Department of Psychology.
J Consult Clin Psychol. 2020 Jun;88(6):554-569. doi: 10.1037/ccp0000498. Epub 2020 Feb 27.
Suicide ideators and suicide attempters might differ in 3 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 2 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 may be sufficient to distinguish the 2 groups, but no combination may be necessary. This study empirically examined these possibilities.
Across 5 samples (total = 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 variables. Subsequently, the same methods were repeated after removing the top 5 most important or discriminative variables, and a randomly selected 10% subset of variables. Multiple logistic regressions were conducted with all variables.
Results were consistent across samples. Univariate logistic regressions on average yielded chance-level accuracy. ML algorithms with all variables showed good accuracy; substantial deviation from the optimized algorithms through the removal of variables did not result in significantly poorer performance. Multiple logistic regressions produced poor to fair accuracy.
Differences between suicide ideators and attempters are complex. Findings suggest that their differences may be better understood on a psychological primitive level than a biopsychosocial factor level. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
自杀意念者和自杀未遂者可能在以下 3 个方面存在差异。首先,他们可能存在简单的差异,即一个或一小部分因素既是必要条件,也是区分两者的充分条件。其次,意念者和未遂者可能存在复杂的差异,即特定的一组合适的多种因素组合对于区分两者是必要和充分的。第三,可能存在复杂的差异:大量因素的许多可能组合可能足以区分两者,但没有任何组合是必要的。本研究通过实证检验了这些可能性。
在 5 个样本(总计=3869)中,进行单变量逻辑回归以检验简单差异。为了检验复杂和复杂的差异,使用机器学习(ML)方法来识别具有所有变量的最优算法。随后,在去除前 5 个最重要或最具区分性的变量以及随机选择的 10%变量子集后,重复相同的方法,并对所有变量进行多项逻辑回归。
结果在样本间具有一致性。单变量逻辑回归的平均准确率为机会水平。使用所有变量的 ML 算法具有良好的准确性;通过去除变量,与优化算法有较大偏差并不会导致性能显著下降。多项逻辑回归产生了较差到一般的准确性。
自杀意念者和未遂者之间的差异是复杂的。研究结果表明,它们的差异可能在心理原始层面上比在生物心理社会因素层面上更容易理解。(PsycInfo 数据库记录(c)2020 APA,保留所有权利)。