The Effect of Memorizing the Al Quran on Quality of Life in Stroke Patients With Aphasia Motoric Disorders
Bibliographic record
Abstract
BACKGROUND/AIM: The purpose of this study was to determine and analyze the effect of memorizing the Al Quran surah Thaha verse 25–28 on functional communication skills, independence, and quality of life in stroke patients with motoric aphasia disorders. MATERIALS & METHODS: The study was conducted at Ja'far Medika Karanganyar General Hospital, Central Java, Indonesia for approximately 3 months, with a total sample of 102 motor aphasia stroke sufferers, divided into 2 groups (n = 51) as controls receiving medical therapy, (n = 51) intervention group who received medical therapy and were trained to memorizing the Al Quran. The time of the study was carried out for three months starting December 4, 2017 to Maret 21, 2018. Type of quantitative research, using experimental design, simple randomized the pretest-posttest control group design. RESULTS: Based on the results of path analysis that memorizing the Al Quran significantly influences the quality of life in stroke patients with motoric aphasia disorders of (r = 0.735; p = 0.000), while family support is (r = 0.321; p = 0,000), functional communication is (r = 0.017; p = 0.618) and independence by (r = 0.035; p = 0.305). Thus the direct influence of memorizing the Al Quran and family support for the quality of life is better, without having to go through functional communication and the level of independence as mediation. CONCLUSION: Memorizing the Al Quran surah Thaha verse 25–28 is very effective for improving functional communication skills, independence, and quality of life in stroke patients with aphasia motoric disorders.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".