How do students prepare in the pre-class setting of a flipped undergraduate math course? A latent profile analysis of learning behavior and the impact of achievement goals

2020 ◽  
Vol 46 ◽  
pp. 100731 ◽  
Author(s):  
Zhiru Sun ◽  
Kui Xie
Keyword(s):  
Achievement Goals ◽  
Latent Profile Analysis ◽  
Profile Analysis ◽  
Learning Behavior ◽  
The Impact ◽  
Latent Profile

Exploring Science Career Interest: Latent Profile Analysis of High School Occupational Preferences for Science

2018 ◽  
Vol 46 (5) ◽  
pp. 583-598 ◽  
Author(s):  
Sarah L. Ferguson ◽  
Darrell M. Hull
Keyword(s):  
High School ◽  
Gender Differences ◽  
Latent Profile Analysis ◽  
Profile Analysis ◽  
Future Research ◽  
Academic Experience ◽  
Science Interest ◽  
Future Research Directions ◽  
The Impact ◽  
Latent Profile

The present study evaluates high school juniors and seniors ( n = 295) to explore their preference for science as indicated by science motivation, attitude, academic experience, and interest. Latent profile analysis was used to model profiles of preferences for science with a person-centered approach. Then, the impact of self-concept variables was explored and four profiles of science interest were identified. Gender differences were of particular interest due to concerns noted in the literature, and some gender differences were identified in the present study. Covariate analysis indicated vocabulary ability and personality as significantly different for students in the high science interest profile. Implications of these results and future research directions are discussed.

The Impact of Parenting Style on Attitudes toward Masturbation: A Latent Profile Analysis

2021 ◽  
pp. 1-15
Author(s):  
Ethan Klukas ◽  
Emily Draper ◽  
Kimberley Kaseweter ◽  
Nina Gregoire ◽  
Jan Cioe
Keyword(s):  
Parenting Style ◽  
Latent Profile Analysis ◽  
Profile Analysis ◽  
The Impact ◽  
Latent Profile

Factor Analysis of Spontaneous Speech in Aphasia

2020 ◽  
Vol 63 (12) ◽  
pp. 4127-4147
Author(s):  
Jean K. Gordon
Keyword(s):  
Factor Analysis ◽  
Language Production ◽  
Latent Profile Analysis ◽  
Profile Analysis ◽  
Ecological Validity ◽  
Spontaneous Speech ◽  
Factor Scores ◽  
Linear Discriminant ◽  
The Impact ◽  
Latent Profile

Purpose Spontaneous speech tasks are critically important for characterizing spoken language production deficits in aphasia and for assessing the impact of therapy. The utility of such tasks arises from the complex interaction of linguistic demands (word retrieval, sentence formulation, articulation). However, this complexity also makes spontaneous speech hugely variable and difficult to assess. The current study aimed to simplify the problem by identifying latent factors underlying performance in spontaneous speech in aphasia. The ecological validity of the factors was examined by examining how well the factor structures corresponded to traditionally defined aphasia subtypes. Method A factor analysis was conducted on 17 microlinguistic measures of narratives from 274 individuals with aphasia in AphasiaBank. The resulting factor scores were compared across aphasia subtypes. Supervised (linear discriminant analysis) and unsupervised (latent profile analysis) classification techniques were then conducted on the factor scores and the solutions compared to traditional aphasia subtypes. Results Six factors were identified. Two reflected aspects of fluency, one at the phrase level (Phrase Building) and one at the narrative level (Narrative Productivity). Two other factors reflected the accuracy of productions, one at the word level (Semantic Anomaly) and one at the utterance level (Grammatical Error). The other two factors reflected the complexity of sentence structures (Grammatical Complexity) and the use of repair behaviors (Repair), respectively. Linear discriminant analyses showed that only about two thirds of speakers were classified correctly and that misclassifications were similar to disagreements between clinical diagnoses. The most accurately diagnosed syndromes were the largest groups—Broca's and anomic aphasia. The latent profile analysis also generated profiles similar to Broca's and anomic aphasia but separated some subtypes according to severity. Conclusions The factor solution and the classification analyses reflected broad patterns of spontaneous speech performance in a large and representative sample of individuals with aphasia. However, such data-driven approaches present a simplified picture of aphasia patterns, much as traditional syndrome categories do. To ensure ecological validity, a hybrid approach is recommended, balancing population-level analyses with examination of performance at the level of theoretically specified subgroups or individuals. Supplemental Material https://doi.org/10.23641/asha.13232354

scholarly journals General and Eating Disorder Psychopathology in Relation to Short- and Long-Term Weight Change in Treatment-Seeking Children: A Latent Profile Analysis

2020 ◽  
Author(s):  
Anne Claire Grammer ◽  
John R Best ◽  
Lauren A Fowler ◽  
Katherine N Balantekin ◽  
Richard I Stein ◽  
...  
Keyword(s):  
Eating Disorder ◽  
Weight Change ◽  
Latent Profile Analysis ◽  
Profile Analysis ◽  
Weight Maintenance ◽  
Future Research ◽  
Eating Disorder Psychopathology ◽  
The Impact ◽  
Latent Profile

Abstract Background Concurrent general psychopathology (GP) and eating disorder psychopathology (EDP) are commonly reported among youth with overweight/obesity and may impact weight change. Purpose We identified patterns of GP and EDP in children with overweight/obesity and examined the impact on weight change following family-based behavioral obesity treatment (FBT) and maintenance interventions. Methods Children (N = 172) participated in 4 month FBT and subsequent 8 month weight maintenance interventions. GP and EDP were assessed prior to FBT (baseline). Child percentage overweight was assessed at baseline, post-FBT (4 months), and post-maintenance (12 months). Latent profile analysis identified patterns of baseline GP and EDP. Linear mixed-effects models examined if profiles predicted 4- and 12-month change in percentage overweight and if there were two-way and three-way interactions among these variables, adjusting for relevant covariates. Results Results indicated a three-profile structure: lower GP and EDP (LOWER); subclinically elevated GP and EDP without loss of control (LOC; HIGHER); and subclinically elevated GP and EDP with LOC (HIGHER + LOC). Across profiles, children on average achieved clinically meaningful weight loss (i.e., ≥9 unit change in percentage overweight) from baseline to 4 month FBT and sustained these improvements at 12 month maintenance. There was no evidence that latent profiles were related to percentage overweight change from baseline to FBT (p > .05) or baseline to maintenance (p > .05). There was no evidence for two-way or three-way interactions (p > .05). Conclusion Concurrent GP and EDP do not portend differential short- or long-term weight change following FBT and maintenance. Future research is warranted on the durability of weight change among youth with GP and EDP. Trial registration NCT00759746.

Clustering of Endorsements of Techniques of Neutralization as Predictors of Offending Among College Students: A Latent Profile Analysis Approach

2020 ◽  
pp. 073401682096216
Author(s):  
Thomas Wojciechowski
Keyword(s):  
College Students ◽  
Undergraduate Students ◽  
Latent Profile Analysis ◽  
Profile Analysis ◽  
Past Research ◽  
Theory Approach ◽  
Techniques Of Neutralization ◽  
High Profile ◽  
The Impact ◽  
Latent Profile

Past research has provided evidence that techniques of neutralization may be used to rationalize offending, and individuals who endorse such rationalizations demonstrate greater offending risk. However, there is a dearth of research focused on how the endorsement of multiple techniques of neutralization may cluster together within an individual. There is also little understanding of how different clusters predict offending risk. The present study utilized data from 248 undergraduate students. Latent profile analysis was utilized to identify unobserved clusters of stronger/weaker endorsement of techniques of neutralization. Logistic regression was utilized to model the impact of differential clustering to predict offending risk. Results indicated that a five-profile solution best fits the data (low, responsibility deniers, moderate, victim deniers, and high). Participants assigned to the high profile demonstrated elevated offending risk relative to participants assigned to any of the other profiles. Participants assigned to the high profile reported relatively high endorsement of all techniques of neutralization but especially appeal to higher loyalties and denial of injury. Identification of college students demonstrating endorsement of techniques of neutralization consistent with the high profile should be targeted for intervention. Mentoring programs that take a social learning theory approach may be useful in this regard.

scholarly journals Influence of baseline user characteristics and usage patterns within the first 24 hours on long-term engagement and effectiveness of a web-based weight loss randomized controlled trial: a latent profile analysis (Preprint)

2020 ◽  
Author(s):  
Andre Q Andrade ◽  
Alline Beleigoli ◽  
Maria De Fatima Diniz ◽  
Antonio Luiz Ribeiro
Keyword(s):  
Weight Loss ◽  
Latent Profile Analysis ◽  
Profile Analysis ◽  
Controlled Trial ◽  
User Characteristics ◽  
Class Membership ◽  
Usage Patterns ◽  
The Impact ◽  
Latent Profile

BACKGROUND Adherence to online behaviour change interventions is one of the main challenges impacting long-term efficacy. Better understanding of baseline user characteristics can improve design and fit. OBJECTIVE We aim to understand the impact of users’ characteristics and the first 24h usage patterns of a web-platform for weight loss on user engagement and weight loss in the long-term (6 months). METHODS Data from participants of the POEmaS randomised controlled trial, which compared a weight loss platform, platform plus coach and control, were analysed. Data included baseline behaviour and usage logs from initial 24h after platform access. Latent profile analysis (LPA) was used to identify classes and Kruskal-Wallis was used to test whether class membership was associated with long-term (24 weeks) adherence and weight loss. RESULTS Among 828 participants assigned to intervention arms, three classes were identified through LPA: Motivated Healthy (better baseline health habits, high 24h platform use), Indifferent Majority (balanced), Unhealthy Quitters (worse habits and low 24h platform use). Class membership was associated with long-term adherence (p<0.001), and Unhealthy Quitters had the lowest adherence. Weight loss was not associated with class membership (p=0.49), regardless of the intervention arm (platform or platform plus coach). However, Indifferent Majority users assigned to platform plus coach lost more weight than those assigned to platform only (p=0.02). CONCLUSIONS Baseline questionnaires and usage data from the first 24h after login allowed distinguishing classes, which were associated with long term adherence. This suggests that this classification might be a useful guide to improve engagement and select interventions to individual users. CLINICALTRIAL ClinicalTrials.gov NCT03435445; https://clinicaltrials.gov/ct2/show/NCT03435445.

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