分析社交平台用户抑郁症状表达差异，发现注意力缺陷与自闭症群体语言特征不同。
Population-Level Profiling of DSM-5 Depressive Symptoms Among Self-Reported ADHD and ASD Users on Twitter: An Exploratory Study Using Advanced NLP and Statistical Analysis
- 用先进NLP模型识别推文中的九类抑郁症状
- 注意力缺陷者更常提认知、睡眠和疲劳问题
- 结果具可复现性，但不支持个体层面诊断差异
背景：抑郁症常与注意缺陷多动障碍（ADHD）及自闭症谱系障碍（ASD）共病，但两群体在抑郁症状表达上的总体差异尚未充分探索。目标：分析社交媒体用户中ADHD与ASD群体在表达DSM-5抑郁症状时的差异，并检验不同抑郁内容过滤阈值下的稳健性。方法：分析792名自报诊断用户的1,282,437条推文（622例ADHD；170例ASD）。先通过零样本自然语言推理（zero-shot NLI）筛选抑郁相关推文，再使用在ReDSM5数据集微调的MentalRoBERTa模型分类为九类DSM-5症状。每位用户症状得分均值中心化后，采用带交叉验证的L1正则逻辑回归区分两组，结合皮尔逊相关分析症状共现模式，并通过自助法测试五种过滤阈值下的稳健性。结果：MentalRoBERTa在独立测试集上取得0.901的宏平均F1，优于原始ReDSM5基准。分类性能稳定但有限（交叉验证ROC-AUC 0.645–0.653）。ADHD群体更倾向报告认知问题、睡眠障碍、食欲改变和疲劳；而ASD群体更常提及自杀意念和快感缺失。两组症状共现结构高度相似，无任何症状对达到显著特异性标准。结论：在不同过滤阈值下，两群体抑郁语言表达差异具一致性，反映可复现性而非临床有效性。研究结果为探索性，不支持个体水平的表型差异。
原文摘要 · Abstract (English)
Background: Depression frequently co-occurs with ADHD and autism spectrum disorder (ASD), but population-level differences in symptom expression between these groups remain underexplored. Objective: We examined whether social media users with ADHD and ASD differ in how they express DSM-5 depressive symptoms in their tweets, and whether differences persist across varying levels of depressive-content filtering. Methods: We analysed 1,282,437 tweets from 792 users (622 ADHD; 170 ASD) with self-reported diagnoses on Twitter. Tweets were pre-filtered for depressive relevance using zero-shot NLI, then classified into nine DSM-5 symptoms using MentalRoBERTa fine-tuned on ReDSM5. Profiles were mean-centered per user. We applied L1-penalised logistic regression with cross-validation to distinguish ADHD from ASD users, complemented by Pearson correlations for symptom co-occurrence, and tested robustness across five filtering thresholds using bootstrapping. Results: MentalRoBERTa achieved macro-F1 of 0.901 on a held-out set, outperforming the original ReDSM5 benchmark. ADHD vs ASD classification yielded stable but modest performance (cross-validated ROC-AUC 0.645-0.653). Cognitive issues, sleep issues, appetite change, and fatigue leaned toward ADHD, while suicidal ideation and anhedonia leaned toward ASD. A largely shared symptom co-occurrence structure emerged between groups; no pair met our criterion for a robust disorder-specific difference. Conclusions: Population-level differences in depression-related language between ADHD and ASD social media users were consistently observed across thresholds, reflecting reproducibility rather than clinical validity. Findings are exploratory and do not establish differing phenomenology at the individual level.
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