Notice bibliographique
Résumé
What Is the Issue? The rate of mental illnesses, such as major depressive disorder and generalized anxiety disorder, has significantly increased among people aged 15 and older living in Canada. In Canada, more than 1 in 3f those with mental illnesses do not receive adequate mental health (MH) services, with notable geographic disparities in the availability and quality of services. Specialized MH services remain particularly scarce in remote and rural areas. Providing MH counselling through virtual platforms has the potential to enhance the accessibility of MH services and reduce the stigma associated with in-person services. A review of the clinical effectiveness and evidence-based guidelines is required to help understand the potential role of virtual MH counselling in clinical practice. What Did We Do? To inform decisions regarding the use of virtual MH counselling for people with depression, anxiety, obsessive-compulsive disorder (OCD) or posttraumatic stress disorder (PTSD), we conducted a rapid review and summarized evidence that compared the clinical effectiveness of MH counselling provided in a virtual setting versus in person. We also sought to identify evidence-based guidelines regarding the use of virtual MH counselling for these populations. We searched key resources, including journal citation databases, and conducted a focused internet search for relevant evidence published since 2019. One reviewer screened articles for inclusion based on predefined criteria, critically appraised the included studies, and narratively summarized the findings. What Did We Find? We found 6 systematic reviews (SRs) relevant to the present review that evaluated the clinical effectiveness of MH counselling provided through virtual versus in-person settings. Most SRs and their included randomized controlled trials (RCTs) reported results on the reduction of depression and anxiety, followed by PTSD and OCD. For depression, PTSD and specific anxiety outcomes (generalized anxiety disorder, social anxiety disorder, and panic disorder), the effectiveness of virtual MH counselling in improving these outcomes was comparable to in-person settings. For OCD, results were inconsistent, suggesting virtual MH counselling can be an alternative treatment where in-person MH counselling is not readily available. We found 5 evidence-based guidelines that provide recommendations on the use of virtual MH counselling for adults with depression, anxiety, and PTSD, based mostly on low-quality evidence or expert opinion. We did not find any evidence-based guidelines or relevant recommendations regarding the use of virtual MH counselling for people of any age with OCD nor children and youth with depression, anxiety, and PTSD. Virtual MH counselling is recommended as a first-line intervention for adults with mild depression and for reducing symptoms of anxiety in older adults. Virtual MH counselling is recommended as second-line adjunctive or alternative intervention for adults with moderate-severe depression, certain anxiety disorders, and PTSD. What Does This Mean? Virtual MH counselling may improve clinical outcomes for people with depression, anxiety, OCD, or PTSD and can be used as a comparable or alternative treatment to in-person MH counselling. Virtual MH counselling may address equity issues regarding access to evidence-based MH services where in-person MH counselling is not readily available. Clinicians and health care decision-makers can use the evidence summarized in this review to inform decisions regarding the implementation of virtual MH counselling for adults with depression, anxiety, OCD, or PTSD.
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 | 0,010 | 0,075 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,004 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,005 | 0,006 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,034 | 0,003 |
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 ».