In many schools today, smartphones are a constant presence in corridors and classrooms. They have become a central part of young people’s daily lives, and by early adolescence most young people in the UK own a smartphone and use it regularly (Ofcom, 2024). This rise in smartphone use has led to growing concern about how phones might affect young people’s mental health and wellbeing.
In response, many schools have introduced policies restricting smartphone use during the school day in an attempt to reduce classroom distraction and improve learning (Department for Education, 2026). However, evidence about whether restricting phone use in schools actually improves young people’s wellbeing remains limited. A previous Mental Elf blog (Sullivan E, 2025) discussing research by the same team, highlighted that restricting phone use during the school day was not associated with improvements in adolescent mental wellbeing, behaviour, or academic outcomes. The current study builds on those findings by asking a follow-on question: even if restrictive policies don’t improve wellbeing, do they at least represent good value for money for schools?
While most research has focused on whether these policies affect pupils’ wellbeing, less attention has been paid to their costs for schools. Managing smartphone use can take time and resources from teachers and other staff. This study by Perry and colleagues (2026) aimed to examine whether restrictive smartphone policies are cost-effective for secondary schools in England, compared with more flexible phone policies.
Smartphones are now part of everyday school life, but does restricting them actually improve pupil wellbeing?
Methods
This study used data from the SMART Schools project to examine the costs and wellbeing outcomes associated with different smartphone policies in England’s secondary schools. Schools were classified as either restrictive (phone use was not allowed during the school day), or permissive (phones allowed at certain times or places). Schools were selected from different regions and backgrounds to ensure a balanced comparison between the two policy groups.
Data were collected between November 2022 and November 2023. Participants included:
- Pupils aged 12-15
- Teachers
- Senior school staff
The wider SMART Schools study recruited 30 secondary schools, but the economic analysis focused on the 20 schools (13 restrictive, 7 permissive) that had complete cost data available. Pupils completed surveys measuring:
- Quality of life using the Child Health Utility 9D (CHU9D)
- Mental wellbeing using the Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS)
School staff also reported the time spent implementing and enforcing smartphone policies, which researchers used to estimate the costs of each policy.
Results
Data were collected from 1,227 pupils, 54 teachers, and 30 senior leadership staff. The main analysis focused on 815 pupils who had complete data from 20 secondary schools (13 with restrictive policies and 7 with permissive policies). The researchers also repeated the analysis using all 1,227 pupils by estimating missing information to check whether the findings were similar.
Staff time spent managing smartphone policies
Schools reported spending a considerable amount of time managing smartphone use. On average, staff in restrictive schools spent around 102 hours per week implementing and enforcing smartphone policies, compared with 108 hours per week in permissive schools.
Over a full school year (39 weeks), this equated to around 3,963 hours in restrictive schools and 4,198 hours in permissive schools. This means that managing smartphone policies required the equivalent of around three full-time staff members per school, regardless of the type of policy.
Costs of smartphone policies
When staff time was converted into financial costs, restrictive smartphone policies were estimated to cost around £94 less per pupil per school year compared with permissive policies. However, the exact difference in costs may vary between schools.
Pupil wellbeing outcomes
The study also examined differences in pupils’ quality of life and mental wellbeing.
Pupils in restrictive schools had slightly higher quality-adjusted life years than pupils in permissive schools. However, the difference was very small, suggesting there was little meaningful difference in quality of life between the two groups. This indicates that restrictive smartphone policies may not have a noticeable impact on pupils’ overall quality of life.
For mental wellbeing-adjusted life years, pupils in restrictive schools had slightly lower scores than those in permissive schools. However, this difference was very small, suggesting that restrictive smartphone policies were unlikely to have a meaningful impact on pupils’ mental wellbeing.
Cost-effectiveness
When costs and outcomes were considered together, restrictive smartphone policies were estimated to have around a 90% probability of being cost-effective when quality of life was used as the main outcome.
Overall, the findings suggest that restrictive smartphone policies may slightly reduce the costs of managing phone use in schools, but they appear to have little impact on pupils’ wellbeing.
Restrictive school smartphone policies may reduce costs, but show little impact on pupil wellbeing.
Conclusions
- Managing smartphone use requires substantial staff time, equivalent to three full-time members of staff per school, regardless of policy type.
- Restrictive phone policies offer only modest cost savings compared to permissive phone policies.
- There is little evidence that restrictive policies significantly improve pupils’ mental wellbeing and quality of life.
- Overall, the findings raise questions on whether phone policies provide enough economic and welfare benefits to justify their implementation in schools.
Restrictive phone policies alone are unlikely to improve pupil wellbeing, but they may offer real cost savings for schools.
Strengths and limitations
A strength to this study is the use of data from the SMART school study. This study selected a nationally representative sample of 20 secondary schools and adjusted for school and pupil level characteristics, making the results from this study applicable to the wider UK population. This improves the generalisability of the results and increases the confidence that the findings can be applied to a broad range of secondary school settings.
The study uses a strong and reliable way of analysing costs, including methods that take into account uncertainty in the results. Furthermore, it bases its cost estimates on official local authority mean salaries. As these pay rates are standard across the UK, the results are easier to apply to other schools, making conclusions more useful in real world settings.
A key limitation of the study is the method used to collect data on staff time spent implementing phone policies, which forms the primary cost estimate. This data was based on self-reported estimates from senior staff members. There is a potential for recall bias, as staff may inaccurately report the time spent on policy-related activities. The authors also note that relying on a single senior staff member per school to estimate time across multiple staff roles may reduce the precision of the cost estimates, potentially leading to overestimation or underestimation of true costs.
This study uses a representative sample and rigorous analysis, but reliance on staff self-reports introduces uncertainty in the true costs.
Implications for practice
This study suggests that restrictive smartphone policies do not meaningfully improve pupil wellbeing due to differences in wellbeing measures being small and uncertain. Therefore, restrictive policies on phone use in schools should not necessarily be adopted as a first-line strategy for enhancing pupils’ wellbeing. Policymakers could avoid framing such policies as mental health initiatives and instead lead with their moderate cost benefits to schools.
However, these findings suggest a potential organisational benefit, as restrictive policies may reduce the time teachers spend on managing phone-related incidents, and therefore be cost effective. This has implications for staff workload and resource allocation. Therefore, the evidence may still be useful in informing school-level operational decisions rather than wellbeing interventions.
The authors highlight that schools need new policies and practices that actively reduce the amount of staff time consumed by managing phone use during the school day, potentially freeing up resources for more beneficial educational and wellbeing activities.
This study shows that we still need stronger evidence to understand whether smartphone policies in schools actually improve wellbeing or save money. To do this, future research should move beyond one-time comparisons by tracking pupils and teachers before and after policy implementation, allowing outcomes to be compared more accurately over time. We should also design studies where researchers can have more control over the policies being used. If all schools received the same version of a restrictive or permissive policy type, it would be easier for researchers to compare outcomes between schools and have better control over confounding factors that may impact schools individually.
Finally, future research should incorporate broader economic evaluations. While this study suggests potential cost savings through reduced staff time spent on smartphone related incidents in an academic year, there are other costs to consider. For example, the time spent developing policies prior to roll out and the additional costs associated with restricting phone use such as phone pouches for all pupils. Considering these costs would result in a more comprehensive economic evaluation.
Despite no improvements in mental wellbeing, restrictive phone policies might show promise for cost savings.
Statement of interests
Wilfred Bates and Emily Gillings acknowledge the use of ChatGPT (version GPT-5, https://chatgpt.com) to proofread our final draft.
Edited by
Dr Simon Bradstreet.
Links
Primary paper
Perry, S. J., Goodyear, V. A., Pallan, M., Adab, P., Fenton, S., Michail, M., Patterson, P., Randhawa, A., Sitch, A. J., Wade, M., & Al-Janabi, H. (2026). Health economics analysis of restrictive school smartphone policies in secondary schools in England (SMART Schools). BMJ Mental Health, 29(1), e301892.
Other references
Department for Education. (2026). Mobile phones in school. Available at:Â https://www.gov.uk/government/publications/mobile-phones-in-schools/mobile-phones-in-schools
Ofcom. (2024). Children and Parents: Media Use and Attitudes report. Available at:Â https://www.ofcom.org.uk/media-use-and-attitudes/media-habits-children/children-and-parents-media-use-and-attitudes-report-2024
