The differences between suicide ideators and suicide attempters: simple, complicated, or complex
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Abstract
Background: Given that many people think about suicide and relatively few attempt suicide, researchers have proposed that accurate differentiation between ideators and attempters can aid suicide prevention efforts. Ideators and attempters might differ in three possible ways. First, they might differ in a simple way such that one or a small set of factors are both necessary and sufficient to distinguish between the two groups. Second, ideators and attempters might differ in a complicated way such that a specific combination of a large set of factors is necessary and sufficient for the distinction. Third, complex differences might exist: many possible combinations of a large set of factors are sufficient to distinguish the two groups, but no combination is necessary. This study empirically examined the difference between suicide ideators and attempters. To support a simple difference, individual factors need to produce high classification accuracy. To support complicated differences, one optimized algorithm including a large number of factors needs to produce high accuracy, but removal of factors from the algorithm should substantially reduce the accuracy. To support complex differences, multiple algorithms including a large number of factors need to produce similarly high accuracy, and meanwhile not all algorithms should lead to high accuracy.Methods: Across five samples (total N = 3,869), univariate logistic regressions were conducted to test for simple differences. To test for complicated and complex differences, Machine learning (ML) methods were used to identify the optimized algorithm with all available variables. Subsequently, the same methods were repeated after removing the top five most important or discriminative variables, and a randomly selected 10% subset of variables. Multiple logistic regressions were conducted with all variables.Results: Results were highly consistent across samples. Univariate logistic regressions on average yielded chance-level accuracy. ML algorithms with all variables or with a subset of variables removed showed good accuracy, whereas multiple logistic regressions produced poor to fair accuracy.Conclusions: The study found that differences between suicide ideators and attempters are complex rather than simple or complicated. The findings are consistent with broader psychological evidence and bear important implications for research and clinical practice.
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A wide variety of constellations of stress factors can lead to suicidal behaviour.
“In addition, a wide variety of constellations of stress factors can lead to suicidal behaviour (9)”
From Ambivalence model of suicidality [ABS-model]: an orientation model for the treatment of suicidal individuals (2024) · cites this paper as [9]
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Franklin, J. C. (2019) · BMC Medicine · doi:10.1186/s12916-019-1435-1 · Cited by 28 · see citing works
Self-citationZettle (1995) · doi:10.1002/1097-4679(199503)51:2
VERIFICATION OF FORECASTS EXPRESSED IN TERMS OF PROBABILITY
BRIER, G. W. (1950) · Monthly Weather Review · doi:10.1175/1520-0493(1950)078
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The three-step theory of suicide: Description, evidence, and some useful points of clarification
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Evidence of Inflated Prediction Performance: A Commentary on Machine Learning and Suicide Research
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Moseley, R. L., Gregory, N. J., Smith, P. L., Allison, C. L., Cassidy, S., & Baron‐Cohen, S. (2022) · Molecular Autism · doi:10.1186/s13229-022-00522-5 · Cited by 30 · see citing works
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Psychological primitives can make sense of biopsychosocial factor complexity in psychopathology
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Hedley, D., Batterham, P. J., Bury, S. M., Clapperton, A., Denney, K. E., Dissanayake, C., Fox, P., Frazier, T. W., Gallagher, E., Hayward, S. M., et al. (2022) · Autism · doi:10.1177/13623613221131234 · Cited by 28 · see citing works
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Heckler, W. F., Feijó, L. P., de Carvalho, J. V., & Barbosa, J. L. V. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.120918 · Cited by 19 · see citing works
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Factor Structure and Measurement Invariance of the Suicide Status Form-IV
Oakey‐Frost, N., Divers, R. M., Moscardini, E. H., Pardue-Bourgeois, S., Gerner, J. L., Robinson, A. D., Breaux, E., Crapanzano, K. A., Calamia, M. R., Jobes, D. A., et al. (2023) · Assessment · doi:10.1177/10731911231170150 · Cited by 7 · see citing works
Oh, H. Y., & Nicholson, H. L. (2021) · Journal of Affective Disorders · doi:10.1016/j.jad.2021.02.023 · Cited by 7 · see citing works
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Shoib, S., Siddiqui, M. F., Turan, S., Chandradasa, M., Armiya’u, A. Y., Saeed, F., Berardis, D. D., Islam, S. M. S., & Zaidi, I. (2025) · Preventive Medicine Research & Reviews · doi:10.4103/pmrr.pmrr_121_24 · Cited by 7 · see citing works
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Killian, K. D. (2024) · Contemporary Family Therapy · doi:10.1007/s10591-024-09705-z · Cited by 3 · see citing works
Bryan, C. J., Bozzay, M. L., Tabares, J. V., Daruwala, S. E., Butner, J., & Gorka, S. M. (2024) · Journal of Affective Disorders · doi:10.1016/j.jad.2024.09.119 · Cited by 2 · see citing works
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Multi-environment prediction of suicidal beliefs
Goddard, A. V., Su, A. Y., Yu, X., & Bryan, C. J. (2024) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2024.1425416 · Cited by 1 · see citing works
Jankowsky, K., Steger, D., & Schroeders, U. (2022) · doi:10.31234/osf.io/sa37x · Cited by 1 · see citing works
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Grundlagen der Diagnostik und Therapie
(2024) · Elsevier eBooks · doi:10.1016/b978-3-437-22487-4.16001-0
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Souza, L. D. D. M., Veleda, G. W., & Jansen, K. (2025) · Springer eBooks · doi:10.1007/978-3-032-01297-5_13
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Teismann, T., & Lewitzka, U. (2026) · Springer Reference Medizin · doi:10.1007/978-3-642-45028-0_92-2
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- Authors
- Huang, X., Ribeiro, J. D., & Franklin, J. C.
- Venue
- Journal of Consulting and Clinical Psychology
- Published
- 2020-06
- Volume
- 88
- Issue
- 6
- Pages
- 554-569
- ISSN
- 0022-006X (ISSN-L)
- 1939-2117
- OpenAlex
- W3008517898
- Cited by
- 50
- References
- 109
- Citations by year
- 2026: 5 · 2025: 3 · 2024: 9 · 2023: 5 · 2022: 8 · 2021: 11 · 2020: 8 · 2019: 1
- FWCI
- 3.18
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Consulting and Clinical Psychology (publishedVersion)
- PubMed (publishedVersion)
- PsyArXiv (OSF Preprints) (submittedVersion)
- Funders
- Association for Psychological Science
- Florida State University
- Office of the Assistant Secretary of Defense for Health Affairs (W81XWH-10–2-0181)
- Topics
- Social Sciences › Psychology › Clinical Psychology › Suicide and Self-Harm Studies
- Social Sciences › Psychology › Social Psychology › Mental Health via Writing
- Social Sciences › Sociology and Political Science › Homicide, Infanticide, and Child Abuse
- Keywords
- suicidal ideation, suicide attempts, suicide attempters, machine learning, feature importance, biopsychosocial model, suicide risk prediction
- MeSH terms
- Adolescent, Adult, Female, Humans, Male, Middle Aged, Risk Factors, Suicide, Suicide, Attempted, Young Adult, Suicidal Ideation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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