Differences in religious and spiritual practice variables between Canadian counselors and psychologists
Bibliographic record
Abstract
This article investigates whether there are differences in religious and spiritual (R/S) beliefs, attitudes, practices, training, and self-assessed competence between counselors and psychologists in Canada. Researchers surveyed 307 mental health professionals in Canada with two standardized measures (the Assessment of Spirituality and Religious Sentiments Scale and the Duke University Religion Index) and various other questions corresponding to variables investigated or alluded to in past research. We hypothesized that, compared with psychologists, counselors would (a) have stronger personal R/S beliefs, (b) demonstrate more positive attitudes about the appropriateness of using R/S techniques with clients, (c) utilize R/S techniques more in sessions, (d) possess more positive attitudes toward training in this area, and (e) have higher self-assessed competence for working with R/S clients. These hypotheses were generally supported except for the last one: there were no significant differences found between counselors and psychologists in self-assessed competence in working with R/S clients. We compare our findings to those of extant research, particularly the study by Plumb who examined counselors in Canada. On the basis of our findings, we advocate for more systematic cultivation of R/S competence in programs for both counselors and psychologists in Canada.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".