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Exercise for Mood and Anxiety Disorders

2014· book-chapter· en· W4244893003 on OpenAlexaff
Kristin L. Szuhany, Jasper A. J. Smits, Gordon J. G. Asmundson, Michael W. Otto

Bibliographic record

VenueOxford University Press eBooks · 2014
Typebook-chapter
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsAnxietyMoodPsychologyClinical psychologyMood disordersPsychiatry

Abstract

fetched live from OpenAlex

Abstract Mood and anxiety disorders represent the most common psychiatric conditions in the United States. Psychological and pharmacological treatments are the most commonly utilized interventions for these disorders; however, many individuals do not fully respond to these treatments. Exercise interventions represent a novel and efficacious form of alternative treatment for individuals suffering from mood and anxiety disorders. This review discusses the evidence for efficacy of exercise interventions for decreasing mood and anxiety symptoms as well as potential psychological (e.g., distress intolerance, behavioral activation) and physiological (e.g., neurotransmitters, brain-derived neurotrophic factor) mechanisms of action. In addition, we discuss measures to promote exercise adherence and to reduce barriers to exercise. We conclude with a discussion of dissemination of exercise interventions to a broader population.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.029
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0290.012

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 head0.023
GPT teacher head0.231
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations8
Published2014
Admission routes1
Has abstractyes

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