An innovative model of psychological service delivery in primary healthcare: the Single-Session Intervention
Bibliographic record
Abstract
BACKGROUND: In Canada, the demand for mental health care exceeds the provision of services. This exploratory study aimed to assess the feasibility and impact of a new service delivery model for psychological consultations in primary care settings: the Single-Session Intervention (SSI), inspired by Advanced Access (AA) principles for appointment scheduling. The specific objectives were to examine whether the SSI increases accessibility to psychological consultations, to measure the effects of the intervention on different self-reported measures, and to assess users' consultation experiences. METHODS: Participants were recruited in a University Family Medicine Group in Quebec (Canada), and the SSI was delivered by the on-site psychologist. No referral or formal diagnosis was needed to attend, and participants could promptly obtain an appointment. Participants rated the intensity of their problem, their level of psychological distress and their well-being, before and after the SSI. They also rated their satisfaction with their consultation experience. There was a follow-up 4 to 6 weeks later. RESULTS: Of the N = 69 participants who received SSI, 91% were able to obtain an appointment in less than 7 working days. The number of patients who were able to benefit from a psychological consultation was about 7 times higher after the implementation of SSI compared to previous years, when a traditional model of service delivery was in place. After SSI, participants felt that the intensity of their problem and psychological distress were lower, and that their well-being was increased, as indicated by significant pre-post test clinical measures (p < 0.0001). The observed effects seemed to be sustained at follow-up. Moreover, 51% of participants said that one session was sufficient to help them with their problem. Participants rated SSI as a highly satisfying and helpful consultation experience (92,9% overall satisfaction). CONCLUSIONS: SSI, offered in a timely manner, could be an innovative and cost-effective intervention to provide mental health services on a large scale in primary healthcare. Further research is needed to replicate the results, but these preliminary data seem to indicate that psychological distress may be quickly addressed by SSI, thereby preventing further deteriorations in patients' mental health. TRIAL REGISTRATION: 2019-393, 26 March 2019.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".