User Experiences in a Digital Intervention to Support Total Skin Self-examination by Melanoma Survivors: Nested Qualitative Evaluation Embedded in a Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Melanoma is a relatively common cancer type with a high survival rate, but survivors risk recurrences or second primaries. Consequently, patients receive regular hospital follow-up, but this can be burdensome to attend and not optimally timed to detect arising problems. Total skin self-examination (TSSE) supports improved clinical outcomes from melanoma via earlier detection of recurrences and second primaries, and digital technology has the potential to support TSSE. Recent research with app-based interventions aimed at improving the well-being of older adults has found that they can use the technology and benefit from it, supporting the use of digital health care in diverse demographic groups. Thus, the Achieving Self-directed Integrated Cancer Aftercare (ASICA) digital health care intervention was developed. The intervention provided melanoma survivors with a monthly prompt to perform a TSSE as well as access to a dermatology nurse who provided them with feedback on photographs and descriptions of their skin. OBJECTIVE: We aimed to explore participants' attitudes, beliefs, and experiences regarding TSSE practices. Furthermore, we explored how participants experienced technology and how it influenced their practice of TSSE. Finally, we explored the practical and technical experiences of ASICA users. METHODS: This was a nested qualitative evaluation within a dual-center randomized controlled trial of the ASICA intervention. We conducted semistructured telephone interviews with the participants during a randomized controlled trial. The participants were purposively sampled to achieve a representative sample with representative proportions by age, sex, and residential geography. Interviews were transcribed verbatim and analyzed using a framework analysis approach applied within NVivo 12. RESULTS: A total of 22 interviews were conducted with participants from both groups. In total, 40% (9/22) of the interviewed participants were from rural areas, and 60% (13/22) were from urban areas; 60% (13/22) were from the intervention group, and 40% (9/22) were from the control group. Themes evolved around skin-checking behavior, other people's input into skin checking, contribution of health care professionals outside ASICA and its value, ideas around technology, practical experiences, and potential improvements. ASICA appeared to change participants' perceptions of skin checking. Users were more likely to report routinely performing TSSE thoroughly. There was some variation in beliefs about skin checking and using technology for health care. Overall, ASICA was experienced positively by participants. Several practical suggestions were made for the improvement of ASICA. CONCLUSIONS: The ASICA intervention appeared to have positively influenced the attitudes and TSSE practices of melanoma survivors. This study provides important qualitative information about how a digital health care intervention is an effective means of prompting, recording, and responding to structured TSSE by melanoma survivors. Technical improvements are required, but the app offers promise for technologically enhanced melanoma follow-up in future. TRIAL REGISTRATION: ClinicalTrials.gov NCT03328247; https://clinicaltrials.gov/ct2/show/NCT03328247?term=ASICA&rank=1. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s13063-019-3453-x.
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 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 | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».