{"title":"Supplemental Material for Longitudinal Measurement Invariance of the Personality Inventory for ICD-11 Across Black and White American Older Adults","authors":"","doi":"10.1037/pas0001421.supp","DOIUrl":"https://doi.org/10.1037/pas0001421.supp","url":null,"abstract":"","PeriodicalId":20770,"journal":{"name":"Psychological Assessment","volume":"30 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145396882","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 The Dissociative Symptoms Scale (DSS): Psychometric Properties of Scores on a German Version in Clinical Samples","authors":"","doi":"10.1037/pas0001432.supp","DOIUrl":"https://doi.org/10.1037/pas0001432.supp","url":null,"abstract":"","PeriodicalId":20770,"journal":{"name":"Psychological Assessment","volume":"149 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145397005","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 Development and Validation of the Visual Reasoning Test for the NIH Toolbox","authors":"","doi":"10.1037/pas0001425.supp","DOIUrl":"https://doi.org/10.1037/pas0001425.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":"145396885","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 A Psychometric Examination of Computerized Adaptive Measures of Posttraumatic Stress Disorder Among Military Veterans","authors":"","doi":"10.1037/pas0001429.supp","DOIUrl":"https://doi.org/10.1037/pas0001429.supp","url":null,"abstract":"","PeriodicalId":20770,"journal":{"name":"Psychological Assessment","volume":"30 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145397015","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 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}
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