“Counselling Made Me a Better Muslim”: The Counselling Experiences of Muslim Clients in Western Canada
Bibliographic record
Abstract
As the Muslim population increases in Canada, there is a growing need for culturally responsive counselling services that consider the values and challenges of this group. This includes being aware of and understanding the diverse cultural identities of Muslims, the Islamic faith, and the impacts of various sociopolitical factors on Muslim clients’ lives. Previous studies have explored the role of spirituality/religion in clients’ lives, and there is some research providing guidelines for practitioners who work with Muslims; however, there is a paucity of research directly examining counselling experiences of Muslim clients, particularly in a Canadian context. Semi-structured interviews were conducted with six participants, 22–30 years old, who identified as practicing Muslims from varying cultural and educational backgrounds. Analysis of the interviews resulted in the development of four overarching categories into which 11 themes and 32 sub-themes were organized: (a) contextual factors and systemic considerations, (b) accessing mental health services, (c) process and outcomes of counselling, and (e) Islam and counselling. Findings and discussion include reflections on Islamophobia and racism, decolonizing mental health and counselling, as well as the need to return to Indigenous Islamic approaches (Islamic psychology). This involves the need for counsellors to advocate for and address systemic challenges faced by Muslim clients and the Muslim community at large. Implications for counsellor education and training as well as for community leaders/organizations are presented.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.039 | 0.009 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".