Background

The substance use risk profile scale (SURPS) was developed to assess four personality risk factors: hopelessness, anxiety sensitivity, impulsivity, and sensation seeking. Psychometric validation work—mainly with adolescents and emerging adults—has struggled to support a four-factor simple structure without post-hoc modifications. This study aimed to clarify the factor structure of the SURPS using the most appropriate analytic framework in a sample of adults and investigate its ability to predict various alcohol-related outcomes and motives.

Methods

Adult participants (N = 400; M_age = 32.05, 55% male) completed the SURPS and measures capturing drinking habits and motives. Confirmatory factor analytic (CFA) and exploratory structural equation modeling (ESEM) approaches were used to analyze the dimensionality of the SURPS items, with measurement invariance examined across gender and age. Predictive validity was analyzed using multiple linear regression with observed subscale scores.

Results

Following poor fit of a traditional CFA model with four correlated factors, a four-factor ESEM model (allowing for non-zero item cross-loadings) provided a much stronger fit to the SURPS data. This ESEM model also had scalar invariance across age and gender. Observed subscale scores predicted hypothesized drinking motives. Sensation seeking uniquely predicted hazardous alcohol use while hopelessness, anxiety sensitivity, and sensation seeking uniquely predicted alcohol-related problems.

Conclusion

SURPS model fit was substantially better when using a contemporary ESEM approach. This approach tackles the challenge of CFA being too constraining when faced with the reality of item responses being influenced by correlated clinical constructs.

中文翻译：

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成年期药物使用风险概况量表：探索性结构方程建模方法

背景

物质使用风险概况量表 (SURPS) 旨在评估四种人格风险因素：绝望、焦虑敏感性、冲动和感觉寻求。心理测量验证工作（主要针对青少年和新兴成年人）一直在努力支持四因素简单结构，而无需事后修改。本研究旨在使用成人样本中最合适的分析框架来阐明 SURPS 的因子结构，并调查其预测各种与酒精相关的结果和动机的能力。

方法

成年参与者（N  = 400；M_年龄 = 32.05，55% 男性）完成了 SURPS 并测量了饮酒习惯和动机。使用验证性因素分析 (CFA) 和探索性结构方程模型 (ESEM) 方法来分析 SURPS 项目的维度，并检查不同性别和年龄的测量不变性。使用多元线性回归和观察到的子量表分数来分析预测有效性。

结果

由于传统 CFA 模型与四个相关因子的拟合效果不佳，四因子 ESEM 模型（允许非零项目交叉加载）为 SURPS 数据提供了更强的拟合度。该 ESEM 模型在年龄和性别上也具有标量不变性。观察到的分量表分数预测了假设的饮酒动机。感觉寻求独特地预测了危险的酒精使用，而绝望、焦虑敏感性和感觉寻求独特地预测了与酒精相关的问题。

结论

使用当代 ESEM 方法时，SURPS 模型拟合效果要好得多。这种方法解决了 CFA 在面对项目反应受到相关临床结构影响的现实时过于受限的挑战。