Shedding Light on a Forbidden Topic: The Need for Mental Health Professionals to Accommodate the Faith-Based Practices of Immigrant Clients
Bibliographic record
Abstract
Abstract There is much to learn about how immigrants describe their experiences of faith in the counselling context while negotiating meaningful relationships with mental health professionals (MHPs). Here, MHPs refer to individuals in the helping profession who provide services to immigrant clients such as social workers, psychologists, clinicians, practitioners, and counsellors. For the purpose of this presentation, immigrants are viewed as persons relocating to a host country for the purpose of resettlement for a better life (Perruchoud & Redpath-Cross, 2011). In this context, faith describes one’s committed spiritual and religious belief system. Although, it is important to the wellbeing of many immigrant clients, some MHPs struggle to integrate religious faith into the counselling process. According to Plumb (2011), these challenges might be a result of limited training in the area of faith as well as lack of confidence, competence, and comfort related to faith-based practices (Plumb, 2011). These professionals also appear to lack the knowledge and skill set needed to adapt culturally appropriate faith-based interventions in their work with immigrant clients (Dixon, 2015). Many immigrants rely on such faith-based interventions as a source of internal strength and comfort to manage social inequities like racism and discrimination. As such, MHPs have a responsibility to accommodate, recognize, and consider the importance of faith-based practices and interventions when providing counselling services to diverse immigrant client populations. Therefore, the aim of this live virtual presentation session is to engage in reflective discussions with attendees that highlight the role of faith within the therapeutic relationship. The co-presenters will provide useful faith-based interventions for attendees to consider when working with immigrant clients. We will also create a culturally safe environment for attendees to discuss practical ways that they have incorporated faith-based interventions in their counselling practices. Key words: Immigrants, Faith, Faith-Based Interventions, Mental Health Professionals
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 | 0.016 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.014 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.012 | 0.022 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".