跨症状相互作用无法预测四个生态瞬间评估数据集的未来症状状态

Symptom networks have emerged as a popular framework for characterizing the interactions among psychiatric symptoms. Estimated from longitudinal ecological momentary assessment (EMA) recordings, they promise individualized insights into psychopathology and its treatment. Yet whether these networks can be robustly estimated from the short, noisy, and irregularly sampled time series typical of EMA studies remains an open question. We address this through the lens of predictive validity: do estimated cross-symptom connections improve forecasts of future symptom states? In a systematic analysis sp