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Social zeitgeber and sleep loss as risk factors for suicide in American Indian adolescents.

Cindy L EhlersDavid A GilderJessica BenedictDerek N WillsEvie PhillipsCathy GonzalesKatherine J Karriker-JaffeRebecca A Bernert
Published in: Transcultural psychiatry (2024)
American Indians / Alaska Natives (AI/AN) bear a high burden of suicide, the reasons for which are not completely understood, and rates can vary by tribal group and location. This article aims to identify circumstances reported by a community group of American Indian adolescent participants to be associated with their depression and/or suicide. American Indian adolescents (n  =  360) were recruited from contiguous reservations and were assessed with a semi-structured diagnostic interview. Twenty percent of the adolescents reported suicidal thoughts (ideation, plans), an additional 8% reported a history of suicide attempts, and three deaths due to suicide were reported. Suicidal behaviors and major depressive disorder (MDD) co-occurred and were more common among female adolescents. The distressing events that adolescents most often reported were: death in the family, family disruption, peer relationship problems, and school problems. All of these events were significantly associated with suicidal behaviors, however those with suicidal acts were more likely to report death in the family. Those with MDD but no suicidal behaviors were more likely to report disruptions in the family. Disruptions in falling asleep were also associated with suicidal behaviors and having experienced a death in the family. Disruptions in important relationships, particularly through death or divorce, may be interpreted as a loss or disruption in "social zeitgebers" that may in turn disturb biological rhythms, such as sleep, thus potentially increase the risk for MDD and/or suicide. Prevention programs aimed at ameliorating the impact of disruptions in important relationships may potentially reduce suicidal behaviors in AI/AN adolescents.
Keyphrases
  • young adults
  • major depressive disorder
  • depressive symptoms
  • physical activity
  • mental health
  • bipolar disorder
  • healthcare
  • sleep quality
  • machine learning
  • sensitive detection
  • single molecule