Causal Impact of Parental Registration on Teen Outcomes

Meta plans to let parents register and link to their teen’s account. Leaders are concerned about potential negative effects on teens (e.g., well-being, engagement quality). Design a study to estimate the causal effect of parental registration on teen outcomes.

Answer precisely:

1. Define success metrics and guardrails
   • List primary and secondary outcomes, desired direction of change, and minimal detectable effect (MDE) assumptions. Include concrete examples (e.g., time on platform, harmful-content impressions, report/mute rates, session-length volatility, churn).
2. Experimental design
   • Choose the unit of randomization (teen, parent, household, or cluster by social graph) and justify it given potential interference/SUTVA violations (e.g., messages between linked family members, peer spillovers).
   • Propose a practical assignment mechanism (e.g., encouragement design, stepped-wedge rollout) and define exposure.
3. Power and duration
   • Outline sample-size inputs, expected compliance/takeup, and how to handle staggered adoption and late joiners.
4. Measurement and attribution
   • Specify ITT vs. TOT, handling of partial compliance, mislinking, and attrition.
   • Propose CUPED/covariate adjustment to improve precision.
5. Threats to validity and mitigations
   • Identify at least five concrete risks (e.g., selection bias of families who opt in, network interference, policy-induced behavior changes, seasonality/back-to-school, measurement error in well-being proxies). For each, give a mitigation (e.g., household-level randomization, graph clustering, pre-exposure matching, difference-in-differences with teen fixed effects, synthetic controls, instrumental variables, exclusion windows).
6. If an RCT is infeasible, propose a credible quasi-experiment
   • Specify the design (e.g., regression discontinuity at age thresholds, instrument via exogenous invite timing, diff-in-diff before/after with matched controls), identification assumptions, diagnostics, and robustness checks.
7. Ethics and safety
   • Define eligibility filters, safety holdouts, monitoring, and stop conditions for adverse outcomes. Describe how you’d communicate results and make a launch decision under uncertainty.