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Record W6921903992 · doi:10.11575/prism/37398

Integrating Traditional Healing Methods into Counselling and Psychotherapy with Punjabi and Sikh Individuals

2019· other· en· W6921903992 on OpenAlexvenueaboutno aff

Bibliographic record

VenueLibraries and Cultural Resources (University of Calgary) · 2019
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsPsychological interventionContext (archaeology)Mental healthSubject (documents)Clinical PracticeHealth professionals

Abstract

fetched live from OpenAlex

Evidence-based practice goes well beyond merely matching client disorder to theoretical approach and instead entails the integration of research evidence with clinical expertise in the context of patient characteristics, culture, and preferences. For clients who are less acculturated to Canadian society or for those who still strongly identify with their cultural roots, incorporation of traditional healing methods into counselling and psychotherapy appears highly beneficial. Based on a review of the literature, this paper offers a discussion of frameworks which can guide the incorporation of traditional healing practices into counselling and psychotherapy and outlines model/theory-embedded strategies and interventions that have been reported to be effective with some Punjabi Sikh clients in peer-reviewed published outlets. This information will be useful for professionals who have limited experience with Punjabi Sikh individuals, clinical supervisors overseeing trainees providing mental health services to Punjabi Sikhs, instructors teaching cross/multicultural counselling or psychotherapy classes, and those wishing to further develop or refine existing competence. These proposed strategies and interventions should be subject to research investigations and clinically tested by practitioners to further increase confidence in their application.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.779
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.238
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations0
Published2019
Admission routes2
Has abstractyes

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