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Record W4385738707 · doi:10.3389/fneur.2023.1163094

Train-your-brain program to reduce depression, anxiety, and stress in stroke survivors: a pilot community-based cognitive intervention study

2023· article· en· W4385738707 on OpenAlexaboutno aff
Xiang Cong Tham, Vanessa Jing Xin Phua, Evelyn Kit Yee Ho, Tiebin Yan, Nicole Yun Ching Chen, Lijun Zuo, Claire Thompson, YanHong Dong

Bibliographic record

VenueFrontiers in Neurology · 2023
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
FundersNational Medical Research CouncilMedical Research CouncilSaint Luke's Health System
KeywordsAnxietyCognitionStroke (engine)Psychological interventionPsychologyMoodClinical psychologyPhysical therapyPsychiatryMedicine

Abstract

fetched live from OpenAlex

Introduction: Stroke is a major cause of death and disability worldwide, and it often results in depression, anxiety, stress, and cognitive impairment in survivors. There is a lack of community-based cognitive interventions for stroke survivors. This pilot single trial aimed to assess the feasibility, acceptability, and perceived effectiveness of a community-based cognitive intervention program called Train-Your-Brain (TYB) for stroke survivors and caregivers. The study focused on improvements in emotional and psychological well-being, as well as cognitive functioning. Methods: A quasi-experimental design was used in this study. A total of 48 participants were recruited and assessed using Depression, Anxiety, Stress Scale - 21 items (DASS-21), Montreal Cognitive Assessment (MoCA) and Symbol Digits Modality Test (SDMT) before and after the intervention. The TYB program consisted of nine sessions and was conducted via the Zoom software application. Participants provided feedback on the program, highlighting areas for improvement. Results: Twenty-seven stroke survivors and 21 caregivers completed the program. Participants expressed high satisfaction with the TYB program but recommended avoiding assessments in December and customizing the program for stroke survivors and caregivers. Stroke survivors showed significant improvements in depression and stress scores, while caregivers experienced no significant improvements after the program. While there was a slight improvement in stroke survivors' cognitive scores after the program, it was not statistically significant. Caregivers, however, experienced a significant decline in cognitive scores. Discussion: The TYB program provided group support and validation, resulting in improved mood and reduced stress among stroke survivors. Cultural collectivism played a significant role in fostering group cohesion. However, the program's limited focus on caregivers and timing of assessments during the December holidays may have affected the outcomes. The TYB program demonstrated feasibility and potential effectiveness in alleviating psychological distress and enhancing cognitive function among stroke survivors. Future research should explore long-term effects, larger sample sizes, and non-English-speaking populations to enhance generalizability. Tailored interventions for caregivers are necessary.

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)0.001
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: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.032
GPT teacher head0.339
Teacher spread0.307 · 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 designNon-randomized trial
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

Citations7
Published2023
Admission routes1
Has abstractyes

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