Bibliography: the online-safety and wellbeing evidence base

The consolidated, annotated sources for the safety pillar; every work is cited in the library. Method notes: how we grade · reading research critically.

Screens and wellbeing (the calibration literature)

• Przybylski, A. K., & Weinstein, N. (2017). The Goldilocks hypothesis. Psychological Science, 28(2). Moderate use ≈ fine; the dose-shape finding — screen time, honestly.
• Orben, A., & Przybylski, A. K. (2019). Nature Human Behaviour, 3. The specification-curve corrective — how small and analysis-dependent the associations are.
• Carter, B., et al. (2016). JAMA Pediatrics, 170(12). Devices and sleep — the displacement corner with real evidence; bedtime is the rule worth having.
• Johannes, N., Vuorre, M., & Przybylski, A. K. (2021). Royal Society Open Science. Telemetry-based gaming-wellbeing data — gaming.
• Ferguson, C. J. (2015). Perspectives on Psychological Science, 10(5). The aggression meta-analytic corrective.

Family mediation and disclosure

• Livingstone, S., Haddon, L., Görzig, A., & Ólafsson, K. (2011). EU Kids Online II and Livingstone, S., et al. (2017). Journal of Communication. Active vs restrictive mediation; the disclosure evidence — talking points, parental controls.
• Przybylski, A. K., & Nash, V. — the parental-controls effectiveness studies. Tools don't substitute for talk.
• Priebe, G., & Svedin, C. G. (2008). Child Abuse & Neglect, 32(12). The disclosure-barrier anchor.

Bullying and bystanders

• Kärnä, A., Salmivalli, C., et al. (2011). Child Development, 82(1). KiVa's randomized evidence — bullying collapses when the audience turns.
• Salmivalli, C. (2010). Aggression and Violent Behavior, 15(2). Participant roles — bullying as an audience phenomenon.
• Latané, B., & Darley, J. M. (1970). The Unresponsive Bystander. Diffusion of responsibility — the mechanism, named and teachable.
• Hinduja, S., & Patchin, J. W. — the Cyberbullying Research Center series. Prevalence, witness ratios, and underreporting.

Safeguarding (adult-facing)

• Wolak, J., Finkelhor, D., Mitchell, K., & Ybarra, M. (2008). American Psychologist, 63(2). The prevalence-calibration corrective — risk real without inflation; the grooming page's foundation.
• Whittle, H., Hamilton-Giachritsis, C., Beech, A., & Collings, G. (2013). Aggression and Violent Behavior, 18(1) and Winters, G. M., & Jeglic, E. L. (2017). Deviant Behavior, 38(6). The grooming-process literature — stages, speed, and the secrecy bright line.
• O'Connell, R. (2003). A typology of child cybersexploitation and online grooming practices. The early typology.

Scams, phishing, manipulation

• Whitty, M. T. — the scam-persuasion research line. Urgency, authority, visceral appeal as stable technique families — the typology's spine.
• Sheng, S., et al. (2007). Anti-Phishing Phil. SOUPS. Game-based phishing training works — the drills' evidence.
• ACCC Targeting Scams reports; eSafety Commissioner guidance. The Australian loss data and practitioner layer.

Gaming monetization

• Zendle, D., & Cairns, P. (2018). PLOS ONE, 13(11) and replications; Zendle, D., et al. (2020). Addiction, 115(9). The loot-box correlations and prevalence — the page that moved regulators.
• Drummond, A., & Sauer, J. D. (2018). Nature Human Behaviour, 2. Structurally akin to gambling.

Regulatory and audit layer

• Human Rights Watch (2022). "How Dare They Peep into My Private Life?" and Internet Safety Labs (2022). K-12 EdTech Safety Benchmark. The measured state of edtech data practices — trackers.
• Online Safety Act 2021 (Cth); Online Safety Amendment (Social Media Minimum Age) Act 2024 (Cth). The Australian statutory layer — reporting, age verification.

Sibling lists: learning science · digital literacy.

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