Accessibility, safety, and effectiveness of telerehabilitation for public safety personnel with posttraumatic stress injuries: an interpretive description study
Bibliographic record
Abstract
BACKGROUND: Public safety personnel (PSP) are regularly exposed to stress which can result in the development of posttraumatic stress injuries (PTSIs) and leave them unable to work. The COVID-19 pandemic caused a shift in the delivery of PTSI rehabilitation to telerehabilitation (mainly videoconference, but some telephone-based care). METHODS: The present study employed an Interpretive Description design to explore the lived experiences of PSP, clinicians, and decision-makers regarding the safety, accessibility, and effectiveness of PTSI telerehabilitation. We used purposive and convenience sampling techniques, aiming to maximize variation. Interview data were generated using semi-structured interviews and analyzed using an integrated, team-based approach to Braun and Clarke’s reflexive thematic analysis. RESULTS: Our final sample consisted of 34 participants: 12 PSP, 14 clinicians, and eight decision-makers. Three themes were generated: (1) Responding to the uniqueness of individuals and their contexts; (2) Prioritizing different elements of safety at different times; and (3) Facets of care that lead to perceptions of credibility. While telerehabilitation offers accessibility and flexibility, its application necessitates a nuanced, person-centred approach. CONCLUSIONS: Clinicians need to tailor the mode of delivery to PSP and be aware of the potential limitations in observing subtle cues and fostering the therapeutic alliance virtually. Decision-makers should consider policies that support a hybrid model of care, balancing PSP preference and the potential need for in-person interventions to address avoidance and facilitate crucial components of care. Ultimately, for PSP, telerehabilitation presents a valuable option for accessing timely, comfortable care, but open communication with clinicians about preferences and any challenges experienced with virtual modalities is paramount.
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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 | 0.037 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".