Suppr超能文献

当预测相互支持的匹配在实践中几乎不可能时。

When Forecasting Mutually Supportive Matches Will Be Practically Impossible.

机构信息

Department of Psychology, Grand Valley State University.

出版信息

Psychol Sci. 2021 May;32(5):780-788. doi: 10.1177/0956797620984460. Epub 2021 Apr 26.

Abstract

Forecasting which dyads will develop mutually supportive relationships is an important applied and basic research question. Applying psychometric theory to the design of forecasting studies shows that agreement between dyad members about their relationship (relational reciprocity) sets an upper limit for forecasting accuracy by determining the reliability of measurement. To test this, we estimated relational reciprocity in Study 1. Participants in seven samples (six student and one military; = 504; = 766) rated each other on support-related constructs in round-robin designs. Relational reciprocity was very low, undermining reliability. Formulas from psychometric theory predicted that forecasting supportive dyads would be practically impossible. To test this, we had participants in Study 2 complete a measure for matching dyads derived from recent theory. As predicted, supportive matches could not be forecast with acceptable precision. Theoretically, this falsifies some predictions of recent social-support theory. Practically, it remains unclear how to translate basic social-support research into effective interventions.

摘要

预测哪些对偶体会发展出相互支持的关系是一个重要的应用和基础研究问题。将心理测量理论应用于预测研究的设计表明,对偶体成员之间对其关系的一致性(关系互惠性)通过确定测量的可靠性,为预测准确性设定了上限。为了检验这一点,我们在研究 1 中估计了关系互惠性。七个样本(六个学生和一个军事样本;n=504;n=766)的参与者在循环设计中相互评价支持相关结构。关系互惠性非常低,破坏了可靠性。心理测量理论的公式预测,预测支持性对偶体几乎是不可能的。为了检验这一点,我们让研究 2 的参与者完成了一项基于最近理论的匹配对偶体的测量。正如预测的那样,支持性匹配无法以可接受的精度进行预测。从理论上讲,这否定了最近社会支持理论的一些预测。从实践上讲,目前还不清楚如何将基本的社会支持研究转化为有效的干预措施。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验