Background: Given their modifiable nature, understanding the intrapersonal factors involved in the cessation of non-suicidal self-injury (NSSI) is needed to inform existing therapeutic approaches and explore novel avenues for supporting individuals with NSSI. This study aimed to examine the relative contributions of and interactions among intrapersonal factors (self-concept, emotion regulation, and cognitive flexibility) in distinguishing between ceased and current NSSI. Methods: 202 adults aged 18-71 years ( M = 31.50, SD = 11.23; 74.75% female) were surveyed to compare facets of self-concept, emotion regulation, and cognitive flexibility that contributed most to discriminating those who had ceased NSSI for one year from those who continued. These intrapersonal factors were also explored as potential indirect pathways between identity and NSSI status. Results: Significant differences between ceased and current NSSI groups were observed across all intrapersonal factors, with moderate to large effects. Most differences persisted after accounting for psychological distress. Less identity fragmentation, greater emotional clarity, internal locus of control, self-liking, access to emotion regulation strategies, and impulse control contributed most to discriminating NSSI cessation after accounting for psychological distress. The relationship between lack of identity and NSSI status operated indirectly through lack of emotional clarity and self-liking. Conclusions: Having a coherent sense of identity, emotional clarity, internal locus of control, self-liking, access to emotion regulation strategies, and managing impulsivity relate to NSSI cessation. These modifiable factors denote several promising intervention opportunities and should be considered in the design of NSSI-specific treatments.

In this paper, we use a combination of physiological and behavioral metrics of anxiety to detect changes in anxiety status in clinically anxious participants compared with healthy controls, which is important for intervening in a timely manner for the effective management of anxiety. Specifically, we first operationalize four phases of anxiety and select multimodal-multisensor feature candidates to assess those phases, considering preliminary results obtained in prior research employing a generalized mixed additive model-based analysis. Then, we evaluate the performance of selected features and their combinations in detecting the presence of anxiety phases, using the “Anxiety Phases” dataset. The results demonstrate that unimodal features of skin conductance response rate and mean rigidity of wrists detected all four temporal phases in ~50% of high-anxiety individuals. These two features detected at least three phases in ~90% of high-anxiety individuals. The fusion of these two features with an additional postural feature detected all four temporal phases in 65% of high-anxiety individuals. The multimodal-multisensor combination of these three features represented a 30% improvement compared with the best unimodal predictive feature. Implications of these findings are discussed for developing accurate real-time multimodal-multisensor anxiety management systems for clinical populations.