Exercise as an Alternative Approach for Treating Smartphone Addiction: A Systematic Review and Meta-Analysis of Random Controlled Trials
Bibliographic record
Abstract
Background: With the emergence of electronic products, smartphones have become an indispensable tool in our daily life. On the other hand, smartphone addiction has become a public health issue. To help reduce smartphone addiction, cost-effective interventions such as exercise are encouraged. Purpose: We therefore performed a systematic review and meta-analysis evaluating existing literature on the rehabilitative effects of exercise interventions for individuals with a smartphone addiction. Methods: We searched PubMed, Web of Science, Scopus, CNKI, and Wanfang from inception to September 2019. Nine eligible randomized controlled trials (RCT) were finally included for meta-analysis (SMD represents the magnitude of effect of exercise) and their methodological quality were assessed using the PEDro scale. Results: We found significant positive effects of exercise interventions (Taichi, basketball, badminton, dance, run, and bicycle) on reducing the total score (SMD = −1.30, 95% CI −1.53 to −1.07, p < 0.005, I2 = 62%) of smartphone addiction level and its four subscales (withdrawal symptom: SMD = −1.40, 95% CI −1.73 to −1.07, p < 0.001, I2 = 81%; highlight behavior: SMD = −1.95, 95% CI −2.99 to −1.66, p < 0.001, I2 = 79%; social comfort: SMD = −0.99, 95% CI −1.18 to −0.81, p = 0.27, I2 = 21%; mood change: SMD = −0.50, 95% CI 0.31 to 0.69, p = 0.25, I2 = 25%). Furthermore, we found that individuals with severe addiction level (SMD = −1.19, I2 = 0%, 95%CI:−1.19 to −0.98) benefited more from exercise engagement, as compared to those with mild to moderate addiction levels (SMD = − 0.98, I2 = 50%, 95%CI:−1.31 to −0.66); individuals with smartphone addiction who participated in exercise programs of 12 weeks and above showed significantly greater reduction on the total score (SMD = −1.70, I2 = 31.2%, 95% CI −2.04 to −1.36, p = 0.03), as compared to those who participated in less than 12 weeks of exercise intervention (SMD = −1.18, I2 = 0%, 95% CI−1.35 to −1.02, p < 0.00001). In addition, individuals with smartphone addiction who participated in exercise of closed motor skills showed significantly greater reduction on the total score (SMD = −1.22, I2 = 0 %, 95% CI −1.41 to −1.02, p = 0.56), as compared to those who participated in exercise of open motor skills (SMD = −1.17, I2 = 44%, 95% CI−1.47 to −0.0.87, p = 0.03). Conclusions: Exercise interventions may have positive effects on treating smartphone addiction and longer intervention durations may produce greater intervention effects.
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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 | 0.019 | 0.041 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.026 | 0.046 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".