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The Synergistic Effects Of Exercise In Combination With Other Antidepressant Therapies.

2017· article· en· W2619414333 on OpenAlexaffabout
Joanne Gourgouvelis, Bernadette Murphy, Paul Yielder

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2017
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsDepression (economics)AntidepressantMajor depressive disorderPittsburgh Sleep Quality IndexMedicineBeck Depression InventoryAnxietyQuality of life (healthcare)Physical therapyPsychiatryPsychologyInternal medicineInsomniaSleep qualityMood

Abstract

fetched live from OpenAlex

PURPOSE: Major depressive disorder (MDD) is a global public-health concern. Current anti-depressant treatments are far from satisfactory leaving half of patients undertreated. Research has found exercise alone to be an effective treatment for people suffering with mild to moderate depression however its mechanism of action remains unclear. There is also a lack of research investigating the effects of exercise in combination with other conventional antidepressant therapies in people suffering with severe depression such as MDD. The aim of this study is twofold: first, to investigate the effects of an eight week exercise program in combination with antidepressant medication and intensive group therapy in improving depressive symptoms, anxiety and sleep quality; secondly, to identify changes in brain derived neurotrophic factor (BDNF) which is known to be reduced in people suffering with MDD. METHODS: Sixteen sedentary participants were recruited from the Lakeridge Mental Health Day Treatment (LMHDT) program in Oshawa, Ontario, Canada. All participants had a clinical diagnosis of MDD based on DSM-IV criteria and an unstructured clinical interview conducted by hospital psychiatrists. Participants were assigned either to an eight week, supervised, moderate intensity exercise program plus LMHDT group or the LMHDT only group. Depression scores were determined using the Beck Depression Inventory (BDI), sleep quality by the Pittsburgh Sleep Quality Index (PSQI) and plasma BDNF was quantified by ELISA. All variables were measured at baseline and again at eight weeks. RESULTS: Following the eight weeks of combination treatment the exercise group showed a greater decrease in depression scores, F (1,14)=10.18, p=0.007, d=2.04, a greater improvement in sleep quality, F (1,14)=4.81, p=0.046, d=1.28 and a greater increase in plasma BDNF concentration, F(1,14)=12.47, p=0.003, d = 1.99 compared to the non-exercise group. The exercise group also had a greater decrease in anxiety scores although there was no significant difference between the two groups, F (1,14)=0.25, p=0.623, d=.33. CONCLUSIONS: This project has the potential to provide a tool to improve exercise prescription and to guide development of combined treatment approaches in order to optimize treatment outcomes for people suffering with MDD.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.000

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 head0.013
GPT teacher head0.307
Teacher spread0.294 · 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 designObservational
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".

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Citations3
Published2017
Admission routes2
Has abstractyes

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