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Record W4388274335 · doi:10.36472/msd.v10i10.1064

Holistic Approach In Stroke Patients: A Clinical Trial

2023· article· en· W4388274335 on OpenAlexaboutno aff
Abdulvahap Kaya, Ali Timuçin Atayoğlu

Bibliographic record

VenueMedical Science and Discovery · 2023
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsCoping (psychology)CognitionMontreal Cognitive AssessmentPersonalityMedicineClinical psychologyStroke (engine)Physical therapyPsychologyPsychiatryCognitive impairment

Abstract

fetched live from OpenAlex

Objective: This study aimed to explore the holistic relationship between personality types, coping attitudes, physical functioning, and cognitive levels in individuals diagnosed with stroke. Material and Methods: The research employed a single-group design and included 25 stroke patients. The participants, comprising 7 females and 12 males with a mean age of 54.211±8.979 years, underwent a comprehensive assessment. Physical function was assessed using the Berg Balance Scale and Timed Up and Go Tests, and cognitive levels were measured with the Montreal Cognitive Assessment Scale, coping strategies were evaluated through the COPE-R Coping Attitudes Evaluation Scale, and personality types were determined using the Enneagram Scale. Results: A significant correlation was identified between the Montreal Cognitive Assessment, Timed Up and Go, and Berg Balance Scales (p<0.05). However, no significant correlation was observed between COPE-R Coping Attitudes and Enneagram scales (p=0.503). Conclusion: This study underscores the interplay between cognitive and physical functioning in stroke survivors, highlighting the potential impact of cognitive levels on physical capabilities. Surprisingly, coping attitudes and personality types did not significantly influence cognitive or physical function.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score0.413

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.132
GPT teacher head0.497
Teacher spread0.365 · 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 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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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