Engagement With an Internet-Administered, Guided, Low-Intensity Cognitive Behavioral Therapy Intervention for Parents of Children Treated for Cancer: Analysis of Log-Data From the ENGAGE Feasibility Trial
Notice bibliographique
Résumé
BACKGROUND: Parents of children treated for cancer may experience psychological difficulties including depression, anxiety, and posttraumatic stress. Digital interventions, such as internet-administered cognitive behavioral therapy, offer an accessible and flexible means to support parents. However, engagement with and adherence to digital interventions remain a significant challenge, potentially limiting efficacy. Understanding factors influencing user engagement and adherence is crucial for enhancing the acceptability, feasibility, and efficacy of these interventions. We developed an internet-administered, guided, low-intensity cognitive behavioral therapy (LICBT)-based self-help intervention for parents of children treated for cancer, (EJDeR [internetbaserad självhjälp för föräldrar till barn som avslutat en behandling mot cancer or internet-based self-help for parents of children who have completed cancer treatment]). EJDeR included 2 LICBT techniques-behavioral activation and worry management. Subsequently, we conducted the ENGAGE feasibility trial and EJDeR was found to be acceptable and feasible. However, intervention adherence rates were marginally under progression criteria. OBJECTIVE: This study aimed to (1) describe user engagement with the EJDeR intervention and examine whether (2) sociodemographic characteristics differed between adherers and nonadherers, (3) depression and anxiety scores differed between adherers and nonadherers at baseline, (4) user engagement differed between adherers and nonadherers, and (5) user engagement differed between fathers and mothers. METHODS: We performed a secondary analysis of ENGAGE data, including 71 participants. User engagement data were collected through log-data tracking, for example, communication with e-therapists, homework submissions, log-ins, minutes working with EJDeR, and modules completed. Chi-square tests examined differences between adherers and nonadherers and fathers and mothers concerning categorical data. Independent-samples t tests examined differences regarding continuous variables. RESULTS: Module completion rates were higher among those who worked with behavioral activation as their first LICBT module versus worry management. Of the 20 nonadherers who opened the first LICBT module allocated, 30% (n=6) opened behavioral activation and 70% (n=14) opened worry management. No significant differences in sociodemographic characteristics were found. Nonadherers who opened behavioral activation as the first LICBT module allocated had a significantly higher level of depression symptoms at baseline than adherers. No other differences in depression and anxiety scores between adherers and nonadherers were found. Minutes working with EJDeR, number of log-ins, days using EJDeR, number of written messages sent to e-therapists, number of written messages sent to participants, and total number of homework exercises submitted were significantly higher among adherers than among nonadherers. There were no significant differences between fathers and mothers regarding user engagement variables. CONCLUSIONS: Straightforward techniques, such as behavioral activation, may be well-suited for digital delivery, and more complex techniques, such as worry management, may require modifications to improve user engagement. User engagement was measured behaviorally, for example, through log-data tracking, and future research should measure emotional and cognitive components of engagement. TRIAL REGISTRATION: ISRCTN Registry 57233429; https://doi.org/10.1186/ISRCTN57233429.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,013 | 0,030 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».