THE EFFECTIVENESS OF FASTING IN MANAGING SEXUAL DESIRE: A BIBLIOMETRIC ANALYSIS FROM AN ISLAMIC PERSPECTIVE (2015–2024)
Bibliographic record
Abstract
This study presents a bibliometric analysis on the topic of the effectiveness of fasting in managing sexual desire, aiming to uncover scholarly trends, key contributors, and research patterns in this niche but increasingly relevant field. The research is motivated by the growing interest in Islamic psycho-spiritual approaches to managing human desires, particularly in response to rising social concerns such as premarital sex and hypersexualized content in digital media. Despite the traditional and spiritual significance of fasting in Islam, little is known about the academic development of this subject from a bibliometric standpoint. The study employed three main keywords: Islamic, fasting, and desires, in order to retrieve data from the Scopus database using advanced title-based search parameters to ensure content relevance. The inclusion criteria focused on English and Arabic language articles published in peer-reviewed journals between 2015 and 2024. The initial dataset was refined using OpenRefine for data cleaning and deduplication, followed by analysis through the Scopus Analyzer and VOSviewer software for mapping co-authorship, keyword co-occurrence, and country collaboration networks. A total of 736 documents were included in the final dataset. The numerical results indicate that the United States, United Kingdom, and Canada are among the most active contributors, while keywords such as "Ramadan," "spirituality," and "self-control" frequently co-occur with fasting-related studies. The visualized networks highlight significant collaborative potential across Islamic and non-Islamic research contexts. In conclusion, the findings demonstrate an emerging scholarly interest in the intersection between Islamic practices and psychological well-being. This study offers valuable insight into how Islamic fasting is conceptualized within academic discourse and identifies gaps and opportunities for future interdisciplinary research, particularly in the domains of Islamic studies, psychology, and health sciences.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | high |
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.040 | 0.027 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".