| Literature DB >> 35544305 |
Johanna Scheutzow1, Chris Attoe1,2, Joshua Harwood2.
Abstract
BACKGROUND: Web-based interventions have proven to be effective not only in clinical populations but also in the occupational setting. Recent studies conducted in the work environment have focused on the effectiveness of these interventions. However, the role of employees' acceptability of web-based interventions and programs has not yet enjoyed a similar level of attention.Entities:
Keywords: acceptability; e-mental health; employees; mobile phone; occupational online interventions; online mental health interventions
Year: 2022 PMID: 35544305 PMCID: PMC9133994 DOI: 10.2196/34655
Source DB: PubMed Journal: JMIR Ment Health ISSN: 2368-7959
Figure 1PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram.
Study characteristicsa.
| Author and country | Intervention, duration, and aim | Design and recruitment | Population | Results | Acceptance measure | Reasons for dropout | Level (acceptance) | |||||||
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| Sample size, N | Age (years) | Gender | Employment details |
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| Abbott et al [ | Internet-delivered CBTb program for employees with tinnitus distress in industrial organizations; 6 weeks; effectiveness of the program | Clustered RCTc comparing CBT intervention group with IOCd; recruited in industrial organizations (BP Australia and BHP Billiton) | 56 | CBT: mean 50.5 (SD 9.5); IOC: mean 48.7 (SD 8.6) | CBT: 96% men; IOC: 82% men | —e | CBT program was similarly effective to the information program for treating tinnitus distress, depression, anxiety, stress, and quality of life | Attrition rate: 50% (CBT: 70%); satisfaction: 73.4% (mean 5.14/7) | Unknown | ~f | ||||
| Allexandre et al [ | Web-based interactive educational stress management program (website), | RCT comparing 4 groups, including no support, group support, group and expert clinical support, and waitlist control; recruitment via email in a corporate call center | 161 | Mean 40.0 (SD 12.6) | 83.2% women | 49.1% full-time work shift (days); debt collectors and customer service or fraud representatives | Participants favored guided practices and showed low use of program. All groups decreased in perceived stress and improved in psychological and emotional well-being | Web-based use: 10% to 15% (intervention) | Lack of time | − −g | ||||
| Beiwinkel et al [ | Web-based program, | RCT comparing intervention with control; recruitment via health insurance | 180 | Mean 48 | 68% women | 51% full-time work | Dropout: 45.5% after the assessment, 67.7% follow-up; satisfaction: 68.2% (mean 2.04, intervention) | Relationship between age (older) and education (higher) and dropout rates (lower) | −h | |||||
| Birney et al [ | Mobile app intervention | RCT: MoodHacker group compared with alternative care with links to websites on depression; recruited via EAPsi and other outreaches | 300 | MoodHacker: mean 40.6 (SD 11.5); alternative care: mean 40.7 (SD 11.2) | MoodHacker: 74.6% women; alternative care: 78.7% women | 56% full-time, 35.3% part-time, and 8.7% self-employed | MoodHacker caused significant effects on depression symptoms compared with alternative care | Attrition: 6.7% follow-up; satisfaction: 76% (mean 4.6/6); system usability: B+ | Unknown |
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| Billings et al [ | Web-based stress and mood management multimedia program for employees based on CBT; 12-week access; effectiveness of the program to reduce depression and increase behavioral activation, knowledge of depression, and performance at work | RCT: experimental and control; recruited from a technology company via email and health fair | 309 | Most (51%) between 30 and 40 | 70.6% women | — | Decrease in stress, increase in knowledge of anxiety and depression as well as positive perception of treatment and improvement in the consumption of alcohol; most used it only once | Ratings (0-5): 71% useful (mean 3.55); interesting: M 3.47; appealing: M 3.34; motivating: M 3.21 | Participants who knew how to handle mood and stress at baseline had an increased likelihood of finishing the study |
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| Bolier et al [ | Web-based health promotion programs ( | Clustered RCT: web-based condition and waitlist control; recruited nurses and health professionals in a medical center via mail | 1140 | Mean 40 | 79.8% women | 71.9% nurses | The intervention significantly enhanced positive mental health | Uptake rate and compliance: 16% logged in, 5% started; dropout: 60.7% (intervention), 44% overall | Age predicted dropout (the younger the participants, the more likely they were to drop out) | − − | ||||
| Ebert et al [ | Web-based unguided recovery training, | RCT: intervention and waitlist control group; recruited via email at schools by the Ministry of Education (Germany, NRWl) | 64 | Mean 48.5 (SD 9.9) | 74.2% women | — | Significant reduction in insomnia severity | Completion rate: 48.4% all sessions | 38.5% technical problems, lack of time or motivation, disputed usefulness, or did not see any more benefit in using the program further before the final module; others did not report reasons | − | ||||
| Ebert et al [ | Unguided web-based stress management program, | RCT: intervention or waitlist control; recruited from general employees via the occupational health program of a health insurance company as well as via contacted HRm departments in Germany | 264 | Mean 42 | 72% women | 75% full-time; diverse sectors including economy, health, service, and social | Effectively reduced symptoms of mental and work-related stress among employees with stress | Attrition rate: 42% (7 sessions); dropout: 90% provided follow-up data; satisfaction (high): 95% overall | — |
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| Hamamura et al [ | Computer-delivered intervention (app), | Pilot non-RCT, quasi-experiment with intervention and control groups; recruited via research marketing company | 557 | Mean 38.82 (SD 9.58) | 41.2% women | 71.6% employed by a company, 7.5% employed by the government or a nonprofit organization, 6.3% self-employed, and 3.1% professionals | Intervention heightened participants’ perception of their pathological thoughts and alcohol consumption, whereas they only decreased face to face | Dropout rate: 15.3% follow up; adherence: 64.8% (intervention) stopped after the first day | — | − | ||||
| Heber et al [ | Stress website, | RCT: intervention and waitlist control group; recruited by the Ministry of Education from the general working population showing symptoms of stress and through newspaper articles | 264 | Mean 43.3 (SD 10.2) | 73.1% women | 77.3% full-time | Web-based interventions effectively decreased stress in employees | Completion rate: 70.05% all sessions; satisfaction (high): 92.2% | Time constraints (4/9), motivation constraints (3/9), technical difficulties (1/9), and dissatisfaction with the intervention (1/9) |
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| Ketelaar et al [ | eMHn interventions for health professionals— | RCT, randomization at ward level with intervention and control groups; recruited nurses and health professionals employed at an academic hospital | 1140 | Mean 39.5 | 80% men | — | eMH approach was not more effective than a control to increase work functioning and psychological well-being | Compliance rate: 6% started the intervention; dropout: 45% to follow-up | Younger participants were more likely to drop out; technical problems | − − | ||||
| Ly et al [ | Mobile phone stress management intervention for managers including short audio lectures, information, and exercise focusing on acceptance and commitment therapy; 6 weeks; efficacy of the smartphone treatment | RCT: stress intervention and waitlist control group; recruitment took place after a presentation about the project at multiple organizations (Swedish or American) and via advertisements on the internet | 73 | Mean 41.5 (SD 7.2) | 57.5% men | — | Intervention reduced stress and increased general health among managers | Adherence: 44.4% | — | − | ||||
| Nevedal et al [ | Digital health coaching program for chronic pain management using psychoeducation on self-management, coping, and stress; 4 weeks; effectiveness of the program on work interference, activity, stress, pain, quality of life, and health | Case report; 1-group design; recruited via mailings, emails, and posted communications within 37 American organizations or a member of 1 of 18 health care plans | 645 | Mean 56.16 (SD 12.83) | 69.3% women | — | Supported effectiveness of interventions on pain (1 and 6 months after treatment) as well as quality of life (after 6 months) | Satisfaction (good or better): 82.6% | — |
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| Feicht et al [ | Happiness exercises to develop a positive psychological state; 7 weeks; examined the impact of the intervention on psychological and physiological parameters | Longitudinal design (2 groups—intervention and control); recruited via local insurance company in Germany (2 participating departments were chosen by the company) | 142 | Mean 37 (SD 7.7) | 68.8% women | — | Happiness, satisfaction, mindfulness, and quality of life improved; stress decreased; and recovery experience increased significantly | Dropout rate: 31.3% total | Difference in age in intervention and control groups (10 years) |
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| Thiart et al [ | Internet-based CBT-Io intervention, | RCT: intervention group and waitlist control; recruited via email sent to schools in Germany | 128 | Mean 48.0 (SD 9.9) | 74.2% women | 100% school teachers | The intervention reduced sleep difficulties and fostered psychological detachment from work | Completion rate: 95.3%; satisfaction: 91% would recommend it | — |
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| Umanodan et al [ | Computer-based stress management training using self-paced behavioral, communication, and cognitive techniques; 7 weeks; effectiveness of the program in improving mental health and performance at work | Clustered RCT; recruited via informational posters and the supervisor during meetings in a manufacturing company | 263 | Mean 38.85 | 92.6% men | 23% managers | Knowledge about stress management and coping skills increased (if participants had enough time) | Completion rate (intervention group): 89% | High baseline levels of distress increased the chance of dropout |
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| Wood et al [ | Resilience mobile app to decrease burnout (assessment tools); 4 weeks; assess usability, acceptability, and effectiveness | Pilot study; recruited mental health care professionals from a health care system | 30 | Mean 42.5 (SD 12) | — | 43% psychologists, 30% social workers, 13% psychiatric nurses, 7% psychiatrists, and 7% other | App reduced burnout and compassion fatigue in participants | System usability (overall): 79.4% | — |
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| Bush et al [ | Mixed methods design: qualitative and quantitative (Likert-style and open-ended questions); recruited via posters and flyers distributed by WTUq | 8 | — | 62% men | Clinical social work staff | The app was perceived as easy to use, helpful, and beneficial | Useful rating: 88%; qualitative: utility rating positive but could incorporate additional factors to make it more manifold | 2 participants did not want to download the app (privacy concerns were assumed) |
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| Carolan et al [ | Web-based stress management intervention, | Qualitative study: 18 semistructured interviews (taken from previous RCT with and without access to a web-facilitated discussion group); recruited from 6 UK-based organizations and invited via mail (universities, local authorities, third sector, and telecommunications) | 18 (based on the sample N=82) | Mean 45 | 78% women | 78% office work and 22% mixture of office and client work | Outlined advantages of digital mental health interventions, but high barriers appeared with the application in the workplace | Engagement: 39%; qualitative: preference for short, interactive, easy to use, personalized, and anonymous interventions and access via computer or mobile phone | — | − | ||||
| Deady et al [ | Emergency service workers’ attitude toward mobile mental health apps | Cross-sectional study; recruited from 4 metropolitan Fire and Rescue stations | 106 | Mean 37.8 (SD 9.51) | 88% men | Firefighters | Participants showed positive perception and interest in using mental health apps but had preferences regarding language, features, and therapeutic techniques | Divided interests in using a mental health app. Apps should avoid stigmatized terminology and focus on well-being, mental fitness, resilience, stress, lifestyle, and sleep by implementing attractive multimedia features | — |
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| Deady et al [ | Acceptance and effectiveness study on | 2-stage pilot study; recruited via email and Facebook from industrial organizations (agriculture, freight or postage, and mining) | Stage 1: 21; stage 2: 84 | Stage 1: mean 37.86 (SD 10.98); stage 2: mean 38 (SD 9.23) | Stage 1: 50% women; stage 2: 100% men | Stage 1: most worked in freight and postage (n=11); stage 2: male-dominated industry | HeadGear was effective and reduced symptoms significantly. However, attrition rate was high | Utility: 40% to 50% would use it; qualitative: most appreciated the utility, helpfulness, overall ease, and accessibility but complained about engagement and navigation issues | — | − | ||||
| Eklund et al [ | University staff’s experiences of a customized, interactive, web-based program that aims to change behavior in stress management as well as explore intervention adjustments | Explorative qualitative study: semistructured interviews; recruitment via 3 departments at the university | 9 | Mean 45.9 | — | University staff | Staff accepted a web-based program for stress-related problems | Acceptance was positive as long as it was short in time and applied in a transparent and tailored way | — |
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| Hennemann et al [ | Employees’ acceptance of organizational eMH interventions focusing on work-related distress | Longitudinal cohort study: self-administered questionnaire; recruited employees showing health problems and previous sickness absence | 1829 | Mean 49.93 (SD 4.06) | — | — | Attitudes toward organizational eMH interventions were disadvantageous | Acceptance (low): 89.1%; suggestions for improvement of acceptance: previous education (awareness and attitudes regarding efficacy and usability) | Higher scores in men and high-education group, those with previous experience with eHealth, and mentally demanding work types; lower scores in those diagnosed with a mental health disorder and non–internet users | − − | ||||
| Peters et al [ | Explorative workshop of perceptions, thoughts, and preferences of employees in male-dominated workplaces to build and adapt a mental health mobile app | Exploratory qualitative study; recruited via emails distributed to 2 organizations (state fire and rescue service and a freight transport organization) | 60 | Between 26 and 65 | 92% men | 27% rural, 23% suburban, and 50% urban | Relevance of considering language use and preferred features and balancing preferences with the need for evidence-based interventions | Men preferred unstigmatized language use, a simple mood management app, and guidance involvement | — |
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| Schneider et al [ | Views and acceptance of 2 self-help applications for depression: | Mixed methods; recruited from 3 organizations: 2 private enterprises (telecommunications and transport) and 1 health organization | 637 | Mean 42 (SD 9.6) | 50.2% men | — | Evidence-based computerized approaches supported acceptability, which could be increased by taking care of barriers and users’ expectations | Dropout: 63%; positive rating: 24%; various intrinsic and extrinsic barriers that lead to a high unacceptance; acceptance increases with interactive support | Intrinsic: intrapersonal problems; extrinsic: technical problems; generic: perception of cCBT | − − | ||||
| Wang and Ho [ | Explorative study on barriers and preferences for specific features among male workers in a mental health tool | Cross-sectional study; recruited by random digit-calling method to households collecting data from 511 men with risk of depression | 841 | Mean 44.3 (SD 13.7) | 100% men | — | Overall positive results, but men’s preferences and perceived barriers should be taken into account to increase acceptability | Acceptance in men was good, but apps should be mobile and tailored to preferences, including various topics and designs | Having high risk of depression at baseline increased the chance to see the utility of the intervention compared with low-risk individuals (83.4% vs 75%) |
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| Williams et al [ | Feasibility of a web-enhanced behavioral self-management program, | Cross-sectional study; recruited and invited all active-duty members at Naval Medical Center, Portsmouth, Virginia | 142 | Mean 41.1 (SD 9.2) | 55% women | 24% officers and 76% enlisted sailors | Supported the feasibility of Stress Gym as being a web-based CBT-based self-help intervention accepted by the users and demonstrated reduction in stress | StressGym was rated as very useful and informative | — |
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| Wilson et al [ | Soldiers’ attitude toward technology-based approaches to mental health care | Cross-sectional study; recruited from pre- and postdeployment clinic (in the waiting room for screening visits) | 352 | Mean 25.9 (SD 5.8) | 92% men | — | Feasibility of technology-based approaches was supported | Willingness to use: 84% were willing to use one of the 11 interventions; comfort: 75% felt neutral/very comfortable using a computer/program | — |
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aSorted from indirect to more direct measures.
bCBT: cognitive behavioral therapy.
cRCT: randomized controlled trial.
dIOC: information-only control.
eData missing or not relevant.
fMixed results.
gLow.
hModerate.
iEAP: employee assistance program.
jVery high.
kHigh.
lNRW: North Rhine-Westphalia.
mHR: human resources.
neMH: e-mental health.
oCBT-I: cognitive behavioral therapy for insomnia.
pPTSD: posttraumatic stress disorder.
qWTU: Warrior Transition Unit.
rcCBT: computerized cognitive behavioral therapy.