Predictors of suicidal ideation in older people: a decision tree analysis

Tonelle E Handley; Sarah A Hiles; Kerry J Inder; Frances J Kay-Lambkin; Brian J Kelly; Terry J Lewin; Mark McEvoy; Roseanne Peel; John R Attia

doi:10.1016/j.jagp.2013.05.009

Predictors of suicidal ideation in older people: a decision tree analysis

Am J Geriatr Psychiatry. 2014 Nov;22(11):1325-35. doi: 10.1016/j.jagp.2013.05.009. Epub 2013 Sep 5.

Authors

Tonelle E Handley¹, Sarah A Hiles², Kerry J Inder³, Frances J Kay-Lambkin⁴, Brian J Kelly³, Terry J Lewin³, Mark McEvoy⁵, Roseanne Peel⁵, John R Attia⁶

Affiliations

¹ Centre for Translational Neuroscience and Mental Health, University of Newcastle, Callaghan, Australia. Electronic address: tonelle.handley@newcastle.edu.au.
² Centre for Translational Neuroscience and Mental Health, University of Newcastle, Callaghan, Australia.
³ Centre for Translational Neuroscience and Mental Health, University of Newcastle, Callaghan, Australia; Hunter Medical Research Institute, Hunter Region Mail Centre, Newcastle, Australia.
⁴ Centre for Translational Neuroscience and Mental Health, University of Newcastle, Callaghan, Australia; National Drug and Alcohol Research Centre, University of New South Wales, Sydney, Australia.
⁵ Centre for Clinical Epidemiology and Biostatistics, University of Newcastle, Newcastle, Australia.
⁶ Hunter Medical Research Institute, Hunter Region Mail Centre, Newcastle, Australia; Centre for Clinical Epidemiology and Biostatistics, University of Newcastle, Newcastle, Australia.

PMID: 24012228
DOI: 10.1016/j.jagp.2013.05.009

Abstract

Objectives: Suicide among older adults is a major public health issue worldwide. Although studies have identified psychological, physical, and social contributors to suicidal thoughts in older adults, few have explored the specific interactions between these factors. This article used a novel statistical approach to explore predictors of suicidal ideation in a community-based sample of older adults.

Design: Prospective cohort study.

Participants and setting: Participants aged 55-85 years were randomly selected from the Hunter Region, a large regional center in New South Wales, Australia.

Measurements: Baseline psychological, physical, and social factors, including psychological distress, physical functioning, and social support, were used to predict suicidal ideation at the 5-year follow-up. Classification and regression tree modeling was used to determine specific risk profiles for participants depending on their individual well-being in each of these key areas.

Results: Psychological distress was the strongest predictor, with 25% of people with high distress reporting suicidal ideation. Within high psychological distress, lower physical functioning significantly increased the likelihood of suicidal ideation, with high distress and low functioning being associated with ideation in 50% of cases. A substantial subgroup reported suicidal ideation in the absence of psychological distress; dissatisfaction with social support was the most important predictor among this group. The performance of the model was high (area under the curve: 0.81).

Conclusions: Decision tree modeling enabled individualized "risk" profiles for suicidal ideation to be determined. Although psychological factors are important for predicting suicidal ideation, both physical and social factors significantly improved the predictive ability of the model. Assessing these factors may enhance identification of older people at risk of suicidal ideation.

Keywords: CART; decision tree; older; physical functioning; psychological distress; social support; suicidal ideation.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Activities of Daily Living / psychology
Aged
Aged, 80 and over
Chronic Disease / psychology
Decision Trees
Female
Humans
Male
Middle Aged
Prospective Studies
Risk Factors
Social Support
Stress, Psychological / complications
Stress, Psychological / psychology
Suicidal Ideation*