Therapy Companion Mobile App for Acceptance and Commitment Therapy Exercises (ACTaide): Therapist and Client Co-Design Study
Notice bibliographique
Résumé
BACKGROUND: Acceptance and commitment therapy (ACT) relies heavily on the between-session practice of therapeutic exercises to promote skill acquisition and improve psychological flexibility. However, adherence to this between-session practice remains a challenge. Mobile apps offer a promising solution to bridge this gap. However, few ACT apps focus exclusively on supporting clients in their between-session practice, and fewer apps involve stakeholders in their design. ACTaide, a therapy companion mobile app co-designed with stakeholders, addresses these barriers by guiding clients through ACT exercises and metaphors using annotated image sequences, supporting their between-session practice. OBJECTIVE: This study aimed to co-design ACTaide with therapists and clients, incorporating their feedback to ensure the app aligns with clinical goals and the needs of end users. The research explored stakeholder preferences and feedback on app functionality, design, and features to guide iterative design improvements. METHODS: Using a qualitative, user-centered design framework, we conducted 4 consecutive focus groups: 2 with 10 licensed ACT therapists and 2 with 14 psychotherapy clients. Each focus group included semistructured discussions and co-design activities. Data were collected through audio recordings and design artifacts (eg, sketches), which were analyzed using thematic content analysis. RESULTS: A total of 9 themes were identified, reflecting areas of convergence and divergence between therapists and clients. The therapists and clients expressed enthusiasm for ACTaide as a tool to support between-session practice. Both groups emphasized the importance of a user-friendly, intuitive, and aesthetically appealing interface, with a preference for high-quality visuals over text-heavy features. Personalization and customization were viewed as essential for enhancing app engagement. The therapists prioritized accessibility and clinical appropriateness, voicing concerns about features that may be inconsistent with ACT principles, such as symptom rating scales, and clarified their role in app delivery. By contrast, the clients emphasized wanting greater interactivity and elements of gamification to improve engagement. Slight discrepancies were noted between therapists' preferences for minimal designs and clients' preferences for more vibrant and engaging aesthetics. Overall, both groups recognized the app's potential to address barriers to homework adherence and to extend the benefits of therapy into clients' daily lives. CONCLUSIONS: The study illustrates the value of using a user-centered, co-design approach in the development of ACTaide, an adjunctive mental health app for the between-session practice of ACT exercises and metaphors tailored to therapist and client preferences. Through the integration of stakeholder feedback, the findings provide actionable insights for designing psychotherapy tools that balance clinical goals with user preferences. Future research will focus on testing high-fidelity prototypes to evaluate acceptability, usability, and engagement.
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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 | 0,016 | 0,021 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,001 |
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 ».