The Experts below are selected from a list of 8796 Experts worldwide ranked by ideXlab platform
Rinad S Beidas - One of the best experts on this subject based on the ideXlab platform.
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characterizing the heterogeneity of clinician practice use in community mental health using Latent Profile Analysis
BMC Psychiatry, 2019Co-Authors: Rinad S Beidas, Emily M Beckerhaimes, Viktor Lushin, Torrey A CreedAbstract:The behavioral health service provider population is highly heterogeneous. However, it is rarely treated as such within evidence-based practice implementation efforts. This study aimed to evaluate, as a proof of concept, the utility of Latent Profile Analysis to identify distinct Profiles of clinician practices in a large sample of youth-serving community mental health clinicians. This study also aimed to identify predictors of Profile membership to inform implementation efforts. Participants were 484 practicing clinicians (79.4% female, 45.7% White, M age = 37.1 years). As part of a larger survey, clinicians reported on their use of cognitive, behavioral, family, and psychodynamic treatment techniques with a representative client on their caseload. Latent Profile Analysis was used to determine the presence of clinician practice Profiles. Multilevel multinomial logistic regressions examined predictors of Profile membership. Latent Profile Analysis indicated a 4-Profile solution best fit the data, with clinicians who: 1) used generally low levels of all examined techniques and preferred cognitive techniques (Low Eclectics, 16%), 2) delivered moderate levels of all techniques (Moderate Eclectics, 53%), 3) demonstrated preference for use of family techniques (Family Preferred, 11%), and 4) used high levels of all techniques (Super Users, 20%). Clinician discipline (e.g., social work), education, and years of experience predicted Profile membership. Findings from this proof of concept study underscore the utility of Latent Profile Analysis to characterize the complex and heterogeneous makeup of community mental health. Results extend prior work highlighting the eclectic nature of community mental health practice. Predictor analyses underscore the important influence of clinician background characteristics on practice use.
Donald W. Hine - One of the best experts on this subject based on the ideXlab platform.
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Latent Profile Analysis of working memory capacity and thinking styles in adults and adolescents
Journal of Research in Personality, 2012Co-Authors: Jennifer Fletcher, Anthony D. G. Marks, Donald W. HineAbstract:Abstract This study of adults (n = 269) and adolescents (n = 308) applied Latent Profile Analysis to preference for rational and/or experiential cognition, coupled with working memory capacity (WMC). A 4-Profile solution comprising rationally dominant, experientially dominant, dual preference, and disengaged groups was retained for both adult and adolescent samples. Our solution indicated that high WMC was associated with both preference and ability to engage in rational processing. Profile membership significantly discriminated both adults and adolescents on several reasoning tasks and measures of cognitive biases. Overall our results indicate that cognitive processing styles and WMC can be combined to create a typology that distinguishes between four types of thinkers who significantly differ in their performance on reasoning tasks.
B. S. Coral Lim - One of the best experts on this subject based on the ideXlab platform.
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A Latent Profile Analysis of sedentary and physical activity patterns
Journal of Public Health, 2011Co-Authors: C.k. John Wang, Stuart J. H. Biddle, Woon Chia Liu, B. S. Coral LimAbstract:Aim The aim of the current study was to examine the physical activity and sedentary behavioral patterns of children and adolescents using the model-based Latent Profile Analysis (LPA) approach.
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A Latent Profile Analysis of sedentary and physical activity patterns
Journal of Public Health, 2011Co-Authors: C.k. John Wang, Stuart J. H. Biddle, Woon Chia Liu, B. S. Coral LimAbstract:Aim: The aim of the current study was to examine the physical activity and sedentary behavioral patterns of children and adolescents using the model-based Latent Profile Analysis (LPA) approach. Subject and methods: A sample of 847 school children aged 10 to 16 years from 28 Singapore schools took part in the study. Physical activity and sedentary behavior were assessed using a 7-day physical activity recall questionnaire. Results: The findings of the present study showed that there were at least five groups of students with unique sedentary and physical activity patterns. A few clusters were genderspecific. For example, groups 1 and 4 were femaledominated clusters and group 3 was male-dominated. The younger children in the primary school had different sedentary and physical activity behaviors. Conclusions: This study demonstrates the use of LPA to group individuals into homogenous groupings in order to help researchers make informed decisions about the number of underlying groupings. This can have benefits for targeting specific groups in interventions. © Springer-Verlag 2011.
Emily M Beckerhaimes - One of the best experts on this subject based on the ideXlab platform.
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characterizing the heterogeneity of clinician practice use in community mental health using Latent Profile Analysis
BMC Psychiatry, 2019Co-Authors: Rinad S Beidas, Emily M Beckerhaimes, Viktor Lushin, Torrey A CreedAbstract:The behavioral health service provider population is highly heterogeneous. However, it is rarely treated as such within evidence-based practice implementation efforts. This study aimed to evaluate, as a proof of concept, the utility of Latent Profile Analysis to identify distinct Profiles of clinician practices in a large sample of youth-serving community mental health clinicians. This study also aimed to identify predictors of Profile membership to inform implementation efforts. Participants were 484 practicing clinicians (79.4% female, 45.7% White, M age = 37.1 years). As part of a larger survey, clinicians reported on their use of cognitive, behavioral, family, and psychodynamic treatment techniques with a representative client on their caseload. Latent Profile Analysis was used to determine the presence of clinician practice Profiles. Multilevel multinomial logistic regressions examined predictors of Profile membership. Latent Profile Analysis indicated a 4-Profile solution best fit the data, with clinicians who: 1) used generally low levels of all examined techniques and preferred cognitive techniques (Low Eclectics, 16%), 2) delivered moderate levels of all techniques (Moderate Eclectics, 53%), 3) demonstrated preference for use of family techniques (Family Preferred, 11%), and 4) used high levels of all techniques (Super Users, 20%). Clinician discipline (e.g., social work), education, and years of experience predicted Profile membership. Findings from this proof of concept study underscore the utility of Latent Profile Analysis to characterize the complex and heterogeneous makeup of community mental health. Results extend prior work highlighting the eclectic nature of community mental health practice. Predictor analyses underscore the important influence of clinician background characteristics on practice use.
Jennifer Fletcher - One of the best experts on this subject based on the ideXlab platform.
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Latent Profile Analysis of working memory capacity and thinking styles in adults and adolescents
Journal of Research in Personality, 2012Co-Authors: Jennifer Fletcher, Anthony D. G. Marks, Donald W. HineAbstract:Abstract This study of adults (n = 269) and adolescents (n = 308) applied Latent Profile Analysis to preference for rational and/or experiential cognition, coupled with working memory capacity (WMC). A 4-Profile solution comprising rationally dominant, experientially dominant, dual preference, and disengaged groups was retained for both adult and adolescent samples. Our solution indicated that high WMC was associated with both preference and ability to engage in rational processing. Profile membership significantly discriminated both adults and adolescents on several reasoning tasks and measures of cognitive biases. Overall our results indicate that cognitive processing styles and WMC can be combined to create a typology that distinguishes between four types of thinkers who significantly differ in their performance on reasoning tasks.
