背景:延迟折扣量化了个人对较小,短期回报大于较大,长期奖励,并代表与许多不良健康结局相关的跨诊断因素。而不是固定的特征,延迟折扣可能会随着时间和地点而变化,受个人和环境因素的影响。连续,实时测量可以为各种健康状况的适应性干预提供信息。
目的:本文的目的是2倍。首先,我们展示并验证了一部小说,短,我们开发了基于生态瞬时评估(EMA)的延迟贴现量表。第二,我们评估该工具重现延迟折扣和健康行为之间已知关联的能力(即,物质使用和渴望)使用基于方便的样本。
方法:参与者(N=97)是成年人(年龄范围18-71岁),在社交媒体上招募。在第一阶段,收集了有关参与者社会人口统计学特征的数据,延迟贴现是通过传统的货币选择问卷(MCQ)和我们的新方法(即,7项时间选择和7项货币选择量表)。在第二阶段(大约6个月后),参与者完成了MCQ,我们新颖的延迟贴现措施,和健康结果问题。检查了我们的方法与传统的MCQ之间的相关性。为了减少规模,迭代选择随机数量的项目,并评估了完整量表和随机量表之间的相关性。然后,我们检查了在第二阶段评估的时间和货币选择量表与参与者认可使用或渴望酒精的评估百分比之间的关联。烟草,或者大麻.
结果:总计,7个个体时间选择项目中的6个与全量表高度相关(r>0.89)。时间选择(r=0.71;P<.001)和货币选择(r=0.66;P<.001)延迟折现率在第1和第2阶段都具有很高的测试重测可靠性。第1阶段MCQ延迟贴现函数与第1阶段(r=0.76;P<.001)和第2阶段(r=0.45;P<.001)的时间选择延迟贴现量表高度相关。一个或多个随机选择的时间选择项目与全量表高度相关(r>0.94)。通过时间选择措施测量的更大的延迟折扣(调整后的平均差=5.89,95%CI1.99-9.79),但不是货币选择量表(调整后平均差=-0.62,95%CI-3.57至2.32),在后续调查中,与过去一小时更多的烟草使用认可有关。
结论:本研究评估了一种基于EMA的新型量表有效可靠地评估延迟折扣的能力。通过在自然环境中通过EMA测量更少的物品和原位的延迟折扣,研究人员可能能够更好地识别出健康状况不佳的风险个体.
BACKGROUND: Delay discounting quantifies an individual\'s preference for smaller, short-term rewards over larger, long-term rewards and represents a transdiagnostic factor associated with numerous adverse health outcomes. Rather than a fixed trait, delay discounting may vary over time and place, influenced by individual and contextual factors. Continuous, real-time measurement could inform adaptive interventions for various health conditions.
OBJECTIVE: The goals of this paper are 2-fold. First, we present and validate a novel, short, ecological momentary assessment (EMA)-based delay discounting scale we developed. Second, we assess this tool\'s ability to reproduce known associations between delay discounting and health behaviors (ie, substance use and craving) using a convenience-based sample.
METHODS: Participants (N=97) were adults (age range 18-71 years), recruited on social media. In phase 1, data were collected on participant sociodemographic characteristics, and delay discounting was evaluated via the traditional Monetary Choice Questionnaire (MCQ) and our novel method (ie, 7-item time-selection and 7-item monetary-selection scales). During phase 2 (approximately 6 months later), participants completed the MCQ, our novel delay discounting measures, and health outcomes questions. The correlations between our method and the traditional MCQ within and across phases were examined. For scale reduction, a random number of items were iteratively selected, and the correlation between the full and random scales was assessed. We then examined the association between our time- and monetary-selection scales assessed during phase 2 and the percentage of assessments that participants endorsed using or craving alcohol, tobacco, or cannabis.
RESULTS: In total, 6 of the 7 individual time-selection items were highly correlated with the full scale (r>0.89). Both time-selection (r=0.71; P<.001) and monetary-selection (r=0.66; P<.001) delay discounting rates had high test-retest reliability across phases 1 and 2. Phase 1 MCQ delay discounting function highly correlated with phase 1 (r=0.76; P<.001) and phase 2 (r=0.45; P<.001) time-selection delay discounting scales. One or more randomly chosen time-selection items were highly correlated with the full scale (r>0.94). Greater delay discounting measured via the time-selection measure (adjusted mean difference=5.89, 95% CI 1.99-9.79), but not the monetary-selection scale (adjusted mean difference=-0.62, 95% CI -3.57 to 2.32), was associated with more past-hour tobacco use endorsement in follow-up surveys.
CONCLUSIONS: This
study evaluated a novel EMA-based scale\'s ability to validly and reliably assess delay discounting. By measuring delay discounting with fewer items and in situ via EMA in natural environments, researchers may be better able to identify individuals at risk for poor health outcomes.