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dc.contributor.authorStratton, E
dc.contributor.authorLampit, A
dc.contributor.authorChoi, I
dc.contributor.authorCalvo, RA
dc.contributor.authorHarvey, SB
dc.contributor.authorGlozier, N
dc.date.accessioned2020-12-09T23:14:47Z
dc.date.available2020-12-09T23:14:47Z
dc.date.issued2017-12-21
dc.identifierpii: PONE-D-17-30363
dc.identifier.citationStratton, E., Lampit, A., Choi, I., Calvo, R. A., Harvey, S. B. & Glozier, N. (2017). Effectiveness of eHealth interventions for reducing mental health conditions in employees: A systematic review and meta-analysis. PLOS ONE, 12 (12), https://doi.org/10.1371/journal.pone.0189904.
dc.identifier.issn1932-6203
dc.identifier.urihttp://hdl.handle.net/11343/253176
dc.description.abstractBACKGROUND: Many organisations promote eHealth applications as a feasible, low-cost method of addressing mental ill-health and stress amongst their employees. However, there are good reasons why the efficacy identified in clinical or other samples may not generalize to employees, and many Apps are being developed specifically for this group. The aim of this paper is to conduct the first comprehensive systematic review and meta-analysis evaluating the evidence for the effectiveness and examine the relative efficacy of different types of eHealth interventions for employees. METHODS: Systematic searches were conducted for relevant articles published from 1975 until November 17, 2016, of trials of eHealth mental health interventions (App or web-based) focused on the mental health of employees. The quality and bias of all identified studies was assessed. We extracted means and standard deviations from published reports, comparing the difference in effect sizes (Hedge's g) in standardized mental health outcomes. We meta-analysed these using a random effects model, stratified by length of follow up, intervention type, and whether the intervention was universal (unselected) or targeted to selected groups e.g. "stressed". RESULTS: 23 controlled trials of eHealth interventions were identified which overall suggested a small positive effect at both post intervention (g = 0.24, 95% CI 0.13 to 0.35) and follow up (g = 0.23, 95% CI 0.03 to 0.42). There were differential short term effects seen between the intervention types whereby Mindfulness based interventions (g = 0.60, 95% CI 0.34 to 0.85, n = 6) showed larger effects than the Cognitive Behaviour Therapy (CBT) based (g = 0.15, 95% CI 0.02 to 0.29, n = 11) and Stress Management based (g = 0.17, 95%CI -0.01 to 0.34, n = 6) interventions. The Stress Management interventions however differed by whether delivered to universal or targeted groups with a moderately large effect size at both post-intervention (g = 0.64, 95% CI 0.54 to 0.85) and follow-up (g = 0.69, 95% CI 0.06 to 1.33) in targeted groups, but no effect in unselected groups. INTERPRETATION: There is reasonable evidence that eHealth interventions delivered to employees may reduce mental health and stress symptoms post intervention and still have a benefit, although reduced at follow-up. Despite the enthusiasm in the corporate world for such approaches, employers and other organisations should be aware not all such interventions are equal, many lack evidence, and achieving the best outcomes depends upon providing the right type of intervention to the correct population.
dc.languageEnglish
dc.publisherPUBLIC LIBRARY SCIENCE
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.titleEffectiveness of eHealth interventions for reducing mental health conditions in employees: A systematic review and meta-analysis
dc.typeJournal Article
dc.identifier.doi10.1371/journal.pone.0189904
melbourne.affiliation.departmentPsychiatry
melbourne.source.titlePLoS One
melbourne.source.volume12
melbourne.source.issue12
dc.rights.licenseCC BY
melbourne.elementsid1305038
melbourne.contributor.authorLampit, Amit
dc.identifier.eissn1932-6203
melbourne.accessrightsOpen Access


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