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Record W4394780486 · doi:10.1101/2024.04.09.24305560

Exploring the Perspectives of Clients and Clinicians Regarding Digitally Delivered Psychotherapies Utilized for Trauma-Affected Populations

2024· preprint· en· W4394780486 on OpenAlexafffundabout
Sidney Yap, Rashell R. Allen, Katherine Bright, Matthew R. Brown, Lisa Burback, Jake Hayward, Olga Winkler, Kristopher Wells, Chelsea Jones, Phillip R. Sevigny, Megan McElheran, Keith Zukiwski, Andrew J. Greenshaw, Suzette Brémault‐Phillips

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsMental Health Research CanadaMacEwan UniversityUniversity of Alberta
FundersCanadian Institutes of Health ResearchGovernment of Alberta
KeywordsFocus groupMental healthPsychological interventionMedicinePublic healthPsychologyNursingPsychiatry

Abstract

fetched live from OpenAlex

Abstract During the COVID-19 pandemic, many clinical sites shifted towards digital delivery of mental health services. However, there is still much to learn regarding using digitally delivered psychotherapies in trauma-affected populations, including military members, Veterans, and public safety personnel. This study examined perceptions of psychotherapies utilized for trauma-maffected populations, as reported by Canadian military members, Veterans, and public safety personnel who completed such interventions and mental health clinicians who provided them. Specifically, we explored the imposed shift to digital health use, what changed with this rapid shift, what needs, problems, and solutions arose, and important future considerations associated with delivering trauma-focused and adjunct treatments digitally. Quantitative survey data were collected from 11 Canadian patients (military members, Veterans, and public safety personnel with post-traumatic stress injury) and 12 Canadian mental health clinicians. Survey questions were adapted from the Alberta Quality Matrix for Health (AQMH) and Unified Theory of Acceptance and Use of Technology (UTAUT) model. As a follow-up, participants were invited to participate in either a semi-structured qualitative interview or focus group to further explore their perspectives on digitally delivered trauma-focused and adjunct therapies. Four clients and 19 clinician participants participated in an interview or focus group. In survey and interview/focus group results, patient and clinician participants reported that digitally delivered trauma and adjunct therapies offered similar treatment effectiveness as in-person delivery while also improving treatment access. Participants indicated unique advantages of digital delivery, including the increased accessibility of treatment, cost effectiveness, and more efficient use of resources. However, some participants struggled with using digital platforms and felt less comfortable working in a digital environment. Further research with a larger, more diverse population is required to corroborate our results and identify other avenues in which psychotherapies utilized for trauma-affected populations can be engaged with and improved upon. Author Summary Many mental health service sites were faced with rapid and unexpected shifts towards digital delivery of mental health services to comply with mandated physical distancing restrictions put in place during the COVID-19 pandemic. There is still much to learn regarding using digitally delivered psychotherapies in trauma-affected populations, including military members, Veterans, and public safety personnel. This study examined perceptions of Canadian military members, Veterans, and public safety personnel who completed, and mental health clinicians who provided, psychotherapies utilized for trauma-affected populations. This exploration aims to increase our understanding of the strengths and limitations of this mode of delivery. Patient and clinician participants reported that psychotherapies for trauma-affected populations offered similar treatment effectiveness as in-person delivery, while also improving treatment access. Participants indicated unique advantages of digital delivery, including increased accessibility of treatment, cost effectiveness, and more efficient use of resources. Some participants reported struggling with the use of, and felt less comfortable working on, digital platforms. Further research with larger, more diverse populations is required to confirm our results and identify other avenues for using, and improving on, psychotherapies for trauma-affected populations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.146

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.006
Scholarly communication0.0060.002
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.219
GPT teacher head0.421
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes3
Has abstractyes

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