Login / Signup

Understanding Past Experiences of Suicidal Ideation and Behavior in the Life Narratives of Transgender Older Adults.

Eleni M GaverasVanessa D FabbreBraveheart GillaniSteff Sloan
Published in: Qualitative social work : QSW : research and practice (2021)
Transgender people (collectively referred to here as trans) experience disproportionate rates of suicidal ideation and behavior (plans and attempts) attributed to complex constellations of structural and individual factors. Interpretive methods in suicide research elucidate and contextualize intricate patterns of risk factors and strategies for recovery. The life narratives of trans older adults offer unique insights into past suicidal behavior and recovery after distress has diminished and perspective has been gained. This study aimed to illuminate the lived experiences of suicidal ideation and behavior in the biographical interviews of 14 trans older adults as part of the project To Survive on This Shore ( N =88). Data analysis was conducted using a two-phase narrative analysis. Trans older adults contextualized suicide attempts, plans, ideation, and recovery as navigating impossible to possible paths . Impossible paths were seen as hopelessness in their life direction, often after a significant loss. Possible paths were described as pathways to recovery from crises. Transitions from impossible to possible paths were narrated as a turning point or moment of strength combined with outreach to family, friends, or mental health professionals. Narrative approaches hold the potential to illuminate pathways to well-being among trans persons with lived experiences of suicidal ideation and behavior. For social work practitioners, therapeutic narrative work around past suicidal ideation and behavior with trans older adults holds promise for suicidal prevention by identifying important supportive resources and previously used coping skills in crises.
Keyphrases
  • physical activity
  • mental health
  • depressive symptoms
  • risk factors
  • data analysis
  • primary care
  • health insurance
  • machine learning
  • hepatitis c virus
  • big data
  • social support