MétaCan
Menu
Back to cohort
Record W4387579341 · doi:10.4081/hls.2023.11730

The effect of five activities daily living on improving cognitive function in ischemic stroke patients

2023· article· en· W4387579341 on OpenAlexaboutno aff
Frana Andrianur, Dwi Prihatin Era, Arifin Hidayat, Ismansyah Ismansyah, Diah Setiani

Bibliographic record

VenueHealthcare in Low-resource Settings · 2023
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineActivities of daily livingMontreal Cognitive AssessmentCognitionStroke (engine)Wilcoxon signed-rank testPsychological interventionIschemic strokeHemiparesisPhysical therapyNursing Interventions ClassificationPhysical medicine and rehabilitationCognitive impairmentMann–Whitney U testInternal medicineNursingPsychiatryIschemia

Abstract

fetched live from OpenAlex

This study aimed to assess the effects of five activities of daily living (ADL) interventions on improving cognitive function in patients with ischemic stroke. The study employed a quasi-experimental design with 16 ischemic stroke patients (n=8 per group) in an inpatient ward at a regional hospital in Samarinda, Indonesia. Inclusion criteria were: i) confirmed ischemic stroke via medical records, ii) effective communication, iii) current inpatient status, and iv) hemiparesis. Data collection used an ADL activity instrument sheet, while cognitive function was assessed with the MoCA-Ina screening (maximum score: 30 points). Data analysis included the Wilcoxon test and independent T-Test, with significance set at p<0.05. After the intervention, the intervention group's cognitive function significantly improved (from mean 20.25 ± 2.60 to 25.13 ± 1.81), while the control group changed from mean 17.13 ± 2.10 to 20.50 ± 2.00. The intervention group showed a significant cognitive improvement compared to the control group (p < 0.05). In conclusion, ADL interventions enhance cognitive function in ischemic stroke patients, aiding recovery and serving as an effective hospital nursing intervention.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.180
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.265
Teacher spread0.259 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueHealthcare in Low-resource SettingsSame topicStroke Rehabilitation and RecoveryFrench-language works237,207