Challenges and Opportunities of First-Generation Immigrant Therapists in Counselling Indigenous Clients
Bibliographic record
Abstract
Due to historical and ongoing colonialism, Indigenous peoples in Canada experience disproportionately high rates of mental health challenges such as anxiety, depression, and suicide (Ansloos et al., 2019; Yangzom et al., 2023). Prevailing Euro-Western mental healthcare practices undermine Indigenous knowledge systems and continue to act as a form of oppression (Duran, 2019; Fellner et al., 2020; Stewart et al., 2017). In response, there has been increasing awareness and calls for healthcare providers to learn how to effectively work with Indigenous clients (APA, 2017; CPA, 2018; NIMMIWG, 2019; TRC, 2015). At the same time, Canada’s rapid growth in immigration has increased the number of immigrant healthcare providers (Government of Canada, 2022). Existing research has examined barriers that non-Indigenous providers face in their work with Indigenous clients (e.g., limited multicultural competency; Felix, 2023), but less is known about these challenges among immigrant therapists. The present study aimed to address this gap by examining the challenges and opportunities first-generation immigrant therapists face in the context of working with Indigenous clients. Semi-structured interviews with five participants were analyzed using interpretive phenomenological analysis, guided by decolonization, critical race theory, and intersectional feminism. Participants reported personal (e.g., biases) and professional (e.g., lack of training) challenges and opportunities (e.g., relatability) revealed by four Group Experiential Themes: 1) initial perceptions of Indigenous peoples as first-generation immigrants, 2) transformative shifts in understanding and practice, 3) barriers to effectively working with Indigenous clients, and 4) strengths and opportunities as first-generation immigrant therapists. These findings add to ongoing efforts to decolonize mental healthcare by demonstrating the necessity of culturally responsive training, relational accountability, and practices that center Indigenous knowledge within counselling psychology.
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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 | 0.021 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.028 | 0.014 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".