Exploring the Perspectives of Clients and Clinicians Regarding Digitally Delivered Psychotherapies Utilized for Trauma-Affected Populations
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".