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Record W4396656407 · doi:10.31189/2165-7629-13-s2.383

CALL FOR ACTION: GUIDELINES FOR PHYSICAL ACTIVITY BASED INTERVENTIONS IN ADDICTION

2024· article· en· W4396656407 on OpenAlexaff
Mrs Kirrily Gould, Dr Rhiannon Dowla

Bibliographic record

VenueJournal of Clinical Exercise Physiology · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsRichmond Hospital
Fundersnot available
KeywordsPsychological interventionAddictionCall to actionAction (physics)Physical activityPsychologyMedicinePhysical medicine and rehabilitationPsychiatryBusinessAdvertising

Abstract

fetched live from OpenAlex

With the evidence supporting the extensive benefits of exercise for people experiencing substance use disorders (SUD) rapidly growing, the demand for clinical exercise interventions in SUD services is expanding through Australia. However, at present there are no clear safety considerations or guidelines specific to SUD, leaving exercise physiologists falling to broader guidelines when working with SUD, often using those developed for severe mental illness (SMI). When working with SUD, many considerations differ to those being treated with SMI. This includes differences in the common comorbidities seen in SUD compared to SMI, as well as considerations relating to withdrawal and craving management. Furthermore, the different impacts and considerations of each substance class in relation to exercise needs to be elucidated. Therefore, standardised safety considerations and contraindications need to be developed to allow Exercise Physiologists to provide safe and effective interventions for those in the withdrawal and recovery phase of SUD. This call for action proposes the development of a multidisciplinary informed clinical exercise guideline for safety protocols, considerations and contraindications for physical activity-based interventions within substance use disorder treatment.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.883
Threshold uncertainty score0.339

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
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 head0.384
GPT teacher head0.610
Teacher spread0.226 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2024
Admission routes1
Has abstractyes

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