Help to Overcome Problems Effectively for Cancer Survivors: Development and Evaluation of a Digital Self-Management Program
Notice bibliographique
Résumé
BACKGROUND: People living with cancer face numerous psychosocial challenges, including cancer-related fatigue, fear of recurrence, and depression. There is a lack of digital interventions tailored to the needs of people living with all types of cancer. We developed a 6-week, digital, peer-delivered, self-management program: iHOPE (Help to Overcome Problems Effectively; where 'i' indicates the digital version of the program). The program is underpinned by positive psychology and cognitive behavioral therapy to meet these psychosocial challenges. OBJECTIVE: This study aimed to assess the feasibility of the iHOPE program among people living with cancer. Program adherence and satisfaction along with changes in psychological distress and positive well-being were measured. METHODS: A pre-post, acceptability, and feasibility design was used. People living with cancer (N=114) were recruited via a national cancer charity in the United Kingdom and were given access to the iHOPE program. Demographic and other participant characteristics were recorded. Participants completed digital measures at baseline and the end of the 6-week program for depression, anxiety, cancer-related fatigue, cancer worry or fear of cancer recurrence, positive mental well-being, hope, gratitude, and health status. The website's system recorded data on the usage of the program. Satisfaction with the program was also measured. RESULTS: A total of 114 participants completed the baseline questionnaires. Of these, 70 people (61.4%) participated in all 6 sessions. The mean number of sessions undertaken was 5.0 (SD 1.5). Moreover, 44.7% (51/114) of participants completed at least three sessions and end-of-program outcome measures. A total of 59 participants completed the satisfaction questionnaire, where ≥90% (54/58) of participants reported that the program was easy to navigate and was well managed by the peer facilitators, and that they found the social networking tools useful. Preliminary efficacy testing among the 51 participants who completed baseline and postprogram outcome measures showed that postprogram scores decreased for depression, anxiety, cancer-related fatigue, and fear of recurrence (all P<.001) and increased for positive mental well-being (P<.001), hope (both P<.001), and gratitude (P=.02). CONCLUSIONS: The feasibility evidence is promising, showing that the peer-delivered digital iHOPE program is acceptable and practical. Implementation of the iHOPE program on a wider scale will incorporate further research and development to maximize the completion rates of the measures. Initial effectiveness data suggest positive impacts on important cancer-related quality of life and mental well-being outcomes. A randomized controlled trial design with a longer follow-up is needed to confirm the potential of the iHOPE program for improving mental and physical health outcomes for cancer survivors.
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 | 0,003 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| 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) | 0,003 | 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 ».