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Record W2980593430 · doi:10.3390/ijerph16203912

Exercise as an Alternative Approach for Treating Smartphone Addiction: A Systematic Review and Meta-Analysis of Random Controlled Trials

2019· review· en· W2980593430 on OpenAlex
Shijie Liu, Tao Xiao, Lin Yang, Paul D. Loprinzi

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2019
Typereview
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsUniversity of CalgaryAlberta Health Services
Fundersnot available
KeywordsMeta-analysisRandomized controlled trialAddictionMoodPsychological interventionPhysical therapyStrictly standardized mean differenceMedicineClinical psychologyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.042
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.331
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0420.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0110.002
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.328
GPT teacher head0.523
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it