Disturbances in temporality, such as desynchronization with the social environment and its unpredictability, are considered core features of autism with a deep impact on relationships. However, limitations regarding research on this issue include: 1) the dominance of deficit-based medical models of autism, 2) sample size in qualitative research, and 3) the lack of phenomenological anchoring in computational research. To bridge the gap between phenomenological and computational approaches and overcome sample-size limitations, our research integrated three methodologies. Study A: structured phenomenological interviews with autistic individuals using the Transdiagnostic Assessment of Temporal Experience. Study B: computational analysis of an autobiographical corpus of autistic narratives built for this purpose. Study C: a replication of a computational study using narrative flow measures to assess the perceived phenomenological authenticity of autistic autobiographies. Interviews revealed that the most significant differences between the autistic and control groups concerned unpredictability of experience. Computational results mirrored these findings: the temporal lexicon in autistic narratives was significantly more negatively valenced - particularly the "Immediacy & Suddenness" category. Outlier analysis identified terms associated with perceived discontinuity (unpredictably, precipitously, and abruptly) as highly negative. The computational analysis of narrative flow found that the autistic narratives contained within the corpus quantifiably resemble autobiographical stories more than imaginary ones. Overall, the temporal challenges experienced by autistic individuals were shown to primarily concern lived unpredictability and stem from the contents of lived experience, and not from autistic narrative construction.

翻译：时间性紊乱，如与社会环境及其不可预测性的失同步，被认为是自闭症的核心特征，对人际关系具有深远影响。然而，该议题的研究存在以下局限：1）基于缺陷的自闭症医学模型占主导地位，2）质性研究的样本量限制，3）计算研究中缺乏现象学锚定。为弥合现象学与计算方法的差距并克服样本量限制，本研究整合了三种方法。研究A：使用跨诊断时间体验评估对自闭症个体进行结构化现象学访谈。研究B：对为此构建的自闭症叙事自传体语料库进行计算分析。研究C：复制一项使用叙事流测量评估自闭症自传体感知现象学真实性的计算研究。访谈显示，自闭症组与对照组最显著的差异涉及体验的不可预测性。计算结果印证了这些发现：自闭症叙事中的时间词汇具有显著更高的负价——尤其是“即时性与突发性”类别。离群值分析识别出与感知不连续性相关的词汇（unpredictably, precipitously, abruptly）具有高度负价。叙事流的计算分析发现，语料库中的自闭症叙事在量化上更接近自传体故事而非虚构故事。总体而言，自闭症个体经历的时间挑战主要涉及生活不可预测性，并源于生活体验的内容，而非自闭症叙事建构本身。