Yosef Sokol, Sofie Glatt, Marianne Goodman
PASE recovery showed a stable multidimensional structure, with no divergence detected by suicide attempt history or across a three-week interval. Central and bridge features (life worth, meaning, connectedness) are promising candidate intervention targets that need prospective testing. Findings support aftercare that addresses multiple recovery domains rather than a single symptom target.
OBJECTIVES: Personal recovery following a suicidal episode is multifaceted and understudied. Network analysis of the Post Acute Suicidal Episode (PASE), the recovery period that follows an acute episode of suicidal consideration, planning, or attempt, may clarify the multidimensional structure of this recovery and identify clinical intervention points.
METHODS: An online sample with a history of a suicidal episode (N = 940) completed the Recovery Evaluation and Suicide Support Tool (RESST). We applied exploratory graph analysis (EGA) to identify recovery clusters, expected influence and bridge centrality to identify central features, and network comparison tests (NCTs) to compare network structure by suicide attempt history. Dimensional stability was additionally tested across a three-week interval.
RESULTS: EGA identified four stable clusters mirroring the RESST domains, and dimensional structure was consistent across the three-week interval. Central features included life worth, positive self-regard, feeling valued, and connectedness. The strongest bridge items included feeling that life is worth living and having meaning and purpose. NCTs did not identify structural divergence by suicide attempt history.
CONCLUSION: PASE recovery showed a stable multidimensional structure, with no divergence detected by suicide attempt history or across a three-week interval. Central and bridge features (life worth, meaning, connectedness) are promising candidate intervention targets that need prospective testing. Findings support aftercare that addresses multiple recovery domains rather than a single symptom target.