Reluctance to Use a Psycho-Oncology Mobile App Among Patients With Primary Breast Cancer: Retrospective Cross-Sectional Survey
Notice bibliographique
Résumé
Background: eHealth is an increasingly used method of health care in the field of psycho-oncology. While many reports highlight the positive impact of psychological eHealth tools, some patients refuse to use them. Objective: This study aimed to expand knowledge of the motivation and psychoemotional functioning of patients who consciously refuse to use eHealth technology in the form of a mobile psycho-oncology app offered as part of a clinical trial. To our knowledge, this is the first study to address this topic. Methods: A retrospective cross-sectional study was conducted between December 2022 and February 2023 to investigate the reasons why 56 patients with breast cancer refused to use the psycho-oncology mobile app offered as part of a clinical trial by the Breast Cancer Unit. The primary aim of the study was to analyze patients' self-reported reasons for not engaging with the app, while also exploring their psychoemotional functioning, including stress levels (measured using the distress thermometer), personality traits (measured using the Ten-Item Personality Inventory), coping strategies (measured using the Coping Orientation to Problems Experienced Questionnaire), and Self-efficacy (measured using the General Self-Efficacy Scale). Participants in this study declined the app intervention but agreed to participate in this separate observational study, indicating that their refusal was related to the app itself rather than to participation in clinical research in general. Results: The patients experienced a clinically meaningful elevation in stress levels (mean 5, SD 2.1 points) and Self-efficacy (mean 32.1, SD 5.1 points). Among 5 dimensions of personality traits, patients scored highest in Agreeableness (mean 6.5, SD 0.8 stens) and Conscientiousness (mean 6.4, SD 0.9) and lowest in Neuroticism (mean 3.4, SD 1.8) (other dimensions: Extraversion [mean 5.8, SD 1.6 stens] and Openness to Experiences [mean 4.4, SD 1.5 stens]). In terms of coping with stress, patients most frequently used the strategies of Active Coping (mean 2.6, SD 0.5 points), Acceptance (mean 2.6, SD 0.6 points), and Seeking Emotional Support (mean 2.6, SD 0.6 points), and least frequently used the strategies of Psychoactive Substance Use (mean 0.2, SD 0.6 points) and Restraint (mean 0.5, SD 0.7 points). Patient responses regarding refusal to participate in app testing were divided into four categories: (1) Focus on Life Outside the Disease, (2) Focus on Disease and Treatment, (3) Denial Mechanism, and (4) Technical Issues. Statistically significant differences were found between the groups. The Focus on Life Outside the Disease group of patients had higher levels of Self-efficacy, lower Neuroticism, and more frequent use of the Positive reevaluation strategy compared to the other groups. Conclusions: Our patients' decision not to use the eHealth psycho-oncology app was mainly influenced by characteristics suggesting better emotional coping with the disease and treatment. These factors were significantly more influential than other factors studied, particularly those related to technology. Assessing reasons for opting out of eHealth and associated psychomotional functioning may be important for improving patients' adoption of eHealth solutions.
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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 | 0,001 | 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 ».