Nomophobia Symptoms Improved during the Month of Ramadan in Adult Men and Women
Bibliographic record
Abstract
Abstract Introduction: This study was designed to examine the relationship between fasting during Ramadan and symptoms of nomophobia. Methods: Using a before-and-after study design, the nomophobia questionnaire (NMP-Q) was used to measure two occasions of nomophobia symptoms. The first (T1) was 1 week before the start of Ramadan, and the second (T2) was in the 3 rd week of Ramadan 1443 Hijri/2022 Anno Domini. A total of 1867 participants from 16 Arabic countries provided usable responses for the two data sets. Results: The mean age of the participants was 33.5 ± 11.7 years, and 65% were women. The mean NMP-Q scores were 77.49 ± 26.52 and 68.15 ± 25.02 at T1 and T2, respectively. The mean difference was statistically significant ( P < 0.001, Cohen’s d = 2.11). However, the nomophobia scores recorded at either T1 or T2 indicated a moderate level of nomophobia. Linear regression analysis revealed that improvements in nomophobia scores during Ramadan were associated with being younger ( P = 0.015), and higher mobile phone use ( P = 0.021). Conclusion: The findings of this study imply that fasting during Ramadan may reduce nomophobia scores. This finding is corroborated by earlier studies that found that fasting could improve mental health, including lowering anxiety, stress, and depressive symptoms. In addition, engagement in spiritual practices that require no mobile phone, such as prayer and meditation (i.e., distractors), could improve psychological well-being and therefore help reduce the symptoms of nomophobia. This is the first study to investigate nomophobia in an adult population during the Ramadan fasting period. The results suggest that Ramadan fasting was associated with improvements in the symptoms of nomophobia in both men and women.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".