Kidist Bekele-Maxwell, R A Everett, Sijing Shao, Alexis Kuerbis, Lyric Stephenson, H T Banks, Jon Morgenstern
{"title":"Dynamical Systems Modeling to Identify a Cohort of Problem Drinkers with Similar Mechanisms of Behavior Change.","authors":"Kidist Bekele-Maxwell, R A Everett, Sijing Shao, Alexis Kuerbis, Lyric Stephenson, H T Banks, Jon Morgenstern","doi":"10.17505/jpor.2017.09","DOIUrl":"https://doi.org/10.17505/jpor.2017.09","url":null,"abstract":"<p><p>One challenge to understanding mechanisms of behavior change (MOBC) completely among individuals with alcohol use disorder is that processes of change are theorized to be complex, dynamic (time varying), and at times non-linear, and they interact with each other to influence alcohol consumption. We used dynamical systems modeling to better understand MOBC within a cohort of problem drinkers undergoing treatment. We fit a mathematical model to ecological momentary assessment data from individual patients who successfully reduced their drinking by the end of the treatment. The model solutions agreed with the trend of the data reasonably well, suggesting the cohort patients have similar MOBC. This work demonstrates using a personalized approach to psychological research, which complements standard statistical approaches that are often applied at the population level.</p>","PeriodicalId":36744,"journal":{"name":"Journal for Person-Oriented Research","volume":"3 2","pages":"101-118"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7869621/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9909370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Briana N Sprague, Jinshil Hyun, Peter C M Molenaar
{"title":"Revisiting measurement invariance in intelligence testing in aging research: Evidence for almost complete metric invariance across age groups.","authors":"Briana N Sprague, Jinshil Hyun, Peter C M Molenaar","doi":"10.17505/jpor.2017.08","DOIUrl":"10.17505/jpor.2017.08","url":null,"abstract":"<p><strong>Background/objectives: </strong>Invariance of intelligence across age is often assumed but infrequently explicitly tested. Horn and McArdle (1992) tested measurement invariance of intelligence, providing adequate model fit but might not consider all relevant aspects such as sub-test differences. The goal of the current paper is to explore age-related invariance of the WAIS-R using an alternative model that allows direct tests of age on WAIS-R subtests.</p><p><strong>Methods: </strong>Cross-sectional data on 940 participants aged 16-75 from the WAIS-R normative values were used. Subtests examined were information, comprehension, similarities, vocabulary, picture completion, block design, picture arrangement, and object assembly. The two intelligence factors considered were fluid and crystallized intelligence. Self-reported ages were divided into young (16-22, <i>n</i> = 300), adult (29-39, <i>n</i> = 275), middle (40-60, <i>n</i> = 205), and older (61-75, <i>n</i> = 160) adult groups.</p><p><strong>Results: </strong>Results suggested partial metric invariance holds. Although most of the subtests reflected fluid and crystalized intelligence similarly across different ages, invariance did not hold for block design on fluid intelligence and picture arrangement on crystallized intelligence for older adults. Additionally, there was evidence of a correlated residual between information and vocabulary for the young adults only. This partial metric invariance model yielded acceptable model fit compared to previously-proposed invariance models of Horn and McArdle (1992).</p><p><strong>Conclusion: </strong>Almost complete metric invariance holds for a two-factor model of intelligence. Most of the subtests were invariant across age groups, suggesting little evidence for age-related bias in the WAIS-R. However, we did find unique relationships between two subtests and intelligence. Future studies should examine age-related differences in subtests when testing measurement invariance in intelligence.</p>","PeriodicalId":36744,"journal":{"name":"Journal for Person-Oriented Research","volume":" ","pages":"86-100"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983042/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36192440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Dynamics of Change and Change in Dynamics.","authors":"Steven M Boker, Angela D Staples, Yueqin Hu","doi":"10.17505/jpor.2016.05","DOIUrl":"10.17505/jpor.2016.05","url":null,"abstract":"<p><p>A framework is presented for building and testing models of dynamic regulation by categorizing sources of differences between theories of dynamics. A distinction is made between the dynamics of change, i.e., how a system self-regulates on a short time scale, and change in dynamics, i.e., how those dynamics may themselves change over a longer time scale. In order to clarify the categories, models are first built to estimate individual differences in equilibrium value and equilibrium change. Next, models are presented in which there are individual differences in parameters of dynamics such as frequency of fluctuations, damping of fluctuations, and amplitude of fluctuations. Finally, models for within-person change in dynamics over time are proposed. Simulations demonstrating feasibility of these models are presented and OpenMx scripts for fitting these models have been made available in a downloadable archive along with scripts to simulate data so that a researcher may test a selected models' feasibility within a chosen experimental design.</p>","PeriodicalId":36744,"journal":{"name":"Journal for Person-Oriented Research","volume":"2 1-2","pages":"34-55"},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5642952/pdf/nihms866630.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35523419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Adaptive Equilibrium Regulation: A Balancing Act in Two Timescales.","authors":"Steven M Boker","doi":"10.17505/jpor.2015.10","DOIUrl":"https://doi.org/10.17505/jpor.2015.10","url":null,"abstract":"<p><p>An equilibrium involves a balancing of forces. Just as one maintains upright posture in standing or walking, many self-regulatory and interpersonal behaviors can be framed as a balancing act between an ever changing environment and within-person processes. The emerging balance between person and environment, the equilibria, are dynamic and adaptive in response to development and learning. A distinction is made between equilibrium achieved solely due to a short timescale balancing of forces and a longer timescale <i>preferred equilibrium</i> which we define as a state towards which the system slowly adapts. Together, these are developed into a framework that this article calls Adaptive Equilibrium Regulation (ÆR), which separates a regulatory process into two timescales: a faster regulation that automatically balances forces and a slower timescale adaptation process that reconfigures the fast regulation so as to move the system towards its preferred equilibrium when an environmental force persists over the longer timescale. This way of thinking leads to novel models for the interplay between multiple timescales of behavior, learning, and development.</p>","PeriodicalId":36744,"journal":{"name":"Journal for Person-Oriented Research","volume":"1 1-2","pages":"99-109"},"PeriodicalIF":0.0,"publicationDate":"2015-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4824612/pdf/nihms744186.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34391471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}