Evidence map›Paper›PMID 40934463›Full record

ArticleJMIR mental health2025

Child and Adolescent Virtual Mental Health Care and Duration of Treatment: Retrospective Cohort Study.

Allyson Cruickshank, Pantelis Andreou, Debbie Johnson Emberly, Sandra Meier, Leslie Anne Campbell

Abstract read
In one paragraph

Article in JMIR mental health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Allyson CruickshankDepartment of Community Health and Epidemiology, Faculty of Medicine, Dalhousie University, 5790 University Avenue, Halifax, NS, B3H 1V7, Canada, 1 902-494-3860.ORCID 0009-0008-7859-0625
Pantelis AndreouDepartment of Community Health and Epidemiology, Faculty of Medicine, Dalhousie University, 5790 University Avenue, Halifax, NS, B3H 1V7, Canada, 1 902-494-3860.ORCID 0000-0002-5554-1432
Debbie Johnson EmberlyDepartment of Psychology and Neuroscience, Faculty of Science, Dalhousie University, Halifax, NS, Canada.ORCID 0000-0003-0114-1211
Sandra MeierDepartment of Psychiatry, Faculty of Medicine, Dalhousie University, Halifax, NS, Canada.ORCID 0000-0002-3287-5894
Leslie Anne CampbellDepartment of Community Health and Epidemiology, Faculty of Medicine, Dalhousie University, 5790 University Avenue, Halifax, NS, B3H 1V7, Canada, 1 902-494-3860.ORCID 0000-0003-2534-0450

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Due to public health restrictions, the COVID-19 pandemic required significant changes in the delivery of child and adolescent mental health services. The use of virtual care for balancing access with treatment needs requires a shared decision between clients, caregivers, and clinicians. One aspect for consideration is the length of treatment necessary to achieve desired outcomes and whether it differs by treatment modality. Insights gained from the comparison of treatment duration between modalities may improve our understanding of the effectiveness of virtual care and help to inform clinical decision-making and effective use of resources. Objective: We sought to improve our understanding of how treatment modality impacts treatment duration for children and adolescents accessing Community Mental Health and Addictions services at IWK Health following the rapid implementation of virtual care in March 2020. In this study, we aimed to compare the duration of treatment within episodes of care by treatment modality and determine whether client characteristics, system factors, or time period influenced any associations between treatment modality and treatment duration. Methods: Episodes of care were created using administrative data collected by the IWK Mental Health and Addictions program and used as the unit of analysis. A multilevel mixed-effects negative binomial model and time-to-event analysis were used to model the association between treatment modality and treatment duration, both in visits and days, adjusting for client and system characteristics. Results: Virtual episodes of care had more visits than in-person episodes between April 1, 2020, and March 31, 2021 (incidence rate ratio [IRR] 1.59, 95% CI 1.38-1.83), and April 1, 2021, and March 31, 2022 (IRR 1.22, 95% CI 1.10-1.35), whereas between April 1, 2022, and March 31, 2023, virtual episodes of care were associated with fewer visits (IRR 0.82, 95% CI 0.74-0.91). Comparable results were seen for treatment duration in days (2020-2021: hazard ratio [HR] 0.64, 95% CI 0.54-0.76; 2021-2022: HR 0.80, 95% CI 0.70-0.90; and 2022-2023: HR 1.10, 95% CI 0.97-1.25). These differences by time period relative to the onset of the COVID-19 pandemic and switch to virtual care were consistent after adjusting for client and system characteristics. Conclusions: To our knowledge, this is the first study to examine the association between virtual or in-person treatment modality and treatment duration. While initially longer than in-person episodes of care, both in numbers of visits and length in days, over time the average length of episodes conducted mainly virtually had attenuated. These findings may be due to growing comfort with the technology or client factors not adequately captured in administrative data. This information can be valuable to clinicians, clients, and their families regarding expected treatment timelines and aid in informing service planning.

Indexed as

COVID-19Mental DisordersMental Health ServicesTelemedicineAdolescentChildFemaleHumansMaleRetrospective StudiesTime Factorschild and adolescent mental healthepisodes of carehealth services researchmental health servicestelemedicinevirtual care

Identifiers

PMID40934463
PMCPMC12425424

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.