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Home Health Mental Health

Smartphone bans in schools are not associated with better mental wellbeing or reduced screen-time out of school

May 13, 2025
in Mental Health
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Young people are growing up in an increasingly digital world, with 95% of 12- to 15-year-olds in the UK owning a smartphone (Statistica, 2024) and 92% using social media (Ofcom, 2024). Concerns have emerged about the potential effects of excessive smartphones and social media use on young people’s mental health, including links to poorer depression, anxiety, and poorer sleep (Demirci et al., 2015; Odgers & Jensen, 2020; Yang et al., 2020). However, research findings remain mixed and inconsistent. A recent Mental Elf blog by Amanda Sabo and Louise La Sala highlighted that much remains unknown about the relationship between social media and mental health, partly due to how social media use is measured in research.

Recently, more countries have introduced school smartphone bans, with one in four countries implementing laws prohibiting smartphone use during school hours (Unesco, 2023). Despite this, no peer-reviewed studies have examined the impact of such policies on wellbeing, sleep, and physical activity.

This study by Goodyear and colleagues (2025) aimed to compare young people’s mental wellbeing between schools that ban smartphone use and those that allow it. A secondary objective was to assess differences in smartphone and social media use during school hours, over 24 hours and across seven days, and examine how use during these periods related to mental wellbeing.

92% of 12- to 15-year-olds in the UK use at least one social media app or website, indicating just how common this use of technology is among young people.

92% of 12- to 15-year-olds in the UK use at least one social media app or website, indicating just how common this use of technology is among young people.

Methods

A total of 325 schools were initially approached for this study, including 229 restrictive schools (where recreational phone use is prohibited) and 96 permissive schools (where recreational phone use is allowed). Stratified sampling matched the two groups by region, school size and income deprivation index, with no exclusion criteria to minimise selection bias.

Pupils completed an initial online survey to measure mental wellbeing and related outcomes. Mental wellbeing was assessed using the Warwick-Edinburgh Mental Well-Being Scale (WEMWBS; scores range from 14 to 70). Mental wellbeing was reassessed 4-8 weeks later to account for any fluctuations in mental health during that time. Teachers reported on pupils’ classroom behaviour and attainment, and pupils reported on smartphone and social media use via phone data and self-report. However, due to concerns over accuracy of the phone data, only self-reported phone use was used for the main analysis. Participants also wore a device tracking sleep and physical activity.

Linear regression analyses examined the impact of school phone policy type on mental wellbeing, related outcomes, and smartphone, and social media use.

Results

A total of 1,127 participants (aged 12-15) were recruited from 30 schools, including 20 restrictive schools and 10 permissive schools. In restrictive schools, mean age was 13.97 years (SD = 1.07 years), 51.79% of participants were female, and 72.07% were white. In permissive schools, mean age was 14.24 years (SD = 1.14 years), 45.93% of participants were female and 64.62% were white.

Differences in outcomes between schools

The mean score for mental wellbeing across all schools was 47 (SD = 9). No significant differences were found in adolescent mental wellbeing between pupils in restrictive versus permissive schools (restrictive schools: M = 48, SD = 9; permissive schools: M = 46, SD = 9; adjusted mean difference = -0.48, 95% CI [-2.05 to 1.06], p = 0.62). This finding remained consistent even after controlling for variables such as sex, year group, ethnicity, and income deprivation index, and when considering only the first wellbeing assessment.

Additionally, no significant differences were found between groups for self-reported anxiety or depression, as well as teacher-reported disruptiveness and attainment in English and Maths. Even when restricting the analysis to schools where phones were completely inaccessible to pupils during the school day (n = 4) and when controlling for weekend phone use, no significant differences between groups emerged on these outcomes. Collectively, these findings indicate that type of school phone policy (restrictive vs permissive) does not significantly influence pupils’ mental wellbeing or other outcomes like anxiety, depression, or academic performance.

Differences in smartphone use between schools

Regarding phone use, pupils in restrictive schools spent significantly less time on phones (adjusted mean difference = -0.67, 95% CI [-0.92 to -0.43], p <.001>and social media (adjusted mean difference = -0.54, 95% CI [-0.74 to -0.36], p <.001>during school hours compared to pupils in restrictive schools. Overall phone use on weekdays, weekends, and across the week was higher in restrictive schools, although these differences were not statistically significant. Nearly all pupils reported using their phones for more than 1.7 hours on weekdays and more than 2 hours on weekends.

Associations between smartphone use and outcomes

Although school phone policies were not significantly linked to mental wellbeing, across all participants, greater smartphone and social media use was significantly associated with several negative outcomes including:

  • Reduced mental wellbeing
  • Increases in anxiety, depression and problematic social media use
  • Increases in disruptive classroom behaviour
  • Poorer attainment in English and Maths
  • Decreased physical activity
  • Reduced sleep efficiency and sleep duration.
Although school phone policies were not significantly linked to mental wellbeing in young people, greater phone and social media use was associated with several negative outcomes.

Although school phone policies were not significantly linked to mental wellbeing in young people, greater phone and social media use was associated with several negative outcomes.

Conclusions

  • Overall, these findings from Goodyear et al. (2025) suggest that restrictive school phone policies do not improve adolescent mental health, attention, or behaviour compared to permissive school phone policies.
  • Moreover, while such policies reduce phone use during school hours, they do not significantly reduce overall phone or social media use outside of school (e.g., on weekdays and weekends).
  • In this study, it was phone and social media use outside of school that was linked to poorer mental health, including anxiety, depression and sleep disturbances.
  • Therefore, interventions aimed at improving adolescent wellbeing should focus on reducing phone and social media use beyond school hours, rather than solely restricting in-school usage.
The findings from Goodyear et al. (2025) indicate that interventions aiming to improve adolescent wellbeing should focus on reducing phone and social media use beyond school hours, rather than solely restricting in-school usage.

These findings from Goodyear et al. (2025) indicate that interventions aiming to improve adolescent wellbeing should focus on reducing phone and social media use beyond school hours, rather than solely restricting in-school usage.

Strengths and limitations

This study is the first to evaluate the impact of school phone policies on mental health, wellbeing, and other health and education outcomes in a nationally representative UK sample. The use of a nationally representative sample enhances the external validity of the study, meaning that these findings are likely generalisable to all UK schools.

Another key strength of the study is its robust statistical analysis, including sensitivity analyses. Sensitivity analyses are robustness checks that explore how results change when different aspects of the analysis are adjusted. Since all sensitivity analyses returned similar results, this suggests that the findings are consistent and reliable, not influenced by confounding variables or biases, and further increases the credibility of the conclusions. The study was also publicly registered in the International Standard Randomised Controlled Trial Number (ISRCTN) registry, which helps to reduce the risk of bias.

However, several limitations should be noted. First, the study relied on subjective self-reports of phone and social media use, which may be influenced by desirability bias as excessive and/or problematic smartphone and social media use is often labelled as socially undesirable behaviour (Coyne et al., 2023). More robust measures of screen time include tools for tracking smartphone and social media use such as iPhone’s Screen Time and Android’s Digital Wellbeing integrations (Coyne et al., 2023). Although the authors collected phone data, they did not analyse this due to concerns over accuracy.

Furthermore, only the frequency of smartphone and social media use was assessed, rather than the content or type of activities engaged in, which would provide more nuanced insight into the effects of smartphone and social media use on mental wellbeing. For example, different types of phone use (e.g., browsing social media, engaging in online gaming, or general internet use) may have distinct impacts on mental health. Problematic use of social media platforms like Instagram and TikTok have been linked to poorer mental health in adolescents aged 16-18 (Carter et al., 2024). Therefore, future studies should use validated objective measures of screen time such as phone integrations/apps alongside subjective reports and consider the content of phone/social media use.

Another limitation of the study is its cross-sectional design, which makes it difficult to draw conclusions about causality. As data were collected at one timepoint, it is not possible to determine whether school phone policies influence mental wellbeing or whether schools with certain wellbeing profiles are more likely to adopt particular phone policies. Longitudinal research is therefore needed, ideally following students before and after a school phone policy is introduction, to examine changes in mental wellbeing.

Only frequency of phone and social media use was assessed in this study, not the content or type of activities young people were engaging in; this could provide more nuanced insights into the effects on mental wellbeing.

Only frequency of phone and social media use was assessed in this study, not the content or type of activities young people were engaging in, which would provide more nuanced insights into the effects on mental wellbeing.

Implications for practice

This study highlights a lack of evidence supporting school policies that prohibit phone use as effective measures to improve adolescents’ mental, physical, or academic outcomes. However, negative associations were found between increased phone and social media use outside of school and poorer mental health, highlighting the need for broader strategies beyond school policies to improve adolescent wellbeing.

The authors argue that school phone policies should be part of a holistic approach aimed at reducing overall phone and social media use, both in and out of school. This approach could involve teaching digital health behaviours in the PSHE curriculum, such as setting daily app time limits, reducing screen time an hour before bedtime, and keeping phones out of the bedroom at night. Schools could even consider temporary phone bans as educational tools to highlight the benefits of “detox” approaches. Evidence suggests that such bans can reduce problematic usage tendencies (Brailovskaia et al., 2023), offering a potential effective strategy for behavioural change.

This study also opens avenues for future research. One key avenue involves examining the broader mental health impacts of smartphones and social media, including the impacts on social connectedness, loneliness and bullying. In our recent feasibility study as part of the Channel 4 documentary “Swiped”, we did not observe significant declines in social connectedness or increased feelings of loneliness, suggesting temporary abstinence may improve wellbeing without harming social bonds.

Future research should also assess the practicality and impact of interventions that promote healthy digital habits at both school and home. Building on our initial findings from our feasibility study, we are now conducting a follow-up randomised controlled trial to assess the effects of temporary smartphone abstinence (compared to normal use) across different adolescent age groups. Crucially, we are following up participants two months after the ban to assess the longevity of any changes and whether healthier habits, like those mentioned above, are sustained.

In conclusion, efforts to reduce smartphone and social media use should consider both in-school and out-of-school behaviours. Temporary abstinence designs may serve as one tool for behaviour change, but also as a way to raise awareness of digital wellbeing risks. However, a key question moving forward will be to determine whether holistic interventions can produce lasting, positive outcomes for adolescent wellbeing.

Given growing concerns about the impact on phone use on adolescents’, disseminating rapid and rigorous research is essential for informing educational policy.

Given growing concerns about the impact of phone use on adolescents’, conducting and disseminating rapid and rigorous research is essential for informing educational policy.

Statement of interests

I work on studies examining the impact of temporary smartphone and social media abstinence on adolescents’ sleep, mental health, and social and cognitive development.

Links

Primary paper

Goodyear, V. A., Randhawa, A., Adab, P., Al-Janabi, H., Fenton, S., Jones, K., Michail, M., Morrison, B., Patterson, P., Quinlan, J., Sitch, A., Twardochleb, R., Wade, M., & Pallan, M. (2025). School phone policies and their association with mental wellbeing, phone use, and social media use (SMART Schools): A cross-sectional observational study. The Lancet Regional Health – Europe, 101211.

Other references

Brailovskaia, J., Delveaux, J., John, J., Wicker, V., Noveski, A., Kim, S., Schillack, H., & Margraf, J. (2023). Finding the “sweet spot” of smartphone use: Reduction or abstinence to increase well-being and healthy lifestyle?! An experimental intervention study. Journal of Experimental Psychology: Applied, 29(1), 149–161.

Carter, B., Payne, M., Rees, P., Sohn, S. Y., Brown, J., & Kalk, N. J. (2024). A multi-school study in England, to assess problematic smartphone usage and anxiety and depression. Acta Paediatrica, 113(10), 2240–2248.

Coyne, P., Voth, J., & Woodruff, S. J. (2023). A comparison of self-report and objective measurements of smartphone and social media usage. Telematics and Informatics Reports, 10, 100061.

Demirci, K., Akgönül, M., & Akpinar, A. (2015). Relationship of smartphone use severity with sleep quality, depression, and anxiety in university students. Journal of Behavioral Addictions, 4(2), 85-92.

Odgers, C. L., & Jensen, M. R. (2020). Annual Research Review: Adolescent mental health in the digital age: facts, fears, and future directions. Journal of Child Psychology and Psychiatry, 61(3), 336–348.

Ofcom. (2024). Children and Parents: Media Use and Attitudes Report.

Sabo, A., & La Sala, L. (2025). Critical lack of evidence about social media use and youth mental health in clinical populations. The Mental Elf.

Statistica. (2024). UK: Children owning mobile phones by age 2024.

Unesco. (2023). Global education monitoring report 2023: Technology in education—A tool on whose terms?

Yang, J., Fu, X., Liao, X., & Li, Y. (2020). Association of problematic smartphone use with poor sleep quality, depression, and anxiety: A systematic review and meta-analysis. Psychiatry Research, 284, 112686.

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