Evidence map›Paper›PMID 39752192›Full record

ArticleJournal of medical Internet research2025

The Virtual Client Experience Survey for Mental Health and Addictions: Revalidation of a Survey to Measure Client and Family Experiences of Virtual Care.

Allison Crawford, Anne Kirvan, Marcos Sanches, Amanda Gambin, Denise Canso, Eva Serhal

Abstract readValidation Study
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Allison CrawfordCentre for Addiction and Mental Health, Toronto, ON, Canada.ORCID 0000-0002-1320-0664
Anne KirvanCentre for Addiction and Mental Health, Toronto, ON, Canada.ORCID 0000-0002-2168-0848
Marcos SanchesCentre for Addiction and Mental Health, Toronto, ON, Canada.ORCID 0000-0001-9075-1761
Amanda GambinCentre for Addiction and Mental Health, Toronto, ON, Canada.ORCID 0009-0006-7810-8750
Denise CansoCentre for Addiction and Mental Health, Toronto, ON, Canada.ORCID 0009-0008-5997-9862
Eva SerhalCentre for Addiction and Mental Health, Toronto, ON, Canada.ORCID 0000-0003-0451-8694

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe onset of the COVID-19 pandemic precipitated a rapid shift to virtual care in health care settings, inclusive of mental health care. Understanding clients' perspectives on virtual mental health care quality will be critical to informing future policies and practices.

objectiveThis study aimed to outline the process of redesigning and validating the Virtual Client Experience Survey (VCES), which can be used to evaluate client and family experiences of virtual care, specifically virtual mental health and addiction care.

methodsThe VCES was adapted from a previously validated telepsychiatry survey. All items were reviewed and updated, with particular attention to the need to ensure relevance across mental health care sectors and settings. The survey was then revalidated using the 6 domains of health care quality of the Institute of Medicine (IOM) as a guiding framework. These 6 domains include being safe, effective, patient-centered, efficient, timely, and equitable. The VCES was piloted with a convenience sample of clients and family members accessing outpatient care at the Centre for Addiction and Mental Health (CAMH) in Toronto, Ontario, through video or telephone. A confirmatory factor analysis (CFA) was conducted in MPlus and used to test the factorial structures of the VCES, with minor respecification of the model based on modification indices, factor loadings, reliability, and item-total correlation. The respecifications were checked for alignment with the construct definitions and item interpretation. The reliability of the constructs was estimated by the Cronbach α coefficient.

resultsThe survey was completed 181 times. The construct reliability was generally high. Timely was the only subscale with an α lower than 0.7; all others were above 0.8. In all cases, the corrected item-total correlation was higher than 0.3. For the CFA, the model was adjusted after multiple imputations with 20 datasets. The mean chi-square value was 437.5, with df=199 (P<.001). The mean root mean square error of approximation (RMSEA) was 0.08 (SD 0.002), the mean confirmatory fit index (CFI) was 0.987 (SD 0.001), the mean Tucker-Lewis Index (TLI) was 0.985 (SD 0.001), and the mean standardized root mean square residual (SRMR) was 0.04 (SD 0.001).

conclusionsThis study describes the validation of the VCES to evaluate client and family experiences of virtual mental health and addictions care. Given the widespread uptake of virtual care, this survey has broad applicability across settings that provide mental health and addiction care. The VCES can be used to guide targeted quality improvement initiatives across health care quality domains. By effectively addressing challenges as they emerge, it is anticipated that we will continue to move toward hybrid modalities of practice that leverage the strengths and benefits of telephone, video, and in-person care to effectively respond to unique client and family needs and circumstances.

Indexed as

COVID-19Mental Health ServicesTelemedicineAdultFamilyFemaleHumansMaleMiddle AgedOntarioPatient SatisfactionQuality of Health CareReproducibility of ResultsSurveys and Questionnairesclient satisfactiondigital healtheHealthhealth care qualitymental healthtelehealthtelemedicinevirtual careVirtual Client Experience Survey

Identifiers

PMID39752192
PMCPMC11748434

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.