Measuring the suicidal mind: The ‘open source’ Suicidality Scale, for adolescents and adults

PLOS ONE RESEARCH ARTICLE Measuring the suicidal mind: The ‘open source’ Suicidality Scale, for adolescents and adults Keith M. Harris ID1,2*, Lu Wang3, Guanglun M. Mu4, Yanxia Lu ID5, Cheryl So6, Wei Zhang7, Jing Ma8, Kefei Liu9, Wei Wang ID10, Melvyn Wei-bin Zhang11, Roger C. Ho12 a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 1 School of Psychology, Charles Sturt University, Bathurst, New South Wales, Australia, 2 School of Psychology, University of Queensland, St Lucia, Queensland, Australia, 3 School of Environmental and Life Sciences, University of Newcastle, Callaghan, New South Wales, Australia, 4 Education Futures, University of South Australia, Adelaide, South Australia, Australia, 5 Department of Medical Psychology and Ethics, School of Basic Medical Sciences, Shandong University, Jinan, Shandong, China, 6 Private Clinician, Hong Kong, 7 School of Medicine and Health Management, Huazhong University of Science and Technology, Hubei, Wuhan, China, 8 School of Politics and Public Administration, Zhengzhou University, Zhengzhou, Henan, China, 9 Yale School of Medicine, Yale University, New Haven, Connecticut, United States of America, 10 Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway, 11 Biomedical Institute for Global Health Research and Technology, National University of Singapore, Singapore, Singapore, 12 Department of Psychological Medicine, National University of Singapore, Singapore, Singapore * OPEN ACCESS Citation: Harris KM, Wang L, Mu GM, Lu Y, So C, Zhang W, et al. (2023) Measuring the suicidal mind: The ‘open source’ Suicidality Scale, for adolescents and adults. PLoS ONE 18(2): e0282009. https://doi.org/10.1371/journal. pone.0282009 Editor: Sarah A. Arias, Brown University Warren Alpert Medical School, UNITED STATES Received: April 19, 2022 Accepted: January 30, 2023 Published: February 23, 2023 Copyright: © 2023 Harris et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: The data is available at OSF. https://osf.io/vjxnq/ DOI 10.17605/OSF.IO/ VJXNQ. Funding: The author(s) received no specific funding for this work. Abstract Clinicians are expected to provide accurate and useful mental health assessments, sometimes in emergency settings. The most urgent challenge may be in calculating suicide risk. Unfortunately, existing instruments often fail to meet requirements. To address this situation, we used a sustainable scale development approach to create a publicly available Suicidality Scale (SS). Following a critical review of current measures, community input, and panel discussions, an international item pool survey included 5,115 English-speaking participants aged 13–82 years. Revisions were tested with two follow-up cross-sectional surveys (Ns = 814 and 626). Pool items and SS versions were critically examined through item response theory, hierarchical cluster, factor and bifactor analyses, resulting in a unidimensional eight-item scale. Psychometric properties were high (loadings > .77; discrimination > 2.2; test-retest r = .87; internal consistency, ω = .96). Invariance checks were satisfied for age, gender, ethnicity, rural/urban residence, first language, self-reported psychiatric diagnosis and suicide attempt history. The SS showed stronger psychometric properties, and significant differences in bivariate associations with depressive symptoms, compared with included suicide measures. The ‘open source’ Suicidality Scale represents a significant step forward in accurate assessment for people aged 13+, and diverse populations. This study provides an example of sustainable scale development utilizing community input, emphasis on strong psychometric evidence from diverse samples, and a free-to-use license allowing instrument revisions. These methods can be used to develop a wide variety of psychosocial instruments that can benefit clinicians, researchers, and the public. Competing interests: The authors have declared that no competing interests exist. PLOS ONE | https://doi.org/10.1371/journal.pone.0282009 February 23, 2023 1 / 28 PLOS ONE The suicidality scale Introduction Suicide resides at the very core of deaths by despair [1, 2]. Due to this importance, there are long-standing recommendations for clinicians to conduct routine suicide risk assessments [SRA; 3, 4]. However, low-validity SRAs can lead to poorly guided clinical decisions. As with other psychosocial constructs, quantifying the latent trait, suicidality, requires high instrument precision with a focus on the fundamental nature of the construct. Despite serious consequences, those selecting and using tests may not be giving sufficient attention to psychological science, particularly psychometrics [5–11]. A lack of focus on psychometric validity, and concerns over psychological science replication [12], has resulted in continued use of popular measures, regardless of demonstrated weaknesses. In response to current assessment practices, a growing number of psychological scientists are advocating for greater emphasis on measurement validity over consistency [e.g., 13, 14]. That may be particularly relevant for SRAs, which have not notably improved since Beck and colleagues published the Scale for Suicide Ideation [SSI; 15] in 1979. To address the urgent need for accurate assessments, this study utilized a sustainable scale development approach for the Creative Commons licensed (free culture) Suicidality Scale (SS) for adolescents, adults, and diverse populations. We hypothesize that a highly valid measure of the latent trait, current suicidality, may be the best candidate for predicting future suicidal distress and suicide. To measure a latent trait, we first need to define it and determine how it can be quantified. Many find the term suicidality useful as it encompasses the totality of the multifaceted suicidal mind. Decades of evidence and theory reveal a complicated dynamic of affective, cognitive, and behavioral attributes that are volatile but can also pose long-term risk [15–17]. We consider suicidality as the extant summation of one’s feelings, thoughts and behaviors related to taking one’s life. Facets which require strong empirical evidence if they are to form a highly accurate measure. Measurement models To understand the current underwhelming state of SRAs we can look to the overwhelming popularity of classical test theory (CTT). There are various measurement models to consider when validating a latent trait instrument. The parallel model stipulates all items are equal in measuring the same trait with the same level of accuracy, identical response sets, and identical error [18, 19]. Similarly, CTT assumes a tau-equivalent model, identical to the parallel model but item errors may vary. The (...truncated)