Effectiveness of eHealth interventions for reducing mental health conditions in employees: A systematic review and meta-analysis

Abstract

BackgroundMany 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.MethodsSystematic 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”.Results23 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.InterpretationThere 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.

A Systematic Review of the Evidence Supporting Mobile‐ and Internet‐Based Psychological Interventions For Self‐Harm

“…While there is evidence regarding the potential benefits of Internet‐ and mobile‐based interventions for mental health difficulties (Firth et al., ; Josephine et al., ; Richards et al., ; Stratton et al., ), the benefits for interventions focused specifically on STB prevention are less established. The majority of identified studies concerned CBT‐ and DBT‐informed interventions (both Internet and mobile application based), and there is preliminary evidence that these are acceptable and can be potentially helpful in reducing suicidal thinking.…”

“…Internet‐ and mobile‐based interventions have the potential to help individuals at risk of STB, but further trials are needed to confirm their efficacy. When considering Internet‐ and mobile‐based interventions together, a larger number of RCTs have been undertaken concerning problems like depression and anxiety (Firth et al., ; Josephine et al., ; Richards et al., ; Stratton et al., ). The comparative smaller number of RCTs that focus on STB may be the result of the often greater risk and complexity associated with STB.…”

“…Such interventions can be considered part of the broader body of Internet‐based interventions, or eHealth (e.g., interventions delivered via Web sites and browser‐based applications; Christensen, Batterham, & O'Dea, ). There is evidence that Web‐ and mobile‐based interventions may be effective for common mental health difficulties including depression and anxiety (Firth et al., ; Josephine, Josefine, Philipp, David, & Harald, ; Richards, Richardson, Timulak, & McElvaney, ; Stratton et al., ). A previous review of eHealth interventions for suicide prevention noted that they may be beneficial, but were likely to be more effective where specifically focused on suicide rather than related problems like depression (Christensen et al., ).…”

Identifying optimal indicators and purposes of population segmentation through engagement of key stakeholders: a qualitative study

“…As expected, one of the most commonly mentioned indicators was 'disease state'. It was believed that, by grouping people with similar health conditions together, the disease state allowed policy-makers to develop interventions specifically targeting segment groups and promoting positive health outcomes [31,32]. Indeed, in the current segmentation framework in Singapore, health conditions are used to segment a population as a sole indicator.…”

Toward a Design of a Telerehabilitation Program for the Functional Recovery in Post-Hip Arthroplasty Patients

“…It has been found that telemedicine is effective in the management of adult malnutrition [11]; asthma [12]; heart disease [13], diabetes-especially type 2 [14]; arterial hypertension [15] and multiple sclerosis [16]. In addition, positive clinical results have been presented for the patient followup and treatment in different situations such as: (1) burned [17]; (2) in palliative care [18]; (3) with acute cerebrovascular accident [19]; (4) with mental disorders [20]; (5) geriatric [21]; and (6) newborns, children and adolescents [22,23].…”