For parents, clinicians, and public health professionals watching adolescent mental health deteriorate in real time, a rigorous mechanistic account of why screen-based childhoods are uniquely damaging — and what biology is actually being harmed — carries urgent practical weight. This review offers exactly that, framing the crisis not as moral panic but as a measurable neuroendocrine and inflammatory phenomenon.
The analysis centers on how attention-optimizing platform algorithms specifically target neurodevelopmental windows when the adolescent prefrontal cortex is still calibrating reward sensitivity and social threat detection. The proposed mechanisms are concrete: chronic digital immersion is linked to dysregulation of the hypothalamic-pituitary-adrenal axis — the body's primary stress-response system — along with circadian disruption and elevated systemic low-grade inflammation, a biomarker increasingly tied to depression and anxiety disorders. Urban environmental stressors compound these effects by further sensitizing the brain's social circuitry, creating what the authors term an evolutionary mismatch that amplifies algorithmic influence on psychological distress.
The shift from play-based to phone-based childhood that Generation Z has experienced represents a natural experiment without historical precedent, and the biological plausibility presented here strengthens the case that observed mental health declines are causal rather than merely correlational. That said, this is a narrative review synthesizing emerging evidence, not a controlled trial — the HPA axis and inflammatory findings draw from heterogeneous study designs, and isolating algorithmic exposure from broader socioeconomic and urban stressors remains methodologically challenging. The proposed "Digital Precision Psychiatry" framework, which incorporates continuous digital phenotyping and just-in-time adaptive interventions, is conceptually promising but largely untested at population scale. Still, the integration of neurobiological mechanisms with public health architecture marks this as a genuinely forward-looking contribution — more than incremental, though not yet paradigm-shifting until intervention data mature.
