Smartphone use health outcomes in children and adolescents: A systematic review of behavioral, developmental, and environmental risk pathways

Table 4 Association between smartphone use and mental health outcomes by age group and study design

Ref.	Country	Age group	Sample (n)	Study design	Exposure type	Mental health outcomes	Key effect estimates	Appraisal tool	Primary bias considerations	Overall risk
Meskini et al[30], 2024	Morocco	Middle school adolescents	341	Cross-sectional	Smartphone overuse (SAS)	Depression (HADS); anxiety (HADS)	Depression: r = 0.403 (P < 0.001); anxiety: r = 0.244 (P = 0.013)	JBI	Strengths: Used validated assessment scales (SAS, HADS). Limitations: Geographically restricted to one city (Kenitra); cross-sectional design prevents causal claims	Moderate
Carter et al[31], 2024	United Kingdom	16-18 years	657	Cross-sectional (multi-school)	Problematic smartphone use (SAS); screen time	Moderate depression (PHQ-9); anxiety (GAD-7); insomnia	PSU associated with depression (aOR = 2.96); anxiety (aOR = 2.03); insomnia (aOR = 1.64). Screen time not significant	JBI	Strengths: Multi-school sample (n = 657); adjusted for confounders via multi-level logistic regression	Low to moderate
Mayerhofer et al[32], 2024	Austria	14-20 years	913	Cross-sectional	PSU (SAS-SV); screen time	Depression; anxiety; disordered eating; loneliness	PSU associated with depression (aOR = 1.46); anxiety (aOR = 1.86). Screen time associated with loneliness	JBI	Strengths: Large sample size (n = 913). Limitations: Online survey format may lead to self-selection bias	Moderate
Liu et al[34], 2025	United States	16-18 years	137	Cross-sectional	Smartphone attachment (MPIQ)	Anxiety; depression	Anxiety (adjusted β = 0.26); depression (adjusted β = 0.15)	JBI	Strengths: Used PROMIS pediatric short forms. Limitations: Small sample size (n = 137) and lack of ethnic diversity (79.6% White)	Moderate
Zablotsky et al[33], 2025	United States	12-17 years	Nationally representative	Cross-sectional (NHIS-Teen)	≥ 4 hours/day non-school screen time	Depression; anxiety; low social support	High screen use associated with depression and anxiety symptoms	JBI	Strengths: Large-scale, nationally representative dataset (NHIS-Teen); includes parent-reported covariates	Low
Poulain et al[40], 2025	Germany	10-17 years	1113 (2576 observations)	Repeated cross-sectional (2018-2024)	PSU; > 3 hours/day use	Quality of life	PSU and long duration associated with lower QoL; stronger post-COVID; greater effect in girls	JBI	Strengths: Seven-year time trend analysis (2018-2024) within a dedicated cohort	Low
Selak et al[42], 2025	Europe	10-15 years	284	4-wave longitudinal	Parental smartphone use during interaction	Anger; sadness; subjective well-being	Parental use predicted child anger/sadness → lower well-being (mediation model)	NOS	Strengths: Longitudinal design with four time points; unique predictor (parental phubbing)	Low to moderate
Gath et al[41], 2026	New Zealand	2-8 years (prospective)	6281	Longitudinal cohort	> 1.5-2.5 hours/day early screen exposure	Peer problems; social functioning	> 2.5 hours/day at age 2 associated with increased peer problems at age 8	NOS	Strengths: Very large sample (n = 6281); long-term prospective data from age 2 years to 8 years	Low
El-Sayed Desouky and Abu-Zaid[35], 2020	Saudi Arabia	University students	1513	Cross-sectional	Smartphone addiction (PUMP)	Depression; trait anxiety	Significant positive correlations between addiction and depression/anxiety	JBI	Strengths: Large university sample (n = 1513); used multiple validated tools (PUMP, Taylor, Beck)	Low to moderate
Nikolic et al[36], 2023	Serbia	Medical students	761	Cross-sectional	Smartphone addiction (SAS-SV)	Depression; anxiety; stress	Depression (OR = 2.51); anxiety (OR = 2.04); stress (OR = 1.75)	JBI	Strengths: Multi-city selection; comprehensive analysis (multivariate regression) of independent factors	Low
Daniyal et al[39], 2022	Pakistan	University students	400	Cross-sectional	High vs low cell phone use	Depression; mood disorder; loneliness	Depression (r = 0.430); mood disorder (r = 0.608)	JBI	Strengths: Correlated smartphone use with both physical symptoms (neck/back pain) and mental health	Moderate
Zhu et al[37], 2025	China	Undergraduates	322	Cross-sectional mediation	Smartphone addiction (MPAI)	Depression; anxiety; life satisfaction	Addiction → negative emotions (r = 0.332); depression mediated ↓ life satisfaction	JBI	Strengths: Provides a specific mediation model for life satisfaction	Moderate
Pieh et al[38], 2025	Austria	University students	111	Randomized controlled trial	Screen reduction ≤ 2 hours/day (3 weeks)	Depression (PHQ-9); stress; well-being	Significant reduction in depression (η2 = 0.109); stress (η2 = 0.085); improved well-being	RoB 2	Strengths: RCT design; includes follow-up; intention-to-treat analysis. Limitations: Study was non-blinded	Low to moderate

To evaluate the association between smartphone use and mental health outcomes, the following Risk of Bias assessment has been conducted: Assessments follow the Joanna Briggs Institute checklist for cross-sectional studies, the Newcastle-Ottawa Scale for longitudinal designs, and the Cochrane Risk of Bias for randomized trials. SAS: Zung’s Self-rating Anxiety Scale; HADS: Hospital Anxiety and Depression Scale; JBI: Joanna Briggs Institute; PHQ-9: Patient Health Questionnaire 9; GAD-7: General Anxiety Disorder 7; aOR: Adjusted odds ratio; PSU: Problematic smartphone use; MPIQ: Mobile Phone Involvement Questionnaire; QoL: Quality of life; COVID: Coronavirus disease; NOS: Newcastle-Ottawa Scale; PUMP: Problematic Use of Mobile Phones; OR: Odds ratio; MPAI: Mobile Phone Addiction Index; RoB 2: Cochrane Risk of Bias; RCT: Randomized controlled trial; SAS-SV: Smartphone Addiction Scale-Short Version.