{"title":"Supplemental Material for Development and Validation of the Responsible Drinking Inventory","authors":"","doi":"10.1037/pas0001428.supp","DOIUrl":"https://doi.org/10.1037/pas0001428.supp","url":null,"abstract":"","PeriodicalId":20770,"journal":{"name":"Psychological Assessment","volume":"65 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145397019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Supplemental Material for Measuring Executive Function in Preschoolers: Is a Single Assessment Occasion Sufficient?","authors":"","doi":"10.1037/pas0001419.supp","DOIUrl":"https://doi.org/10.1037/pas0001419.supp","url":null,"abstract":"","PeriodicalId":20770,"journal":{"name":"Psychological Assessment","volume":"31 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145255203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Experience sampling methodology has been widely used to study the links between emotion dynamics and mental health. Most studies rely on time-contingent sampling schemes, with momentary questionnaires being sent at prespecified times, usually multiple hours apart. The present study investigated the added value of episode-contingent (EC) burst designs, which may shed further light on emotion dynamics by triggering a series of closely timed beeps upon detecting emotional episodes. Using data from three EC studies (N = 185), we investigated the effectiveness and feasibility of two types of EC designs: signal-based (EC-Signal; bursts initiated when emotion ratings exceed thresholds) and event-based (EC-Event; bursts initiated by participants). Both EC designs are effective in capturing emotional episodes, but the quantity and intensity of the episodes varied depending on which of these two designs was used and the valence of the episodes. Regarding feasibility, compared to EC-Event, EC-Signal typically led to higher participant burden and lower compliance for both regular and follow-up beeps. Moreover, compliance tended to decrease over time and burden tended to increase for both EC-Signal and time-contingent, but not for EC-Event. In conclusion, both EC approaches showed feasibility but have distinct advantages and drawbacks. To select the best approach, researchers should carefully balance these trade-offs to maximize utility within specific research contexts. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
经验抽样法被广泛用于研究情绪动态与心理健康之间的关系。大多数研究依赖于随时间变化的抽样方案，在预先规定的时间（通常相隔数小时）发送临时问卷。本研究调查了偶发事件（EC）突发设计的附加价值，它可以通过在检测到情绪事件时触发一系列紧密定时的哔哔声来进一步阐明情绪动力学。利用三个EC研究（N = 185）的数据，我们调查了两种类型EC设计的有效性和可行性：基于信号的（EC- signal，当情绪评级超过阈值时引发的爆发）和基于事件的（EC- event，由参与者引发的爆发）。两种EC设计都能有效捕捉情绪发作，但发作的数量和强度因使用哪一种设计和发作的效价而异。在可行性方面，与EC-Event相比，EC-Signal通常会导致参与者负担增加，对常规和后续蜂鸣声的依从性降低。此外，随着时间的推移，依从性倾向于降低，EC-Signal和随时间变化的负担倾向于增加，但EC-Event没有。综上所述，两种EC方法均具有可行性，但各有优缺点。为了选择最好的方法，研究人员应该仔细平衡这些权衡，以在特定的研究背景下最大化效用。（PsycInfo Database Record (c) 2025 APA，版权所有）。
{"title":"Evaluating the feasibility of episode-contingent experience sampling burst designs.","authors":"Yuanyuan Ji,Marieke J Schreuder,Sigert Ariens,Egon Dejonckheere,Eva Ceulemans","doi":"10.1037/pas0001404","DOIUrl":"https://doi.org/10.1037/pas0001404","url":null,"abstract":"Experience sampling methodology has been widely used to study the links between emotion dynamics and mental health. Most studies rely on time-contingent sampling schemes, with momentary questionnaires being sent at prespecified times, usually multiple hours apart. The present study investigated the added value of episode-contingent (EC) burst designs, which may shed further light on emotion dynamics by triggering a series of closely timed beeps upon detecting emotional episodes. Using data from three EC studies (N = 185), we investigated the effectiveness and feasibility of two types of EC designs: signal-based (EC-Signal; bursts initiated when emotion ratings exceed thresholds) and event-based (EC-Event; bursts initiated by participants). Both EC designs are effective in capturing emotional episodes, but the quantity and intensity of the episodes varied depending on which of these two designs was used and the valence of the episodes. Regarding feasibility, compared to EC-Event, EC-Signal typically led to higher participant burden and lower compliance for both regular and follow-up beeps. Moreover, compliance tended to decrease over time and burden tended to increase for both EC-Signal and time-contingent, but not for EC-Event. In conclusion, both EC approaches showed feasibility but have distinct advantages and drawbacks. To select the best approach, researchers should carefully balance these trade-offs to maximize utility within specific research contexts. (PsycInfo Database Record (c) 2025 APA, all rights reserved).","PeriodicalId":20770,"journal":{"name":"Psychological Assessment","volume":"2 1","pages":"520-534"},"PeriodicalIF":3.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145351502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Intensive longitudinal designs are being used with increased frequency in clinical psychology research and assessment, due to their ability to assess within-person, dynamic processes in naturalistic contexts in near real time. However, the complexity inherent in these designs means there is a need for more empirical data to guide decision making for specific research or clinical practice applications. As such, this special issue presents 15 studies (published across two associated journal issues) with innovative findings and methods that can guide clinical psychology researchers and practitioners as they design, conduct, interpret, and analyze intensive longitudinal designs. The articles cover topics including considerations for power/sample size planning and predicting attrition; practices for optimal sampling designs and methods; insights from participants' experiences in intensive longitudinal design studies; and poststudy procedures regarding assessment of data quality, psychometrics, and conducting analyses. Each study is briefly reviewed, and implications for clinical research and practice are discussed. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
密集纵向设计在临床心理学研究和评估中使用的频率越来越高，因为它们能够在接近实时的自然环境中评估人的动态过程。然而，这些设计固有的复杂性意味着需要更多的经验数据来指导具体研究或临床实践应用的决策。因此，本期特刊介绍了15项研究（发表在两期相关期刊上），这些研究具有创新的发现和方法，可以指导临床心理学研究人员和从业人员设计、实施、解释和分析密集的纵向设计。文章涵盖的主题包括功率/样本量规划和预测损耗的考虑；最佳抽样设计和方法的实践；参与者在密集纵向设计研究中的经验见解；以及关于数据质量评估、心理测量学和进行分析的研究后程序。本文简要回顾了每项研究，并讨论了临床研究和实践的意义。（PsycInfo Database Record (c) 2025 APA，版权所有）。
{"title":"Optimizing intensive longitudinal designs for clinical psychology research and assessment.","authors":"Kristin Naragon-Gainey,Kasey Stanton","doi":"10.1037/pas0001424","DOIUrl":"https://doi.org/10.1037/pas0001424","url":null,"abstract":"Intensive longitudinal designs are being used with increased frequency in clinical psychology research and assessment, due to their ability to assess within-person, dynamic processes in naturalistic contexts in near real time. However, the complexity inherent in these designs means there is a need for more empirical data to guide decision making for specific research or clinical practice applications. As such, this special issue presents 15 studies (published across two associated journal issues) with innovative findings and methods that can guide clinical psychology researchers and practitioners as they design, conduct, interpret, and analyze intensive longitudinal designs. The articles cover topics including considerations for power/sample size planning and predicting attrition; practices for optimal sampling designs and methods; insights from participants' experiences in intensive longitudinal design studies; and poststudy procedures regarding assessment of data quality, psychometrics, and conducting analyses. Each study is briefly reviewed, and implications for clinical research and practice are discussed. (PsycInfo Database Record (c) 2025 APA, all rights reserved).","PeriodicalId":20770,"journal":{"name":"Psychological Assessment","volume":"52 1","pages":"461-465"},"PeriodicalIF":3.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145351501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fridtjof Petersen,Laura F Bringmann,Dimitris Rizopoulos
Intensive longitudinal data from ecological momentary assessment (EMA) are widely used in clinical research but often suffer from dropout, leading to reduced statistical power, invalid results, and poor treatment outcomes. Predicting dropout could help with its prevention. While existing methods utilize baseline covariates, few studies account for the temporal dynamics of EMA data or identify the exact timing of dropout. Joint models (JM) enable simultaneous modeling of longitudinal processes and time-to-event data, offering dynamic predictions. However, conventional JMs assume limited measurement occasions and do not account for the autocorrelation inherent in EMA data. We extended the standard JM by incorporating an autoregressive submodel, capturing temporal dependencies in EMA measurements. We validated our approach through simulation studies, demonstrating good parameter recovery across different missingness mechanisms (missing completely at random, missing at random, missing not at random) and high dropout prediction accuracy. We applied the JM to an existing empirical EMA data set, using baseline (e.g., depression) and time-varying (affect, intermittent missingness) predictors of dropout. The extended JM outperformed a baseline-only survival model in predicting dropout. The sensitivity analysis of the missingness mechanism revealed that fixed-effect estimates remained stable across different missing data mechanisms, whereas random-effect estimates for autocorrelation were sensitive to these assumptions. By integrating autoregressive components, the extended JM accommodates temporal dependencies and dynamically updates predictions of dropout risk. This approach improves dropout prediction in EMA studies and highlights the importance of utilizing JMs for predicting clinically relevant outcomes while integrating EMA data. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
生态瞬时评估（EMA）的大量纵向数据被广泛应用于临床研究，但经常出现退出现象，导致统计效力降低，结果无效，治疗效果差。预测辍学可能有助于预防。虽然现有方法利用基线协变量，但很少有研究考虑EMA数据的时间动态或确定辍学的确切时间。联合模型（JM）可以同时对纵向过程和事件时间数据进行建模，从而提供动态预测。然而，传统的JMs假设有限的测量场合，并且不考虑EMA数据固有的自相关性。我们通过合并一个自回归子模型来扩展标准JM，在EMA测量中捕获时间依赖性。我们通过模拟研究验证了我们的方法，证明了不同缺失机制（完全随机缺失、随机缺失、非随机缺失）下的良好参数恢复和高辍学预测精度。我们将JM应用于现有的经验EMA数据集，使用基线（例如抑郁）和时变（影响，间歇性缺失）辍学预测因子。扩展的JM在预测辍学方面优于仅限基线生存模型。缺失机制的敏感性分析表明，固定效应估计在不同缺失数据机制下保持稳定，而自相关的随机效应估计对这些假设敏感。通过集成自回归组件，扩展的JM适应时间依赖性并动态更新辍学风险的预测。该方法改善了EMA研究中的退出预测，并强调了在整合EMA数据的同时利用JMs预测临床相关结果的重要性。（PsycInfo Database Record (c) 2025 APA，版权所有）。
{"title":"Predicting dropout in intensive longitudinal data: Extending the joint model for autocorrelated data.","authors":"Fridtjof Petersen,Laura F Bringmann,Dimitris Rizopoulos","doi":"10.1037/pas0001397","DOIUrl":"https://doi.org/10.1037/pas0001397","url":null,"abstract":"Intensive longitudinal data from ecological momentary assessment (EMA) are widely used in clinical research but often suffer from dropout, leading to reduced statistical power, invalid results, and poor treatment outcomes. Predicting dropout could help with its prevention. While existing methods utilize baseline covariates, few studies account for the temporal dynamics of EMA data or identify the exact timing of dropout. Joint models (JM) enable simultaneous modeling of longitudinal processes and time-to-event data, offering dynamic predictions. However, conventional JMs assume limited measurement occasions and do not account for the autocorrelation inherent in EMA data. We extended the standard JM by incorporating an autoregressive submodel, capturing temporal dependencies in EMA measurements. We validated our approach through simulation studies, demonstrating good parameter recovery across different missingness mechanisms (missing completely at random, missing at random, missing not at random) and high dropout prediction accuracy. We applied the JM to an existing empirical EMA data set, using baseline (e.g., depression) and time-varying (affect, intermittent missingness) predictors of dropout. The extended JM outperformed a baseline-only survival model in predicting dropout. The sensitivity analysis of the missingness mechanism revealed that fixed-effect estimates remained stable across different missing data mechanisms, whereas random-effect estimates for autocorrelation were sensitive to these assumptions. By integrating autoregressive components, the extended JM accommodates temporal dependencies and dynamically updates predictions of dropout risk. This approach improves dropout prediction in EMA studies and highlights the importance of utilizing JMs for predicting clinically relevant outcomes while integrating EMA data. (PsycInfo Database Record (c) 2025 APA, all rights reserved).","PeriodicalId":20770,"journal":{"name":"Psychological Assessment","volume":"105 1","pages":"493-506"},"PeriodicalIF":3.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145351503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sunhye Bai,Nicole M Froidevaux,Mengyun Chen,Andrew C High,Kaitlyn E Ewing,Jessica DeFelice,Jonathan Weaver,Kelly W Ngigi,Meghan R Riccio,Shou-Chun Chiang,Liu Bai,Erika S Lunkenheimer,Timothy R Brick
To advance the design and use of intensive longitudinal methods in investigations of adolescent depression, we conducted a multimethod and multi-informant study of daily parent-youth interactions, specifically, supportive communication, consisting of (a) naturalistic video observations of parent-youth interactions; (b) passive collection of Bluetooth Low Energy signals to approximate parent-youth proximity; and (c) scheduled, proximity-contingent and self-initiated ecological momentary assessments (EMA). We examined whether these novel and complementary approaches enhanced the assessment of parent-youth interactions, a key source of risk and protection for youth mental health. Specifically, we report participant compliance on the video recording procedures and describe preliminary results from our observational coding of supportive communication. We also report compliance rates on EMAs and examine the frequencies of parent-youth interactions per self-report and Bluetooth Low Energy signals. Participants in the 2-week-long protocol were 12- to 15-year-old adolescents (N = 138; 63.8% female, 42% Center for Epidemiologic Studies Depression ≥ 16) and their parents (95.7% biological mothers, 25% Center for Epidemiologic Studies Depression ≥ 16). Dyads completed mean 122.6 min (SD = 85.6) of video recordings. In 387 min of recordings from three pilot families, we identified 52 supportive communication episodes. The average parent and youth were compliant with EMA procedures, completing the recommended minimum of 40 cumulative surveys each. Parents and youth reported that they interacted with the other member in mean 56%-83% of the EMAs. The study demonstrates innovative ways to leverage technology to conduct multimethod and multi-informant intensive longitudinal assessments of interpersonal interactions, a key source of risk and protection for adolescent mental health. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
为了进一步设计和使用深入的纵向研究方法来研究青少年抑郁症，我们对父母与青少年的日常互动，特别是支持性交流进行了多方法、多信息的研究，包括(a)父母与青少年互动的自然视频观察；(b)被动收集低功耗蓝牙信号，以接近父母与青少年的接近程度；(c)预定的、邻近的和自发的生态瞬间评估（EMA）。我们研究了这些新颖和互补的方法是否增强了亲子互动的评估，亲子互动是青少年心理健康的风险和保护的关键来源。具体来说，我们报告了参与者对视频录制程序的依从性，并描述了我们对支持性沟通的观察编码的初步结果。我们还报告了EMAs的依从率，并根据自我报告和蓝牙低能量信号检查了父母-青少年互动的频率。2周方案的参与者为12- 15岁的青少年（N = 138； 63.8%为女性，42%为流行病学研究中心抑郁症≥16）及其父母（95.7%为亲生母亲，25%为流行病学研究中心抑郁症≥16）。二组平均完成录像122.6 min （SD = 85.6）。在来自三个飞行员家庭的387分钟的录音中，我们确定了52个支持性的交流片段。家长和青少年平均遵守了EMA程序，每人完成了建议的至少40项累积调查。家长和青少年报告说，他们与其他成员互动的平均比例为56%-83%。该研究展示了利用技术对人际交往进行多方法和多信息密集纵向评估的创新方法，人际交往是青少年心理健康风险和保护的关键来源。（PsycInfo Database Record (c) 2025 APA，版权所有）。
{"title":"Families being supportive together: A multimethod and multi-informant intensive longitudinal study of family protective mechanisms for adolescent depression.","authors":"Sunhye Bai,Nicole M Froidevaux,Mengyun Chen,Andrew C High,Kaitlyn E Ewing,Jessica DeFelice,Jonathan Weaver,Kelly W Ngigi,Meghan R Riccio,Shou-Chun Chiang,Liu Bai,Erika S Lunkenheimer,Timothy R Brick","doi":"10.1037/pas0001400","DOIUrl":"https://doi.org/10.1037/pas0001400","url":null,"abstract":"To advance the design and use of intensive longitudinal methods in investigations of adolescent depression, we conducted a multimethod and multi-informant study of daily parent-youth interactions, specifically, supportive communication, consisting of (a) naturalistic video observations of parent-youth interactions; (b) passive collection of Bluetooth Low Energy signals to approximate parent-youth proximity; and (c) scheduled, proximity-contingent and self-initiated ecological momentary assessments (EMA). We examined whether these novel and complementary approaches enhanced the assessment of parent-youth interactions, a key source of risk and protection for youth mental health. Specifically, we report participant compliance on the video recording procedures and describe preliminary results from our observational coding of supportive communication. We also report compliance rates on EMAs and examine the frequencies of parent-youth interactions per self-report and Bluetooth Low Energy signals. Participants in the 2-week-long protocol were 12- to 15-year-old adolescents (N = 138; 63.8% female, 42% Center for Epidemiologic Studies Depression ≥ 16) and their parents (95.7% biological mothers, 25% Center for Epidemiologic Studies Depression ≥ 16). Dyads completed mean 122.6 min (SD = 85.6) of video recordings. In 387 min of recordings from three pilot families, we identified 52 supportive communication episodes. The average parent and youth were compliant with EMA procedures, completing the recommended minimum of 40 cumulative surveys each. Parents and youth reported that they interacted with the other member in mean 56%-83% of the EMAs. The study demonstrates innovative ways to leverage technology to conduct multimethod and multi-informant intensive longitudinal assessments of interpersonal interactions, a key source of risk and protection for adolescent mental health. (PsycInfo Database Record (c) 2025 APA, all rights reserved).","PeriodicalId":20770,"journal":{"name":"Psychological Assessment","volume":"45 1","pages":"535-546"},"PeriodicalIF":3.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145351651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aidan G C Wright,Florian Scharf,Johannes Zimmermann
Ambulatory assessment is popular in research settings for its ability to assess real-world functioning. It is useful for estimating an individual's typical level of a behavior (individual mean), how (un)stable that behavior is (individual standard deviation), how behaviors associate with others or specific contexts (within-person correlation), and shifts in those statistics that might signal an important change in functioning (e.g., early warning signal). However, many of the methodological advances have not made the jump from the lab to clinical practice. Effective use of ambulatory assessment in applied settings to understand functioning and guide potential interventions requires development and application of psychometric standards for N = 1 assessments. We conducted a simulation study to determine how many assessments are necessary to achieve sufficiently reliable (i.e., precise and stable) estimates of an individual's mean and standard deviation on a single variable as well as the correlation between two variables. To ensure the ecological validity of the simulation conditions, we used real time series data from a large sample that included psychiatric patients and nonpatients (capturing realistic levels of autocorrelation and skewness). We found that the minimum number of assessments depends on the statistic of interest and the temporal characteristics of the variable of interest. Individual means can be estimated reliably with a reasonably small number of observations under most conditions, but adequately precise and stable individual correlations require more assessments than may be achievable in many applied settings. Implications of these results for the potential of applied ambulatory assessment in clinical practice are discussed. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
动态评估在研究环境中很受欢迎，因为它能够评估现实世界的功能。它有助于估计个体的典型行为水平（个体均值）、行为的不稳定性（个体标准差）、行为与他人或特定环境的关联（人际相关性），以及那些可能表明功能发生重要变化的统计数据的变化（例如，早期预警信号）。然而，许多方法上的进步并没有从实验室跳到临床实践。在应用环境中有效地使用动态评估来了解功能和指导潜在的干预措施，需要开发和应用N = 1评估的心理测量标准。我们进行了一项模拟研究，以确定需要进行多少次评估才能对单个变量的个人平均值和标准差以及两个变量之间的相关性进行足够可靠（即精确和稳定）的估计。为了确保模拟条件的生态有效性，我们使用了来自包括精神病患者和非患者在内的大样本的实时时序数据（捕获现实水平的自相关和偏度）。我们发现评估的最小数量取决于兴趣的统计量和兴趣变量的时间特征。在大多数条件下，通过少量的观测就可以可靠地估计个体均值，但在许多应用环境中，需要对足够精确和稳定的个体相关性进行更多的评估。这些结果对临床实践中应用动态评估的潜在意义进行了讨论。（PsycInfo Database Record (c) 2025 APA，版权所有）。
{"title":"Minimum sampling recommendations for applied ambulatory assessment.","authors":"Aidan G C Wright,Florian Scharf,Johannes Zimmermann","doi":"10.1037/pas0001408","DOIUrl":"https://doi.org/10.1037/pas0001408","url":null,"abstract":"Ambulatory assessment is popular in research settings for its ability to assess real-world functioning. It is useful for estimating an individual's typical level of a behavior (individual mean), how (un)stable that behavior is (individual standard deviation), how behaviors associate with others or specific contexts (within-person correlation), and shifts in those statistics that might signal an important change in functioning (e.g., early warning signal). However, many of the methodological advances have not made the jump from the lab to clinical practice. Effective use of ambulatory assessment in applied settings to understand functioning and guide potential interventions requires development and application of psychometric standards for N = 1 assessments. We conducted a simulation study to determine how many assessments are necessary to achieve sufficiently reliable (i.e., precise and stable) estimates of an individual's mean and standard deviation on a single variable as well as the correlation between two variables. To ensure the ecological validity of the simulation conditions, we used real time series data from a large sample that included psychiatric patients and nonpatients (capturing realistic levels of autocorrelation and skewness). We found that the minimum number of assessments depends on the statistic of interest and the temporal characteristics of the variable of interest. Individual means can be estimated reliably with a reasonably small number of observations under most conditions, but adequately precise and stable individual correlations require more assessments than may be achievable in many applied settings. Implications of these results for the potential of applied ambulatory assessment in clinical practice are discussed. (PsycInfo Database Record (c) 2025 APA, all rights reserved).","PeriodicalId":20770,"journal":{"name":"Psychological Assessment","volume":"43 1","pages":"466-478"},"PeriodicalIF":3.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145351459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The future of technology-mediated just-in-time interventions requires detecting moments when skills would be most useful. For example, affect regulation skills could be provided during emotional episodes. But how do researchers (and clinicians) operationalize "emotional" episodes? In this study, we use secondary data from an 8-day ecological momentary assessment study (n = 197) where participants rated emotional adjectives of positive (e.g., joyful, calm, relaxed) and negative (e.g., sad, angry, anxious) feelings on a 0-100 scale and a categorical subjective determination of emotion 5×/day. We compared three different ways of classifying whether a moment was "better" (i.e., more positive), "worse" (i.e., more distressing), or typical/as usual affect: (Option A) elevated level of affect for positive and/or negative affect (e.g., whether the rating was high or low on the scale itself), (Option B) a 17-point deviation from the person's own average on positive and a 12-point deviation for negative affect, and (Option C) the participant's own categorical determination of better, same, or worse. Results revealed that affect level (Option A) and the participant's own subjective determination (Option C) resulted in more moments classified as emotional than person-centered deviations, especially person-centered deviations on negative affect. In validating all classification methods, we found that "worse" was associated with more problems (e.g., lower thought clarity and willpower, greater experiential avoidance and rash action urges) than "affect as usual" using all options. We discuss implications for how researchers and clinicians can use technology to find "emotional" moments in future studies, with the aim of guidance toward just-in-time momentary interventions. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
未来以技术为媒介的即时干预需要发现技能最有用的时刻。例如，情感调节技能可以在情绪发作时提供。但是，研究人员（和临床医生）如何操作“情绪”发作呢？在这项研究中，我们使用了一项为期8天的生态瞬间评估研究（n = 197）的辅助数据，参与者在0-100的范围内对积极（如快乐、平静、放松）和消极（如悲伤、愤怒、焦虑）的情绪形容词进行评级，并对情绪进行分类主观判断5x /天。我们比较了三种不同的分类方式，即一个时刻是“更好”（即更积极），“更糟糕”（即更痛苦），还是典型/一如既往的影响：（选项A）对积极和/或消极影响的影响水平升高（例如，量表本身的评分是高还是低），（选项B）对积极影响的平均偏差为17分，对消极影响的平均偏差为12分，（选项C）参与者自己对更好，相同或更差的分类决定。结果表明，情感水平（选项A）和参与者自己的主观决定（选项C）导致更多的时刻被归类为情绪偏差，而不是以人为中心的偏差，尤其是以人为中心的负面情绪偏差。在验证所有分类方法时，我们发现“更糟”与更多问题相关（例如，更低的思路清晰度和意志力，更大的经验回避和鲁莽的行动冲动），而不是“像往常一样”使用所有选项。我们讨论了研究人员和临床医生如何在未来的研究中使用技术来发现“情绪”时刻的影响，目的是指导及时的瞬间干预。（PsycInfo Database Record (c) 2025 APA，版权所有）。
{"title":"Considering how to classify \"emotional\" episodes via ecological momentary assessment.","authors":"Jennifer C Veilleux,Caroline P Dina","doi":"10.1037/pas0001394","DOIUrl":"https://doi.org/10.1037/pas0001394","url":null,"abstract":"The future of technology-mediated just-in-time interventions requires detecting moments when skills would be most useful. For example, affect regulation skills could be provided during emotional episodes. But how do researchers (and clinicians) operationalize \"emotional\" episodes? In this study, we use secondary data from an 8-day ecological momentary assessment study (n = 197) where participants rated emotional adjectives of positive (e.g., joyful, calm, relaxed) and negative (e.g., sad, angry, anxious) feelings on a 0-100 scale and a categorical subjective determination of emotion 5×/day. We compared three different ways of classifying whether a moment was \"better\" (i.e., more positive), \"worse\" (i.e., more distressing), or typical/as usual affect: (Option A) elevated level of affect for positive and/or negative affect (e.g., whether the rating was high or low on the scale itself), (Option B) a 17-point deviation from the person's own average on positive and a 12-point deviation for negative affect, and (Option C) the participant's own categorical determination of better, same, or worse. Results revealed that affect level (Option A) and the participant's own subjective determination (Option C) resulted in more moments classified as emotional than person-centered deviations, especially person-centered deviations on negative affect. In validating all classification methods, we found that \"worse\" was associated with more problems (e.g., lower thought clarity and willpower, greater experiential avoidance and rash action urges) than \"affect as usual\" using all options. We discuss implications for how researchers and clinicians can use technology to find \"emotional\" moments in future studies, with the aim of guidance toward just-in-time momentary interventions. (PsycInfo Database Record (c) 2025 APA, all rights reserved).","PeriodicalId":20770,"journal":{"name":"Psychological Assessment","volume":"69 1","pages":"507-519"},"PeriodicalIF":3.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145351458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jordan Revol,Ginette Lafit,Olivia Kirtley,Eva Ceulemans
The experience sampling method (ESM) plays a pivotal role in investigating the dynamics of psychopathological processes in daily life. A crucial question when designing ESM studies concerns the sample size needed, defined by the number of participants (N) and the number of measurement occasions per participant (T). Higher N and T increase power, but also increase researcher and participant burden, and study cost. Current approaches for sample size planning rarely account for these feasibility and financial constraints explicitly, despite significant variations in ESM studies' design, operational expenses, participant incentives, and compliance rates. This oversight can lead to suboptimal or unrealistic sample size planning. In this article, we extend the traditional power analysis framework to integrate budget constraints into sample size decisions. In particular, we demonstrate how to formalize budget considerations into cost functions for ESM studies and how to use these to optimally select N and T values. Through an illustrative example, we showcase how optimal sample size decisions strongly differ across ESM designs and associated cost functions, even when focusing on the same research questions. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
经验抽样法（ESM）在研究日常生活中心理病理过程的动态方面起着关键作用。设计ESM研究时的一个关键问题涉及所需的样本量，由参与者数量(N)和每个参与者的测量次数(T)定义。更高的N和T增加了权力，但也增加了研究人员和参与者的负担，增加了研究成本。尽管ESM研究的设计、运营费用、参与者激励和遵守率存在显著差异，但目前的样本量规划方法很少明确考虑到这些可行性和财务限制。这种疏忽可能导致次优或不现实的样本量规划。在本文中，我们扩展了传统的权力分析框架，将预算约束集成到样本量决策中。特别是，我们演示了如何将预算考虑形式化为ESM研究的成本函数，以及如何使用这些来最佳地选择N和T值。通过一个说明性的例子，我们展示了最佳样本量决策如何在ESM设计和相关成本函数之间存在巨大差异，即使关注的是相同的研究问题。（PsycInfo Database Record (c) 2025 APA，版权所有）。
{"title":"Cost-effective experience sampling method studies: Integrating budget constraints into sample size decisions.","authors":"Jordan Revol,Ginette Lafit,Olivia Kirtley,Eva Ceulemans","doi":"10.1037/pas0001409","DOIUrl":"https://doi.org/10.1037/pas0001409","url":null,"abstract":"The experience sampling method (ESM) plays a pivotal role in investigating the dynamics of psychopathological processes in daily life. A crucial question when designing ESM studies concerns the sample size needed, defined by the number of participants (N) and the number of measurement occasions per participant (T). Higher N and T increase power, but also increase researcher and participant burden, and study cost. Current approaches for sample size planning rarely account for these feasibility and financial constraints explicitly, despite significant variations in ESM studies' design, operational expenses, participant incentives, and compliance rates. This oversight can lead to suboptimal or unrealistic sample size planning. In this article, we extend the traditional power analysis framework to integrate budget constraints into sample size decisions. In particular, we demonstrate how to formalize budget considerations into cost functions for ESM studies and how to use these to optimally select N and T values. Through an illustrative example, we showcase how optimal sample size decisions strongly differ across ESM designs and associated cost functions, even when focusing on the same research questions. (PsycInfo Database Record (c) 2025 APA, all rights reserved).","PeriodicalId":20770,"journal":{"name":"Psychological Assessment","volume":"201 1","pages":"479-492"},"PeriodicalIF":3.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145351461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J Jongerling,M P J Schellekens,M Bolsinova,M L van der Lee,L V D E Vogelsmeier
Successful personalized treatment requires a thorough understanding of the complex dynamic processes underlying disorders. Intensive longitudinal methods (e.g., experience sampling) that ask patients to complete multiple-item questionnaires several times a day are ideally suited for this. However, collecting such data entails severe patient burden, especially for those with low energy and little concentration (e.g., patients suffering from chronic cancer-related fatigue and/or psychological disorders such as somatic symptom disorder). This burden is currently predominantly lightened with single-item measures, but these cannot validly capture complex conditions, leading to a catch-22 situation: Capturing complex dynamic processes and effective personalized treatment require intensive longitudinal patient data on multiple-item questionnaires, but patients cannot provide this type of data because it is too taxing. To solve this problem, we developed a personalized missingness design that presents an individualized and time-varying minimal subset of items on each occasion, thereby striking an optimal balance between thoroughly mapping patients' symptoms and keeping the number of items a person needs to answer to a minimum. The design builds on multilevel factor analyses to determine which sets of items are most informative, which can change over time. Expert-informed simulations validated our new design. While the design can be universally applied to any measurement of (psychological) symptoms (e.g., to inform cognitive behavioral therapy), we tailored our simulations to patients suffering from chronic cancer-related fatigue in collaboration with experts in psycho-oncology. In the near future, the design will be implemented in the widely used experience sampling app m-Path in collaboration with the developers. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
成功的个性化治疗需要对潜在疾病的复杂动态过程有透彻的了解。密集的纵向方法（例如，经验抽样）要求患者每天多次完成多项问卷调查，这是非常适合的。然而，收集这些数据会给患者带来沉重的负担，特别是对于那些精力不足、注意力不集中的患者（例如患有慢性癌症相关疲劳和/或躯体症状障碍等心理障碍的患者）。目前，单项目措施主要减轻了这一负担，但这些措施不能有效地捕捉复杂的情况，导致进退两难的局面：捕捉复杂的动态过程和有效的个性化治疗需要在多项目问卷上收集大量的纵向患者数据，但患者无法提供这种类型的数据，因为它太费力了。为了解决这个问题，我们开发了一种个性化的缺失设计，在每种情况下呈现个性化和随时间变化的最小项目子集，从而在彻底映射患者症状和保持患者需要回答的项目数量之间取得最佳平衡。该设计建立在多层次因素分析的基础上，以确定哪组项目是最具信息量的，这可以随着时间的推移而改变。专家模拟验证了我们的新设计。虽然该设计可以普遍应用于任何（心理）症状的测量（例如，为认知行为治疗提供信息），但我们与心理肿瘤学专家合作，为患有慢性癌症相关疲劳的患者量身定制了模拟。在不久的将来，该设计将与开发人员合作，在广泛使用的体验采样应用程序m-Path中实现。（PsycInfo Database Record (c) 2025 APA，版权所有）。
{"title":"Reducing patient burden in experience sampling studies: A simulation study to validate the personalized missingness design.","authors":"J Jongerling,M P J Schellekens,M Bolsinova,M L van der Lee,L V D E Vogelsmeier","doi":"10.1037/pas0001391","DOIUrl":"https://doi.org/10.1037/pas0001391","url":null,"abstract":"Successful personalized treatment requires a thorough understanding of the complex dynamic processes underlying disorders. Intensive longitudinal methods (e.g., experience sampling) that ask patients to complete multiple-item questionnaires several times a day are ideally suited for this. However, collecting such data entails severe patient burden, especially for those with low energy and little concentration (e.g., patients suffering from chronic cancer-related fatigue and/or psychological disorders such as somatic symptom disorder). This burden is currently predominantly lightened with single-item measures, but these cannot validly capture complex conditions, leading to a catch-22 situation: Capturing complex dynamic processes and effective personalized treatment require intensive longitudinal patient data on multiple-item questionnaires, but patients cannot provide this type of data because it is too taxing. To solve this problem, we developed a personalized missingness design that presents an individualized and time-varying minimal subset of items on each occasion, thereby striking an optimal balance between thoroughly mapping patients' symptoms and keeping the number of items a person needs to answer to a minimum. The design builds on multilevel factor analyses to determine which sets of items are most informative, which can change over time. Expert-informed simulations validated our new design. While the design can be universally applied to any measurement of (psychological) symptoms (e.g., to inform cognitive behavioral therapy), we tailored our simulations to patients suffering from chronic cancer-related fatigue in collaboration with experts in psycho-oncology. In the near future, the design will be implemented in the widely used experience sampling app m-Path in collaboration with the developers. (PsycInfo Database Record (c) 2025 APA, all rights reserved).","PeriodicalId":20770,"journal":{"name":"Psychological Assessment","volume":"69 1","pages":"547-556"},"PeriodicalIF":3.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145351552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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