Health-Related Internet Usage and Design Feature Preference for E-Mental Health Programs Among Men and Women
Bibliographic record
Abstract
BACKGROUND: Major depressive episodes (MDEs) are prevalent in the workplace and affect workers' health and productivity. Therefore, there is a pressing need for innovation in the prevention of MDEs in the workplace. Electronic mental (e-mental) health programs are a cost-effective approach toward the self-management of stress and emotional issues. E-mental health dropout rate, MDE prevalence, and symptoms greatly vary by sex and age. Thus, the development and implementation of e-mental health programs for the prevention of MDEs need to be examined through a sex and age lens to enhance program use and effectiveness. OBJECTIVE: This study aimed to examine design feature preferences based on sex and age for an e-mental health program targeted toward depression prevention. METHODS: Household residents across Canada were contacted using the random digit dialing method. 500 women and 511 men who were 18 years and older and who were at high risk of having MDEs were interviewed. Internet use was assessed using questions from the 2012 Canadian Internet Use Survey conducted by Statistics Canada, and preferred design features of e-mental health program questions were developed by the BroMatters team members. The proportions of likely use of specific features of e-mental health programs in women were estimated and compared with those in men using chi-square tests. The comparisons were made overall and by age groups. RESULTS: Men (181/511, 35.4%) and women (211/500, 42.2%) differed significantly in their likelihood of using an e-mental health program. Compared with men (307/489, 62.8%), women (408/479, 85.2%) were more likely to use the internet for medical or health-related information. Women were more likely to use the following design features: practices and exercises to help reduce symptoms of stress and depression (350/500, 70.7%), a self-help interactive program that provides information about stress and work problems (302/500, 61.8%), the ability to ask questions and receive answers from mental health professionals via email or text message (294/500, 59.9%), and to receive printed materials by mail (215/500, 43.4%). Men preferred to receive information in a video game format (156/511, 30.7%). Younger men (46/73, 63%) and younger women (49/60, 81%) were more likely to access a program through a mobile phone or an app, and younger men preferred having access to information in a video game format. CONCLUSIONS: Factors such as sex and age influenced design feature preferences for an e-mental health program. Working women who are at high risk for MDEs preferred interactive programs incorporating practice and exercise for reducing stress, quality information about work stress, and some guidance from professionals. This suggests that sex and age should be taken into account when designing e-mental health programs to meet the needs of individuals seeking help via Web-based mental health programs and to enhance their use.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".