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      A Web-Based and Mobile Intervention Program Using a Spaced Education Approach for Workplace Mental Health Literacy: Cluster Randomized Controlled Trial

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          Abstract

          Background

          Workplace mental health is an important global health concern.

          Objectives

          This unblinded, phase-III, wait-listed cluster randomized controlled trial aimed to examine the effectiveness of a mobile health (mHealth) psychoeducation program using a spaced education approach on mental health literacy (MHL) in the workplace. The main interest of this paper was the immediate and 3-month medium-term effect of the program on the MHL of workers. The purposely built mHealth platform was also evaluated as a health-related app.

          Methods

          The mHealth platform was designed using the principle of spaced education as a psychoeducation intervention program, with various modules of web-based and mobile materials presented to the participant in a progressive manner. Short quizzes at the end of each module ensured adequate learning, and successful completion qualified the learner to progress to the next level. The trial recruited 456 employees of specific industries with high levels of work-related stress. Participants who were nested in different offices or units were allocated into the intervention and wait-listed control groups using a block randomization process, with the office or unit as the cluster. A separate sample of 70 individual raters were used for the evaluation of the mHealth platform. The Australian National MHL and Stigma Survey and the Mobile Apps Rating Scale were completed through a web-based self-reported survey to assess MHL and evaluate the app. The trial and follow-up data were analyzed by a generalized linear latent and mixed model with adjustments for the clustering effect of work sites and repeated measures.

          Results

          Of the 456 participants in the trial, 236 (51.8%) responded to the follow-up survey. Most MHL outcomes obtained significant results immediately after the intervention and across time. After adjusting for the clustering effect, the postintervention weighted mean scores were significantly higher in the intervention group than the control group for correct recognition of a mental health problem, help seeking, and stigmatization by 0.2 (SE 0.1; P=.003), 0.9 (SE 0.2; P<.001), and 1.8 (SE 0.4; P<.001), respectively. After adjusting for the clustering effect, significant differences across time were found in help-seeking intention ( P=.01), stigmatization ( P<.001), and social distancing ( P<.001). The evaluation of the mHealth program resulted in average scores of the 4 major domains ranging from 3.8 to 4.2, with engagement having the lowest score.

          Conclusions

          The mHealth psychoeducation intervention program using this platform had immediate and 3-month medium-term effects of retaining and improving MHL. The platform was evaluated to have satisfactory performance in terms of functionality, aesthetics, information content, and utility in enhancing MHL. It is anticipated that ongoing development in digital health will provide great benefits in improving the mental health of the global population.

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          Most cited references31

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          Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010

          The Lancet, 382(9904), 1575-1586
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            Mobile App Rating Scale: A New Tool for Assessing the Quality of Health Mobile Apps

            Background The use of mobile apps for health and well being promotion has grown exponentially in recent years. Yet, there is currently no app-quality assessment tool beyond “star”-ratings. Objective The objective of this study was to develop a reliable, multidimensional measure for trialling, classifying, and rating the quality of mobile health apps. Methods A literature search was conducted to identify articles containing explicit Web or app quality rating criteria published between January 2000 and January 2013. Existing criteria for the assessment of app quality were categorized by an expert panel to develop the new Mobile App Rating Scale (MARS) subscales, items, descriptors, and anchors. There were sixty well being apps that were randomly selected using an iTunes search for MARS rating. There were ten that were used to pilot the rating procedure, and the remaining 50 provided data on interrater reliability. Results There were 372 explicit criteria for assessing Web or app quality that were extracted from 25 published papers, conference proceedings, and Internet resources. There were five broad categories of criteria that were identified including four objective quality scales: engagement, functionality, aesthetics, and information quality; and one subjective quality scale; which were refined into the 23-item MARS. The MARS demonstrated excellent internal consistency (alpha = .90) and interrater reliability intraclass correlation coefficient (ICC = .79). Conclusions The MARS is a simple, objective, and reliable tool for classifying and assessing the quality of mobile health apps. It can also be used to provide a checklist for the design and development of new high quality health apps.
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              Digital technologies in the public-health response to COVID-19

              Digital technologies are being harnessed to support the public-health response to COVID-19 worldwide, including population surveillance, case identification, contact tracing and evaluation of interventions on the basis of mobility data and communication with the public. These rapid responses leverage billions of mobile phones, large online datasets, connected devices, relatively low-cost computing resources and advances in machine learning and natural language processing. This Review aims to capture the breadth of digital innovations for the public-health response to COVID-19 worldwide and their limitations, and barriers to their implementation, including legal, ethical and privacy barriers, as well as organizational and workforce barriers. The future of public health is likely to become increasingly digital, and we review the need for the alignment of international strategies for the regulation, evaluation and use of digital technologies to strengthen pandemic management, and future preparedness for COVID-19 and other infectious diseases.
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                Author and article information

                Contributors
                Journal
                JMIR Ment Health
                JMIR Ment Health
                JMH
                mental
                16
                JMIR Mental Health
                JMIR Mental Health
                2368-7959
                2024
                23 April 2024
                : 11
                : 51791
                Affiliations
                [1 ]departmentFaculty of Medicine , Macau University of Science and Technology , Macau, China
                [2 ]departmentFaculty of Medicine and Health , The University of Sydney , Sydney, Australia
                [3 ]departmentSTEM College , RMIT University , Melbourne, Australia
                Author notes
                Lawrence TLamBSc, MAppPsy, MPH, PhD, Faculty of Medicine, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China, 853 6394-1719; tmlam@ 123456must.edu.mo

                None declared.

                [*]

                all authors contributed equally

                Author information
                http://orcid.org/0000-0001-6183-6854
                http://orcid.org/0000-0001-9451-8203
                Article
                51791
                10.2196/51791
                11063580
                38654570
                4146fdfa-7733-4f17-8468-ee0e4ba4b757
                Copyright © Lawrence T Lam, Mary K P Lam. Originally published in JMIR Mental Health (https://mental.jmir.org)

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Mental Health, is properly cited. The complete bibliographic information, a link to the original publication on https://mental.jmir.org/, as well as this copyright and license information must be included.

                History
                : 11 August 2023
                : 23 February 2024
                : 15 March 2024
                Categories
                Original Paper
                Innovations in Mental Health Systems
                Registered Report
                Web-based and Mobile Health Interventions
                e-Mental Health and Cyberpsychology
                Mobile Health (mhealth)
                mHealth for Wellness, Behavior Change and Prevention
                e-Learning and Medical Education
                Occupational Health and Ergonomics/Prevention at the Workplace
                Custom metadata
                368828
                Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12619000464167; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377176
                RR2-10.1186/s13063-019-3748-y
                Kelvin Cheung
                ESL
                Low
                Yes
                Monisha
                Success
                2024-04-23 11:29:23

                mhealth,web-based intervention,mental health literacy,psychoeducation,randomized controlled trial,workplace,performance,worker,intervention,digital health,mental wellness,promote,well-being,mobile health,technology

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