The Association between Symptoms of Nomophobia, Insomnia and Food Addiction among Young Adults: Findings of an Exploratory Cross-Sectional Survey
Bibliographic record
Abstract
No previous research has examined the association between symptoms of nomophobia and food addiction. Similarly, only a few studies have examined the association between nomophobia and symptoms of insomnia. This exploratory study utilized an online self-administered, structured questionnaire that included: basic sociodemographic and anthropometrics; the nomophobia questionnaire (NMP-Q); the insomnia severity index (ISI); and the Yale Food Addiction Scale (YFAS) in a convenience sample of young adults (18–35 years) in Bahrain (n = 654), 304 (46%) males and 350 (54%) females. Symptoms of severe nomophobia, moderate-severe insomnia, and food addiction were more common among female participants both for each disorder separately and in combination; however, differences did not reach statistical significance. For severe nomophobia, the rate for females was 76 (21.7%) and for males was 57 (18.8%) p = 0.9. For moderate-severe insomnia, the rate for females was 56 (16%) and for males was 36 (11.84%) p = 0.1. For food addiction, the rate for females was 71 (20.29%) and for males was 53 (17.43%) p = 0.3. A statistically significant association was present between nomophobia and insomnia r = 0.60, p < 0.001. No association was found between nomophobia and food addiction. Nomophobia is very common in young adults, particularly in females; nomophobia is associated with insomnia but not with food addiction.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".