A Social Media Outage Was Associated with a Surge in Nomophobia, and the Magnitude of Change in Nomophobia during the Outage Was Associated with Baseline Insomnia
Bibliographic record
Abstract
We examined the immediate impact of a social media outage on nomophobia and associated symptoms using a longitudinal cohort design. Data were collected at two timepoints, baseline (T1) and during the social media outage of 4 October 2021 (T2). T1 was collected in August–September 2021 as part of the baseline of an ongoing study. The nomophobia questionnaire (NMP-Q), Generalized Anxiety Disorder-7 scale (GAD-7), and Athens insomnia scale (AIS) were administered to 2706 healthy participants from the general Bahraini population (56% females, mean age 33.57 ± 11.65 years). Approximately one month later, during the social media outage, 306 of the study participants were opportunistically assessed using the NMP-Q. At baseline, we found that nomophobia levels strongly correlated positively with both insomnia (p = 0.001) and anxiety symptoms (p = 0.001). This is the first report to examine the impact of a social media outage on nomophobia. Our findings indicate that symptoms of nomophobia increased significantly during a social media outage. Baseline insomnia scores predicted a surge in the global scores of nomophobia symptoms during a social media outage.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".