Evaluating the Impact of Australia's Social Media Minimum Age Policy: A Study Protocol
تقييم تأثير سياسة الحد الأدنى لسن استخدام وسائل التواصل الاجتماعي في أستراليا: بروتوكول دراسة
Journal: BMJ open
University: Australian Institute of Family Studies (AIFS)
Study Type: cohort
Evidence Level: preliminary
Participants: 4121
Published:
⚠️ Warning: This is a preliminary study (animal/cell) and has not been proven in humans.
30-Second Summary
This study protocol outlines a mixed-methods evaluation of Australia's Social Media Minimum Age Act, which restricts social media access for individuals under 16. The planned research aims to assess the policy's impact on the digital practices, psychosocial well-being, and family dynamics of 4,121 young people and their parents.
1-Minute Summary
Australia implemented a world-first policy in December 2025 requiring platforms to prevent users under 16 from maintaining social media accounts. This protocol describes a longitudinal study involving 4,121 young people and their caregivers to evaluate the outcomes of this legislation. Data collection methods include five-wave surveys, smartphone tracking, linked administrative data, and qualitative interviews. The planned analyses will investigate adherence to the restrictions and potential changes in psychosocial well-being, distress, and community attitudes.
3-Minute Summary
This analysis is based exclusively on the provided PubMed abstract regarding a study protocol for evaluating the Online Safety Amendment (Social Media Minimum Age) Act 2024 in Australia. It is imperative to state clearly at the outset that full-text verification is required to comprehensively understand the study's complete methodological framework, specific survey instruments, and detailed inclusion or exclusion criteria. Furthermore, because this document is a study protocol, it contains no results, findings, or conclusions regarding the actual impact of the legislation. It solely outlines the planned methodology for future data collection and analysis. The abstract describes the context of the Online Safety Amendment (Social Media Minimum Age) Act 2024 (SMMA), which was implemented in Australia on December 10, 2025. The authors characterize this policy as a world-first age-restriction for social media, mandating that age-restricted platforms take reasonable steps to prevent individuals under the age of 16 from creating or maintaining accounts. According to the preliminary estimates cited in the abstract, approximately 1,194,000 young people are expected to be affected by the deactivation of their social media accounts. In response to the enactment of the SMMA, the researchers have designed a study to systematically examine the outcomes of this policy on young people, their parents, and their broader families. The core objective of the outlined study protocol is to evaluate both the implementation and the outcomes of the SMMA. The researchers have identified five primary domains of interest for their evaluation. First, they aim to assess young people's adherence to the new regulations. The abstract explicitly defines 'adherence' in this context as the participant's experience of account removal or deactivation, as well as any attempts they might make to bypass or circumvent these digital restrictions. The authors note that this term is used for brevity and acknowledge that neither children nor parents are subject to legal obligations under the SMMA itself. Second, the study plans to evaluate the impact of the SMMA on the digital practices of young people. Third, it will investigate the effects on their physical, psychological, and social well-being. Fourth, the evaluation will look at the impact on their families. Finally, the study aims to capture community attitudes and dynamics surrounding the policy implementation. To achieve these evaluative goals, the researchers are employing a comprehensive mixed-methods approach. The planned sample size is substantial, involving 4,121 young people aged 10 to 16 years, alongside their parents or caregivers. The data collection strategy is multifaceted, incorporating both quantitative and qualitative streams. The quantitative component relies heavily on a five-wave longitudinal survey administered to both parents and children. Longitudinal designs of this nature are generally intended to capture changes over time, which is critical for evaluating pre- and post-implementation effects. In addition to self-reported survey data, the protocol includes opt-in passive smartphone tracking. This method is likely intended to gather objective data on device usage to complement the subjective survey responses. Furthermore, the researchers plan to utilize administrative linked and non-linked health and educational data, which could provide broader contextual information regarding the participants' well-being and academic trajectories. The qualitative component of the mixed-methods design involves interviews and focus groups. These methods are intended to capture the lived experiences, nuances, and complex realities of navigating the new digital landscape that quantitative surveys might miss. The abstract notes that qualitative data will be analyzed using a combination of thematic analysis and structured coding approaches. This will involve an iterative analysis of open-ended survey responses, as well as the in-depth data gathered from the interviews and focus groups, to identify key themes and patterns. The planned statistical analysis for the quantitative data is highly detailed. The researchers intend to conduct descriptive analyses, including frequencies, average values, percentages, factor analysis, and reliability of scales for each of the five survey waves. To understand both between-person and within-person changes before and after the SMMA implementation, they propose using various analytical approaches, such as logistic regressions, multi-level modelling, and random-intercept cross-lagged panel models. For causal inference analyses—a challenging endeavor in observational policy evaluation—the primary strategy will be targeted maximum likelihood estimation (TMLE). This approach will be used specifically to evaluate the effect of young people's adherence to the SMMA on key outcomes like psychosocial well-being and distress. Ethical considerations are prominently featured in the abstract. The study has received ethical approval from the Australian Institute of Family Studies (AIFS) Human Research Ethics Committee (application approval number 2025/06). It also complies with the National Statement on Ethical Conduct in Human Research and the Australian Institute of Aboriginal and Torres Strait Islander Studies (AIATSIS) Code of Ethics for Aboriginal and Torres Strait Islander Research. Informed consent is a strict requirement; all participants must provide consent at the baseline survey and in each subsequent wave, and only those who consent are eligible to participate. In summary, this abstract outlines a rigorous, large-scale, mixed-methods protocol designed to evaluate a novel social media age-restriction policy in Australia. However, as a protocol, it provides no empirical data or findings. The researchers state that future findings will inform national policy oversight, contribute to international debates, and support evidence-informed decision-making. Full-text verification remains absolutely necessary to evaluate the specific survey instruments, the precise mechanics of the passive smartphone tracking, the exact nature of the administrative data linkage, and the detailed statistical analysis plan.
Full Analysis
This comprehensive analysis is strictly constrained to the provided PubMed abstract detailing a study protocol for the evaluation of the Online Safety Amendment (Social Media Minimum Age) Act 2024 in Australia. It is of paramount importance to recognize that this document represents a study protocol, not a completed empirical study. Consequently, there are absolutely no findings, results, or conclusions regarding the efficacy, safety, or impact of the legislation reported in this abstract. The abstract serves merely as a blueprint for future research activities. Full-text verification is strictly required to assess the complete methodological rigor, the exact wording of the survey instruments, the technical specifications of the passive smartphone tracking, and the granular details of the planned statistical models. ### 1. Introduction to the Protocol and Policy Context The abstract introduces a research protocol designed to evaluate a significant legislative change in Australia: the Online Safety Amendment (Social Media Minimum Age) Act 2024 (referred to as SMMA). According to the abstract, this legislation was implemented on December 10, 2025. The authors describe this policy as a 'world-first social media age-restriction.' The core mandate of the SMMA, as outlined in the text, requires age-restricted social media platforms to take 'reasonable steps' to prevent Australian citizens and residents under the age of 16 from creating new accounts or keeping existing ones. The scale of this policy intervention is substantial. The abstract cites preliminary estimates suggesting that approximately 1,194,000 young people are expected to be directly affected by the deactivation of their social media accounts. Given the unprecedented nature of this legislation and the large population it impacts, the researchers have developed this protocol to systematically examine the outcomes of the SMMA as it is enacted. The target populations for this evaluation include the young people directly affected by the ban, their parents or caregivers, and their broader families. ### 2. Study Population and Sampling Framework The planned methodology is described as a mixed-methods approach, which integrates both quantitative and qualitative data collection strategies to provide a holistic evaluation of the policy's impact. The planned sample size for this evaluation is notably large, targeting 4,121 young people. The age range for inclusion in the study is specified as 10 to 16 years. Importantly, the study design requires the participation of these young people alongside their parents or caregivers, creating a dyadic data structure that allows researchers to analyze the impacts from multiple familial perspectives. While the abstract provides the total target sample size (4,121) and the age range (10-16 years), it does not detail the sampling methodology. Full-text verification is required to understand how these participants will be recruited, whether the sample is intended to be nationally representative, and what specific inclusion and exclusion criteria will be applied beyond age and the requirement for parental consent. Understanding the sampling framework is critical for assessing the external validity and generalizability of the future findings. ### 3. Quantitative Data Collection Strategies The quantitative arm of the proposed mixed-methods design is highly complex and relies on several distinct data sources. Firstly, the cornerstone of the quantitative data collection is a 'five-wave longitudinal parent-child survey.' Longitudinal designs are essential for evaluating policy changes, as they allow researchers to establish baseline measurements prior to or immediately following the implementation and track changes over time. A five-wave design suggests a robust attempt to capture both immediate and longer-term trajectories in the participants' behaviors and well-being. However, the abstract does not specify the time intervals between these five waves, which requires full-text verification. Secondly, the protocol includes 'opt-in passive smartphone tracking.' This is a significant methodological inclusion. While surveys rely on self-reported data—which is subject to recall bias and social desirability bias—passive tracking can provide objective, continuous data on actual device and application usage. The abstract explicitly notes that this tracking is 'opt-in,' which introduces a critical methodological limitation: selection bias. Participants who agree to have their smartphones passively tracked may differ systematically from those who decline. Full-text verification is needed to understand exactly what metrics will be tracked (e.g., screen time, specific app usage, frequency of unlocking the device) and how the researchers plan to address the potential opt-in bias. Thirdly, the researchers plan to utilize 'administrative linked and non-linked health and educational data.' This suggests an intention to look beyond self-reported outcomes and examine objective markers of health and academic performance. The integration of administrative data can significantly strengthen observational research, but it also introduces complex data linkage challenges and privacy considerations. The abstract does not specify which specific health or educational databases will be accessed. ### 4. Qualitative Data Collection Strategies To complement the quantitative data, the protocol outlines a qualitative research component involving 'qualitative interviews and focus groups.' In mixed-methods research, qualitative data is often used to explore the 'how' and 'why' behind the quantitative trends. In the context of the SMMA, interviews and focus groups could provide deep insights into how young people and families are negotiating the new rules, the emotional impact of account deactivation, and the specific strategies used to adapt to the restrictions. The abstract notes that qualitative data will be analyzed using 'a combination of thematic analysis and structured coding approaches.' This will involve the 'iterative analysis of open-ended survey responses and in-depth qualitative data from interviews, focus groups and related tasks.' The goal of this analysis is to identify 'key themes, patterns and lived experiences.' Full-text verification is necessary to review the planned interview guides, the theoretical framework guiding the thematic analysis, and the specific procedures for ensuring qualitative rigor (e.g., inter-coder reliability, member checking). ### 5. Outcomes of Interest and the Definition of Adherence The protocol outlines five primary domains that the evaluation aims to assess: (a) Young people's adherence to the SMMA. (b) The impact on their digital practices. (c) The impact on their physical, psychological, and social well-being. (d) The impact on their families. (e) Community attitudes and dynamics. The abstract provides a specific and crucial definition for the first domain, 'adherence.' The authors define adherence as 'a participant's experience of account removal/deactivation and any attempts to bypass or circumvent those restrictions.' This is a pragmatic definition that acknowledges the reality of digital policy enforcement: young people may attempt to use virtual private networks (VPNs), create fake accounts with altered birthdates, or use alternative devices to bypass the restrictions. The authors explicitly state that the term 'adherence' is used 'solely for brevity, and we acknowledge that children and parents are not subject to legal obligations under the SMMA.' This clarification is important, as it frames the evaluation around behavioral responses to platform-level restrictions rather than legal compliance by the individuals. ### 6. Planned Analytical and Statistical Approaches The abstract details a sophisticated statistical analysis plan for the quantitative data. The researchers will begin with descriptive analyses, examining 'frequencies, average values, percentages, factor analysis and reliability of scales for each survey wave.' This is standard practice for validating survey instruments and understanding the basic distribution of the data. To analyze changes over time, the protocol lists several advanced modeling techniques: 'logistic regressions, multi-level modelling, random-intercept cross-lagged panel model.' Multi-level modeling is appropriate given the nested nature of the data (e.g., repeated measures nested within individuals, individuals nested within families). The random-intercept cross-lagged panel model (RI-CLPM) is a particularly strong choice for this type of longitudinal data, as it allows researchers to separate within-person variance (how an individual changes relative to their own baseline) from between-person variance (how individuals differ from one another), providing a more accurate understanding of directional effects over time. For causal inference—attempting to determine if the SMMA *caused* changes in well-being, rather than just being correlated with them—the researchers state they will employ 'targeted maximum likelihood estimation (TMLE)' as their primary strategy. TMLE is an advanced, double-robust statistical method used in observational studies to estimate causal effects while minimizing bias from confounding variables. The abstract specifies that TMLE will be used to evaluate the effect of young people's adherence to the SMMA on key outcomes such as 'psychosocial well-being and distress.' Full-text verification is required to understand the specific covariates that will be included in the TMLE models to adjust for confounding. ### 7. Ethical Considerations and Dissemination Given the involvement of minors and the collection of sensitive data (including passive smartphone tracking and health records), ethical oversight is paramount. The abstract confirms that the study received ethical approval from the Australian Institute of Family Studies (AIFS) Human Research Ethics Committee (application approval number 2025/06). Furthermore, it complies with the National Statement on Ethical Conduct in Human Research and the Australian Institute of Aboriginal and Torres Strait Islander Studies (AIATSIS) Code of Ethics for Aboriginal and Torres Strait Islander Research. The inclusion of the AIATSIS code suggests that the study population will include Indigenous Australians, necessitating culturally safe research practices. The abstract emphasizes that 'All participants provided informed consent at the beginning of the baseline survey and in each subsequent wave. Only parents and young people who provided their consent were eligible to take part in the study.' Finally, the abstract outlines the dissemination plan. The researchers intend for the findings to 'inform national policy oversight and implementation in Australia, contribute empirical evidence to international debates and inform other countries considering similar age-based regulation of social media.' Results will be shared through 'public-facing reports, peer-reviewed publications and stakeholder engagement activities.' ### 8. Limitations and the Need for Full-Text Verification The most significant limitation of this abstract is inherent to its nature: it is a study protocol. It contains zero data, zero results, and zero conclusions regarding the impact of the Social Media Minimum Age Act. It only describes what the researchers *plan* to do. Furthermore, while the proposed methodology is robust, longitudinal observational studies face inherent challenges, including participant attrition over the five waves, self-reporting bias in the surveys, and selection bias in the opt-in passive tracking component. The measurement of 'adherence,' particularly regarding attempts to bypass restrictions, will likely be challenging to capture accurately. Full-text verification is absolutely essential to critically evaluate this protocol. The full text is required to review the specific validated scales that will be used to measure 'psychosocial well-being and distress,' the exact technical parameters of the passive smartphone tracking, the detailed sampling and recruitment strategy, the specific administrative databases targeted for linkage, and the comprehensive statistical analysis plan including the handling of missing data and the specification of the TMLE models.Health Implications
This abstract outlines a study protocol; therefore, it establishes a planned methodological framework for future research, but it does not establish any health outcomes, results, or conclusions. It describes how researchers intend to evaluate the implementation of Australia's Online Safety Amendment (Social Media Minimum Age) Act 2024 using a mixed-methods, longitudinal design involving 4,121 young people and their parents. The abstract establishes the researchers' intent to measure adherence (including bypass attempts), digital practices, family dynamics, and physical, psychological, and social well-being over five survey waves, supplemented by passive smartphone tracking and administrative data. It does not establish whether the social media age restriction improves, worsens, or has no effect on youth mental health or well-being. It does not establish the prevalence of social media use or the success rate of the age verification measures. The abstract solely confirms that a structured evaluation is underway. Full-text verification is required to review the specific survey instruments, data linkage protocols, and detailed statistical analysis plans proposed by the research team.
Key Findings
- The protocol outlines a five-wave longitudinal evaluation involving 4,121 young people aged 10 to 16 and their parents.
- The planned study will assess the impact of social media age restrictions on psychosocial well-being, digital practices, and family dynamics.