Virtual Delivery of Early Psychosis Care: A Retrospective Cohort Study of Factors Associated with Initial Engagement (Preprint)
Notice bibliographique
Résumé
BACKGROUND The transition to virtual care delivery following the COVID-19 pandemic had the potential to impact access to and engagement with early psychosis intervention (EPI) services. Despite evidence that virtual EPI is well-received by youth and has benefits such as reported improvements in accessibility, convenience, and comfort, there remain potential challenges with technology including the amplification of the “digital divide” and privacy or confidentiality concerns. Early engagement in EPI services is important for long-term recovery; however, little is known about EPI engagement in the context of virtual care. Our previous work showed that older patients and those referred from the emergency department (ED) were less likely to attend their EPI consultation appointment, but it is not clear how these and other factors impact engagement in virtual care. OBJECTIVE To identify factors associated with attendance at the initial EPI consultation appointment when most were being delivered virtually. METHODS This retrospective cohort study used electronic medical record data from patients aged 16 to 29 who were referred to a large EPI program between April 2020 and December 2020. The primary outcome was the rate of attendance at the EPI consultation appointment. Variables included health equity and service use factors. Statistical comparisons were made with 2018-2019 data from the same site prior to virtual care implementation using chi-square tests for categorical variables and independent t tests for continuous variables, as well as binary logistic regression. RESULTS Between April and December 2020, 301 unique patients were referred for EPI. Patients had a mean (standard deviation) age of 23.2 (3.3) years; 214 (71.1%) identified as male; 88 (29.2%) identified as White; 121 (40.2%) identified as heterosexual; 139 (46.2%) were born in Canada. Compared to pre-virtual care, the proportion of inpatient referrals was higher (114/301, 37.9%), while referrals from outpatient and other providers were lower (122/301, 40.5%) post-virtual care (χ22=18.7, P<.001). The wait time from referral to consultation decreased post-virtual care (t1,149=6.44, P<.001). Attendance at the consultation appointment increased post-virtual care (84.1%, 253/301) compared to pre-virtual care (77.1%, 770/999) (χ21=6.71, P=.01, φ=0.072). In the multivariable model, patients identifying as Black (OR 0.45, 95% CI 0.21-0.96) and patients referred from the ED or bridging clinic (OR 0.23, 95% CI 0.08-0.69) had decreased odds of attendance at the consultation appointment. CONCLUSIONS Findings from this cohort study of patients referred to EPI services suggests that virtual care may improve initial engagement in EPI services; however, barriers to care still exist for structurally marginalized and high acuity patients.
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 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| 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 | 0,001 |
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 ».