The Prevalence of Mild, Moderate, and Severe Nomophobia Symptoms: A Systematic Review, Meta-Analysis, and Meta-Regression
Bibliographic record
Abstract
NOMOPHOBIA, or NO MObile PHone Phobia, refers to a psychological condition in which people fear being disconnected from their mobile phones. The purpose of this review was to establish the prevalence of nomophobia symptoms in youth and young adults according to severity, country, culture, population, measurement tool, and year of data collection. An electronic search of fourteen databases, two digital preservation services, and three content aggregator services was conducted from the inception of each database until 15 September 2021. A total of 52 studies involving 47,399 participants from 20 countries were included in the analyses. The prevalence of nomophobia was defined as the proportion of individuals scoring at or above established cut-offs on validated measures. Based on a random-effects meta-analysis, approximately 20% of individuals showed mild symptoms of nomophobia, 50% showed moderate symptoms, and 20% showed severe symptoms. Our results showed that university students from non-Western cultures are the most likely to suffer severe symptoms. In the year 2021, the prevalence rate of nomophobia increased. The instrument that was best able to detect nomophobia was the nomophobia questionnaire. Most individuals who own mobile phones experience mild or moderate symptoms of nomophobia. Severe symptoms deserve attention from clinicians and research scientists. A valid method of identifying individuals with a severe addiction to their mobile phones will help with timely and effective therapeutic management.
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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 | 0.013 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.034 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".