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Record W2999958396 · doi:10.17744/mehc.42.1.06

A Practitioner’s Guide to Breathwork in Clinical Mental Health Counseling

2020· article· en· W2999958396 on OpenAlexaff
Babatunde Aideyan, Gina C. Martin, Eric T. Beeson

Bibliographic record

VenueJournal of Mental Health Counseling · 2020
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsHealth Sciences North
Fundersnot available
KeywordsMental healthPsychological interventionMindfulnessGuided imageryAnxietyClinical psychologyPsychologyPsychotherapistPsychiatryMedicineDistress

Abstract

fetched live from OpenAlex

Breathwork techniques and therapies offer a set of practical interventions for clinical mental health counselors (CMHCs) and are viable methods for integrating physiological sensitivities in treatment by way of the relaxation response. We discuss an organizing framework of breathwork practices and identify three broad categories of breathwork within the field: deep relaxation breathing, mindfulness breathwork, and yogic breathing. Each style is distinct in how it is applied and in the specific respiratory patterns that users are instructed to use. We also aim to elaborate the physiological effects, clinical research outcomes, and applicability of breathwork for treating mental illness. Overall, research findings indicate that breathwork may be efficacious for treating anxiety, depression, and posttraumatic stress disorder. Despite preliminary evidence for breathwork’s efficacy for treating common psychological distress, more research is needed to evaluate its utility for treating a wider range of mental illness. CMHCs are encouraged to incorporate breathwork techniques in their clinical treatment programs but must appraise the value of each technique individually.

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)0.006
metaresearch head score (Gemma)0.001
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.069
GPT teacher head0.462
Teacher spread0.393 · 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
GenreEmpirical

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

Citations18
Published2020
Admission routes1
Has abstractyes

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