Health-Related Internet Usage and Design Feature Preference for E-Mental Health Programs Among Men and Women (Preprint)
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».