Breaking Open the Black Box: Isolating the Most Potent Features of a Web and Mobile Phone-Based Intervention for Depression, Anxiety, and Stress
Notice bibliographique
Résumé
BACKGROUND: Internet-delivered mental health (eMental Health) interventions produce treatment effects similar to those observed in face-to-face treatment. However, there is a large degree of variation in treatment effects observed from program to program, and eMental Health interventions remain somewhat of a black box in terms of the mechanisms by which they exert their therapeutic benefit. Trials of eMental Health interventions typically use large sample sizes and therefore provide an ideal context within which to systematically investigate the therapeutic benefit of specific program features. Furthermore, the growth and impact of mobile phone technology within eMental Health interventions provides an opportunity to examine associations between symptom improvement and the use of program features delivered across computer and mobile phone platforms. OBJECTIVE: The objective of this study was to identify the patterns of program usage associated with treatment outcome in a randomized controlled trial (RCT) of a fully automated, mobile phone- and Web-based self-help program, "myCompass", for individuals with mild-to-moderate symptoms of depression, anxiety, and/or stress. The core features of the program include interactive psychotherapy modules, a symptom tracking feature, short motivational messages, symptom tracking reminders, and a diary, with many of these features accessible via both computer and mobile phone. METHODS: Patterns of program usage were recorded for 231 participants with mild-to-moderate depression, anxiety, and/or stress, and who were randomly allocated to receive access to myCompass for seven weeks during the RCT. Depression, anxiety, stress, and functional impairment were examined at baseline and at eight weeks. RESULTS: Log data indicated that the most commonly used components were the short motivational messages (used by 68.4%, 158/231 of participants) and the symptom tracking feature (used by 61.5%, 142/231 of participants). Further, after controlling for baseline symptom severity, increased use of these alert features was associated with significant improvements in anxiety and functional impairment. Associations between use of symptom tracking reminders and improved treatment outcome remained significant after controlling for frequency of symptom tracking. Although correlations were not statistically significant, reminders received via SMS (ie, text message) were more strongly associated with symptom reduction than were reminders received via email. CONCLUSIONS: These findings indicate that alerts may be an especially potent component of eMental Health interventions, both via their association with enhanced program usage, as well as independently. Although there was evidence of a stronger association between symptom improvement and use of alerts via the mobile phone platform, the degree of overlap between use of email and SMS alerts may have precluded identification of alert delivery modalities that were most strongly associated with symptom reduction. Future research using random assignment to computer and mobile delivery is needed to fully determine the most ideal platform for delivery of this and other features of online interventions. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ACTRN): 12610000625077; http://www.anzctr.org.au/TrialSearch.aspx? (Archived by WebCite http://www.webcitation.org/6WPqHK0mQ).
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, pas un consensus.
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