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Record W3176276915 · doi:10.1177/11782218211026651

Naturalistic Evaluation of an Adjunctive Yoga Program for Women with Substance Use Disorders in Inpatient Treatment: Within-Treatment Effects on Cravings, Self-efficacy, Psychiatric Symptoms, Impulsivity, and Mindfulness

2021· article· en· W3176276915 on OpenAlexafffund
Tashia Petker, Christine Yanke, Liah Rahman, Laurel Whalen, Karen Demaline, Kari Whitelaw, Debbie Bang, Katherine Holshausen, Michael Amlung, James MacKillop

Bibliographic record

VenueSubstance Abuse Research and Treatment · 2021
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsMcMaster UniversityHomewood Research InstituteSt. Joseph’s Healthcare Hamilton
FundersPeter Boris Centre for Addictions Research
KeywordsMindfulnessAdjunctive treatmentImpulsivityPsychological interventionPsychiatryClinical psychologyIntervention (counseling)AddictionPsychologyMedicinePsychotherapist

Abstract

fetched live from OpenAlex

Addiction continues to be a major public health concern, and rates of relapse following currently-available treatments remain high. There is increasing interest in the adjunctive use of mindfulness-based interventions, such as yoga, to improve treatment outcomes. The current study was a preliminary naturalistic investigation of a novel trauma-informed yoga intervention in an inpatient treatment program for women with substance use disorder (SUD). Changes and differences in somatic symptoms, psychiatric symptoms, and psychological mechanisms were evaluated in women receiving treatment-as-usual (n = 36) and treatment-as-usual plus the yoga intervention (n = 42). For both groups, statistically significant within-subjects changes were present for somatic and psychiatric symptoms, cravings, self-efficacy, and multiple facets of impulsivity and mindfulness. Compared to standard treatment alone, participants in the treatment plus yoga condition significantly improved in range of motion and the Lack of Premeditation facet of impulsivity. Although most domains were not selectively affected, these initial within-treatment findings in this naturalistic evaluation suggest some promise for adjunctive yoga and a need for further evaluation, especially using larger samples and longer term follow-up.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.848
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.048
GPT teacher head0.381
Teacher spread0.333 · 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 designOther design
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

Citations19
Published2021
Admission routes2
Has abstractyes

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