Arigo Danielle, Torous John
Department of Psychology, Rowan University, Glassboro, NJ, United States.
Department of Family Medicine, Rowan School of Osteopathic Medicine, Stratford, NJ, United States.
JMIR Form Res. 2022 May 2;6(5):e36541. doi: 10.2196/36541.
Digital tools may help to address social deficits in schizophrenia, particularly those that engage social comparison processes (ie, evaluating oneself relative to others). Yet, little is known about social comparison processes in schizophrenia or how best to capture between- versus within-person variability, which is critical to engaging comparisons in digital interventions.
The goals of this pilot study were to (1) better understand affective responses to social comparisons among individuals with schizophrenia, relative to healthy controls, using a validated global self-report measure; and (2) test a new brief, mobile assessment of affective responses to social comparison among individuals with schizophrenia, relative to the full measure. This study was conducted in 2 phases.
We first compared self-reported affective responses to social comparisons between individuals with schizophrenia (n=39) and healthy controls (n=38) using a traditional self-report measure, at 2 time points. We examined the temporal stability in responses and differences between groups. We then evaluated the performance of brief, mobile assessment of comparison responses among individuals with schizophrenia, completed over 12 weeks (n=31).
Individuals with schizophrenia showed greater variability in affective responses to social comparison than controls on traditional measures and completed an average of 7.46 mobile assessments over 12 weeks. Mobile assessments captured within-person variability in affective responses in the natural environment (intraclass correlation coefficients of 0.40-0.60). Average scores for mobile assessments were positively correlated with responses to traditional measures.
Affective responses to social comparison vary both between and within individuals with schizophrenia and capturing this variability via smartphone surveys shows some evidence of feasibility. As affective variability is a potential indicator of poor outcomes among individuals with mental health conditions, in the future, a brief, mobile assessment of affective responses to social comparisons may be useful for screening among individuals with schizophrenia. Further research on this process is needed to identify when specific comparison messaging may be most effective in digital interventions and could suggest new therapeutic targets for illnesses such as schizophrenia.
数字工具可能有助于解决精神分裂症患者的社交缺陷问题，尤其是那些涉及社会比较过程（即相对于他人评价自己）的工具。然而，对于精神分裂症患者的社会比较过程，或者如何最好地捕捉个体间与个体内的变异性，我们知之甚少，而这对于在数字干预中进行比较至关重要。
这项试点研究的目标是：（1）使用经过验证的整体自我报告测量方法，相对于健康对照，更好地了解精神分裂症患者对社会比较的情感反应；（2）相对于完整测量方法，测试一种针对精神分裂症患者对社会比较的情感反应的新的简短移动评估方法。本研究分两个阶段进行。
我们首先使用传统自我报告测量方法，在两个时间点比较了精神分裂症患者（n = 39）和健康对照（n = 38）对社会比较的自我报告情感反应。我们检查了反应的时间稳定性和组间差异。然后，我们评估了在12周内完成的针对精神分裂症患者比较反应的简短移动评估的性能（n = 31）。
在传统测量方法上，精神分裂症患者对社会比较的情感反应比对照组表现出更大的变异性，并且在12周内平均完成了7.46次移动评估。移动评估捕捉到了自然环境中情感反应的个体内变异性（组内相关系数为0.40 - 0.60）。移动评估的平均得分与对传统测量方法的反应呈正相关。
精神分裂症患者个体之间以及个体内部对社会比较的情感反应各不相同，通过智能手机调查捕捉这种变异性显示出一定的可行性证据。由于情感变异性是心理健康状况不佳个体预后不良的潜在指标，未来，针对社会比较的情感反应进行简短的移动评估可能有助于精神分裂症患者的筛查。需要对这一过程进行进一步研究，以确定特定的比较信息在数字干预中何时可能最有效，并可能为精神分裂症等疾病提出新的治疗靶点。
