Design and critique teen-parent impact experiment

Meta plans to let parents register and link to their teen’s account. Leaders worry about negative impacts on teens (e.g., well-being, engagement quality). Design a study to estimate the causal effect of parental registration on teens. Answer the following precisely: 1) Define success metrics and guardrails: list primary/secondary outcomes, directionality, and minimal detectable effect 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 under 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 the exposure definition. 3) Power and duration: outline sample sizing inputs, expected compliance/takeup, and how you’d 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 on the same teens 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.