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Record W4410844435 · doi:10.1111/hdi.13250

Effects of Listening to an Audiobook on Anxiety, Depression, and Quality of Life in Patients Receiving Hemodialysis: A Randomized Controlled Trial

2025· article· en· W4410844435 on OpenAlexvenueno aff
Sevgi Demir Çam, Elanur Yılmaz Karabulutlu

Bibliographic record

VenueHemodialysis International · 2025
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsnot available
Fundersnot available
KeywordsRandomized controlled trialAnxietyMedicineQuality of life (healthcare)HemodialysisDepression (economics)Psychological interventionIntervention (counseling)Hospital Anxiety and Depression ScalePhysical therapyPsychiatryInternal medicineNursing

Abstract

fetched live from OpenAlex

INTRODUCTION: This study aimed to assess the impact of audiobooks on anxiety, depression, and quality of life in patients undergoing hemodialysis. METHODS: We conducted a randomized controlled trial involving 60 patients receiving hemodialysis. The intervention group listened to audiobooks for 4 weeks. Data on anxiety and depression levels were collected using the Hospital Anxiety and Depression Scale, and quality of life was assessed using the SF-36 Quality of Life Scale. RESULTS: Statistically significant reductions in anxiety and depression scores were observed in the intervention group following the 4-week audiobook intervention. Furthermore, the intervention group demonstrated significant improvements in quality of life parameters, specifically in energy, social functioning, physical role limitations, and mental health. The control group showed a significant improvement only in social functioning. CONCLUSIONS: The findings suggest that audiobook interventions can effectively reduce anxiety and depression and enhance certain aspects of quality of life in patients receiving hemodialysis. TRIAL REGISTRATION: Registration number: NCT05272891.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.009
GPT teacher head0.291
Teacher spread0.282 · 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 designRandomized 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

Citations1
Published2025
Admission routes1
Has abstractyes

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