Establishment and Maintenance of a Digital Therapeutic Alliance in People Living With Negative Symptoms of Schizophrenia: Two Exploratory Single-Arm Studies
Notice bibliographique
Résumé
BACKGROUND: Evidence-based digital therapeutics represent a new treatment modality in mental health, potentially providing cost-efficient, accessible means of augmenting existing treatments for chronic mental illnesses. CT-155/BI 3972080 is a prescription digital therapeutic under development as an adjunct to standard of care treatments for patients 18 years of age and older with experiential negative symptoms (ENS) of schizophrenia. Individual components of CT-155/BI 3972080 are designed based on the underlying principles of face-to-face treatment. A positive therapeutic alliance between patients and health care providers is linked with improved clinical outcomes in mental health. Likewise, establishing a similar therapeutic alliance with a digital therapeutic (ie, digital working alliance [DWA]) may be important for engagement and treatment effectiveness of this modality. OBJECTIVE: This study aimed to investigate the establishment and maintenance of a DWA between a beta version of CT-155/BI 3972080 (CT-155 beta) and adults with ENS of schizophrenia. METHODS: Two multicenter, exploratory, single-arm studies (study 1: CT-155-C-001 and study 2: CT-155-C-002) enrolled adults with schizophrenia and ENS receiving stable antipsychotic medication (≥12 weeks). Participants had access to CT-155 beta and were presented with daily in-app activities during a 3-week orientation phase that included lessons designed to facilitate building of a DWA. In study 2, the 3-week orientation phase was followed by an abbreviated active 4-week phase. Digital literacy at baseline was evaluated using the Mobile Device Proficiency Questionnaire (MDPQ). The mobile Agnew Relationship Measure (mARM) was used to assess DWA establishment after 3 weeks in both studies, and after 7 weeks in study 2 to assess DWA maintenance. Participant safety, digital literacy, and correlations between negative symptom severity and DWA were assessed in both studies. RESULTS: Of the enrolled participants, 94% (46/49) and 86% (43/50) completed studies 1 and 2, respectively. Most were male (study 1: 71%, 35/49; study 2: 80%, 40/50). The baseline digital literacy assessed through MDPQ score was comparable in both studies (study 1: mean 30.56, SD 8.06; study 2: mean 28.69, SD 8.31) indicating proficiency in mobile device use. After 3 weeks, mARM scores (study 1: mean 5.16, SD 0.8; study 2: mean 5.36, SD 1.06) indicated that a positive DWA was established in both studies. In study 2, the positive DWA established at week 3 was maintained at week 7 (mARM: mean 5.48, SD 0.97). There were no adverse events (AEs) in study 1, and 3 nonserious and nontreatment-related AEs in study 2. CONCLUSIONS: A positive DWA was established between participants and CT-155 beta within 3 weeks. The second 7-week study showed maintenance of the DWA to the end of the study. Results support the establishment and maintenance of a DWA between adults with ENS of schizophrenia and a beta version of CT-155/BI 3972080, a prescription digital therapeutic under development to target these symptoms. TRIAL REGISTRATION: Clinicaltrials.gov NCT05486312; https://clinicaltrials.gov/study/NCT05486312.
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 | 0,011 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,005 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».