. Similarly, a large proportion of respondents (135/193, 69.9%) indicated that the education they had received via social media had increased their use of research evidence within their clinical practice.
CONCLUSIONS: Social media may be an effective educational medium for improving knowledge of health professionals, fostering their use of research evidence, and changing their clinical behaviors by translating new research evidence into clinical practice.

Matched MeSH terms: Social Media/statistics & numerical data*
Fulltext Health Information Engagement Factors in Malaysia: A Content Analysis of Facebook Use by the Ministry of Health in 2016 and 2017

A Rahim AI, Ibrahim MI, A Salim FN, Ariffin MAI

Int J Environ Res Public Health, 2019 02 18;16(4).
PMID: 30781691 DOI: 10.3390/ijerph16040591

Health organizations have widely adopted social media for health promotion, public health communication conveyance, and organizational promotion activities. However, little published data exists on the factors that facilitate health information diffusion in South East Asia, especially Malaysia compared with Western countries. This study aimed to investigate factors associated with good engagement rates among internet users on the Facebook (FB) page of Ministry of Health Malaysia. In this observational study, 2123 FB posts were randomly selected. Data dated from 1 November 2016 to 31 October 2017 was gathered from the Facebook Insight. The logistic regression model was applied to identify factors associated with good engagement rates. This study found that a FB post with a good engagement rate was significantly associated with a health education post (Adjusted Odd Ratio (AOR): 3.80, 95% Confidence Interval CI: 3.02⁻4.78, p < 0.001), a risk communication post (AOR: 1.77, 95% CI: 1.39⁻2.26, p < 0.001), a post in the afternoon (AOR: 1.76, 95% CI: 1.34⁻2.31, p < 0.001) or in the evening (AOR: 1.48, 95% CI: 1.20⁻1.82, p < 0.001), and a video format (AOR: 3.74, 95% CI: 1.44⁻9.71, p = 0.007). Therefore, we present the first comprehensive analysis of health information engagement among internet users in Malaysia. The growing trends of online health information-seeking behaviors and demand for the availability of validated health information require effective strategies by public health organizations to disseminate health information and achieve better audience engagement on social media.

Matched MeSH terms: Social Media/statistics & numerical data*

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