Inclusion of Relationship and Religion/Spirituality Issues in Mental Health Counseling During the COVID-19 Pandemic: A Survey of Canadian Practitioners
Bibliographic record
Abstract
Relationship (REL) and religion/spirituality (R/S) concerns were prominent during the COVID-19 pandemic but mental health practitioners’ engagement with these issues was unclear. A survey of Canadian mental health practitioners’ ( N = 155) based on a convenience sample in two provinces revealed that overall 66% of practitioners reported engagement with REL and 33% with R/S in their first three counseling sessions. Three latent analysis profiles of engagement emerged: Low ( n = 18), Moderate ( n = 91), and High ( n = 46). Confidence and appraisal of the importance of working with REL and R/S strongly predicted engagement in all three groups. Demographically, High Engagers compared to Moderate/Low Engagers tended to be older with more experience, identify as East Asian and Indigenous, Christian or spiritual, hold doctoral degrees, trained as marriage and family therapists and professional counselors and typically working with couples and families in their service. Practitioners reported the least confidence working with couples relative to parenting, generational and workplace issues. Desire expressed to enhance their skills in REL was 64% and 56% for R/S. Implications for training and leveraging the systemic strengths brought by couple and family therapists to meet the needs of future pandemics are highlighted.
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 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 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) | 0.002 | 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".