Phone Ban After a Youth Wellbeing Survey
A school's youth council surveyed 480 students (roll 1,300) about social media and wellbeing. Sixty-two per cent said social media made their body image worse; 48% reported three or more hours daily; 71% said they had seen cyberbullying. The survey was promoted on Instagram, and 82% of respondents were girls. The board is considering banning phones during the school day. A teachers' group cites improved focus; a parents' group cites safety and cost; a local retailer says sales of basic phones rose 12%. The school's research liaison notes the survey is cross-sectional, has no comparison group, and does not measure mental health diagnoses. Academic results have been stable for three years. Cyberbullying reports to the counselling team rose from 11 to 19 in two years. The board wants a decision this term.
1. Assess the quality of the evidence for a phone ban. Identify what the survey can and cannot support.
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The survey has strengths: a large local sample, student voice, and a relevant topic. But it cannot establish that social media causes worse body image. It is self-selected and promoted on Instagram, so it over-represents Instagram users; 82% of respondents were girls, so it does not represent the whole roll. It is cross-sectional and has no comparison group, so it cannot show change over time or causation. It measures perceptions, not clinical diagnoses. The retailer's 12% rise in basic phone sales lacks a baseline and is not evidence about student wellbeing. Stable academic results do not measure mental health. The rise in counselling reports from 11 to 19 is suggestive but could reflect better reporting. Conclusion: the evidence supports further investigation and a monitored trial, not a blanket ban presented as evidence-based.
2. Recommend a decision and an evaluation plan. Justify why your approach is more defensible than an immediate full ban.
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Recommend a trial of phone-free lessons or phone-free intervals rather than a full-day ban, with exemptions for health and caregiving and a clear enforcement policy. A full ban may reduce cyberbullying but also remove a safety tool, create enforcement inequities, and overstate what correlational evidence can support. Evaluation: use a staggered rollout with a comparison group; survey wellbeing before and after; track cyberbullying reports, attendance, academic measures, and student safety perceptions; run focus groups; disaggregate by gender, year level, and equity groups. Consult students, whānau, and counselling staff. Set a two-term review with published criteria. Conclusion: acting is reasonable, but the board should act adaptively and test its theory of change rather than treating a single survey as decisive.
3. Analyse how two stakeholders might use the same evidence to reach different conclusions. Explain what this reveals about evidence and values.
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A teachers' group might cite focus concerns and staff support to argue for a ban; a parents' group might cite safety and cost to argue for exceptions or a narrower policy; the youth council might cite the 62% body-image figure to demand action but oppose a ban as blaming phones rather than platforms. The same survey is being used with different weightings: teachers prioritise classroom attention, parents prioritise safety and affordability, students prioritise voice and access. This reveals that evidence does not interpret itself; values determine which outcomes count and what counts as proportionate. It also shows why disaggregation matters: girls' experiences may differ from boys'. A defensible decision states the values, the evidence threshold, and the review conditions. Conclusion: disagreement is not evidence failure; it is a signal to make value choices explicit.