scholarly journals Latent class analysis for exploring distribution patterns of primary superficial venous insufficiency

2020 ◽  
Vol 28 (3) ◽  
pp. 474-479
Author(s):  
Nurten Andaç Baltacıoğlu
Keyword(s):  
Latent Class Analysis ◽  
Saphenous Vein ◽  
Latent Class ◽  
Lower Extremities ◽  
Distribution Patterns ◽  
Latent Class Models ◽  
Chronic Venous Disease ◽  
Venous Disease ◽  
Class Analysis ◽  
Saphenofemoral Junction

Background: This study aims to identify specific segmental distribution patterns of lower extremity chronic venous disease based on latent class analysis of Doppler mapping results. Methods: A total of 1,871 lower extremities of 1,218 treatment-naïve patients (536 males, 682 females; mean age 45.4 years; range, 21 to 87 years) with chronic venous disease referred for Doppler examination between September 2009 and August 2018 were included. Refluxing superficial venous segments of the lower extremities were mapped and recorded in database in 10 distinct anatomic locations as follows: saphenofemoral junction and proximal greater saphenous vein, mid and distal thigh greater saphenous vein, anterior and posterior accessory saphenous veins, proximal and distal calf greater saphenous vein, saphenopopliteal junction and proximal lesser saphenous vein, distal lesser saphenous vein, and intersaphenous veins including Giacomini’s vein. Repeated examinations were excluded. The latent class analysis was applied to identify any possible anatomic distribution patterns of chronic venous disease. Results: Bayesian information criteria revealed three latent class models fit for refluxing segment distribution as follows: 58.2% (n=1,089) were above-the-knee greater saphenous vein segments including saphenofemoral junction (pattern 1); 29.3% (n=548) were below-the-knee greater saphenous vein segments (pattern 2); and 12.5% (n=234) were lesser saphenous vein segments and intersaphenous veins including Giacomini’s vein (pattern 3). There was no age- or sex-specific differences in the chronic venous disease distribution patterns. Conclusion: The latent class analysis, by identifying previously unseen subgroups within the sampled population, provides a new approach to classification of reflux patterns in chronic venous disease. Identification of latent classes may provide understanding of different pathophysiological bases of venous reflux and more optimal planning for interventions.

scholarly journals Incentivising doctor attendance in rural Bangladesh: a latent class analysis of a discrete choice experiment

2021 ◽  
Vol 6 (7) ◽  
pp. e006001
Author(s):  
Blake Angell ◽  
Mushtaq Khan ◽  
Raihanul Islam ◽  
Kate Mandeville ◽  
Nahitun Naher ◽  
...  
Keyword(s):  
Latent Class Analysis ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Latent Class ◽  
Latent Class Models ◽  
Class Analysis ◽  
Sustainable Solutions ◽  
Rural Bangladesh ◽  
Incentive Payments

ObjectiveDoctor absenteeism is widespread in Bangladesh, and the perspectives of the actors involved are insufficiently understood. This paper sought to elicit preferences of doctors over aspects of jobs in rural areas in Bangladesh that can help to inform the development of packages of policy interventions that may persuade them to stay at their posts.MethodsWe conducted a discrete choice experiment with 308 doctors across four hospitals in Dhaka, Bangladesh. Four attributes of rural postings were included based on a literature review, qualitative research and a consensus-building workshop with policymakers and key health-system stakeholders: relationship with the community, security measures, attendance-based policies and incentive payments. Respondents’ choices were analysed with mixed multinomial logistic and latent class models and were used to simulate the likely uptake of jobs under different policy packages.ResultsAll attributes significantly impacted doctor choices (p<0.01). Doctors strongly preferred jobs at rural facilities where there was a supportive relationship with the community (β=0.93), considered good attendance in education and training (0.77) or promotion decisions (0.67), with functional security (0.67) and higher incentive payments (0.5 per 10% increase of base salary). Jobs with disciplinary action for poor attendance were disliked by respondents (−0.63). Latent class analysis identified three groups of doctors who differed in their uptake of jobs. Scenario modelling identified intervention packages that differentially impacted doctor behaviour and combinations that could feasibly improve doctors’ attendance.ConclusionBangladeshi doctors have strong but varied preferences over interventions to overcome absenteeism. We generated evidence suggesting that interventions considering the perspective of the doctors themselves could result in substantial reductions in absenteeism. Designing policy packages that take account of the different situations facing doctors could begin to improve their ability and motivation to be present at their job and generate sustainable solutions to absenteeism in rural Bangladesh.

Latent Class Analysis for Marketing Scale Development

2011 ◽  
Vol 53 (2) ◽  
pp. 209-230 ◽  
Author(s):  
Francesca Bassi
Keyword(s):  
Scale Development ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Marketing Research ◽  
Latent Class Models ◽  
Measurement Scale ◽  
Class Analysis ◽  
Validity And Reliability ◽  
Measurement Scales ◽  
Scale Validity

Measurement scales are a crucial instrument in marketing research for measuring unobservable variables such as attitudes, opinions and beliefs. In using, evaluating or developing multi-item scales, a number of guidelines and procedures are recommended, to ensure that the measure applied is psychometrically robust. These procedures have been outlined in the psychometric literature since the late 1970s and are composed of steps that refer to construct and domain definition, scale validity, reliability, dimensionality and generalisability. Various statistical instruments are used in the scale-developing process, almost always referring to metric variables (interval or ratio scales). Instead, items forming scales are rarely measured metrically; items are frequently ordinal and, in some rare cases, nominal. In this paper, it is shown how the implementation of latent class analysis may improve the process of measurement scale development, since it explicitly considers that items generate ordinal or even nominal variables. Specifically, applying appropriate latent class models allows us to assess scale validity and reliability more soundly than traditionally used methods.

scholarly journals Latent Class Analysis of Obesogenic Behaviors among Korean Adolescents: Associations with Weight-Related Outcomes

2021 ◽  
Vol 18 (21) ◽  
pp. 11059
Author(s):  
Haein Lee ◽  
In-Seo La
Keyword(s):  
Latent Class Analysis ◽  
Weight Status ◽  
Latent Class ◽  
Dietary Habits ◽  
Latent Class Models ◽  
Psychological Status ◽  
Class Analysis ◽  
Weight Control Behaviors ◽  
Obesogenic Behaviors ◽  
Class Models

This study aimed to explore sex-specific latent class models of adolescent obesogenic behaviors (OBs), predictors of latent class membership (LCM), and associations between LCM and weight-related outcomes (i.e., weight status and unhealthy weight control behaviors). We analyzed nationally representative data from the 2019 Korea Youth Risk Behavior Survey. To identify latent classes for boys (n = 29,841) and girls (n = 27,462), we conducted a multiple-group latent class analysis using eight OBs (e.g., breakfast skipping, physical activity, and tobacco product use). Moreover, we performed a multinomial logistic regression analysis and a three-step method to examine associations of LCM with predictors and weight-related outcomes. Among both sexes, the 3-class models best fit the data: (a) mostly healthy behavior class, (b) poor dietary habits and high Internet use class, and (c) poor dietary habits and substance use class. School year, residential area, academic performance, and psychological status predicted the LCM for both sexes. In addition, perceived economic status predicted the LCM for girls. The distribution of weight-related outcomes differed across sex-specific classes. Our findings highlight the importance of developing obesity prevention and treatment interventions tailored to each homogeneous pattern of adolescent OBs, considering differences in their associations with predictors and weight-related outcomes.

scholarly journals Latent Class Analysis in Depression, Including Clinical and Functional Variables: Evidence of a Complex Depressive Subtype in Primary Care in Chile

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Verónica Vitriol ◽  
Alfredo Cancino ◽  
Carlos Serrano ◽  
Soledad Ballesteros ◽  
Marcela Ormazábal ◽  
...  
Keyword(s):  
Latent Class Analysis ◽  
Partner Violence ◽  
Latent Class ◽  
Rating Scale ◽  
Suicide Attempts ◽  
Life Experiences ◽  
Latent Class Models ◽  
Class Analysis ◽  
Multinomial Regression ◽  
Depressed Patients

Objective. To establish differentiated depressive subtypes using a latent class analysis (LCA), including clinical and functional indicators in a sample of depressed patients consulted in Chilean Primary Health Care. Methods. A LCA was performed on a sample of 297 depressed patients consulted in Chilean PHC. The Mini International Neuropsychiatric Interview, the Hamilton Depression Rating Scale, the Outcome Questionnaire -social role, and interpersonal subscales were as instruments. A regression analysis of the different subtypes with sociodemographic and adverse life experiences was performed. Results. In a sample characterized by 87.5% of women, two, three, and four latent class models were obtained. The three-class model likely represents the best clinical implications. In this model, the classes were labeled: “complex depression” (CD) (58% of the sample), “recurrent depression” (RD) (34%), and “single depression episode” (SD) (8%). Members of CD showed a higher probability of history of suicide attempts, interpersonal, and social dysfunction. Psychiatric comorbidities differentiated the RD from SD. According to a multinomial regression model, childhood trauma experiences, recent stressful life experiences, and intimate partner violence events were associated with the CD class ( p < 0.01 ). Limitations. The vast majority of participants were females from Chile and the sample studied was not random. So, the results may not necessarily represent outpatient clinics. Conclusions. This study can provide additional evidence that depression, specifically in female gender, could be better understood as a complex heterogeneous disorder when clinical and functional indicators are studied. Furthermore, adverse life experiences starting in childhood could lead to a differentiated complex depressive subtype.

A study to evaluate patterns of superficial venous reflux in patients with primary chronic venous disease

2014 ◽  
Vol 30 (7) ◽  
pp. 455-461 ◽  
Author(s):  
Mahim I Qureshi ◽  
Manj Gohel ◽  
Louise Wing ◽  
Andrew MacDonald ◽  
Chung S Lim ◽  
...  
Keyword(s):  
Saphenous Vein ◽  
Great Saphenous Vein ◽  
Chronic Venous Disease ◽  
Duplex Ultrasonography ◽  
Venous Disease ◽  
Venous Reflux ◽  
History Of ◽  
Primary Chronic Venous Disease ◽  
Saphenofemoral Junction ◽  
Vein Reflux

Objective This study assessed patterns of superficial reflux in patients with primary chronic venous disease. Methods Retrospective review of all patient venous duplex ultrasonography reports at one institution between 2000 and 2009. Legs with secondary, deep or no superficial reflux were excluded. Results In total, 8654 limbs were scanned; 2559 legs from 2053 patients (mean age 52.3 years) were included for analysis. Great saphenous vein reflux predominated (68%), followed by combined great saphenous vein/small saphenous vein reflux (20%) and small saphenous vein reflux (7%). The majority of legs with competent saphenofemoral junction had below-knee great saphenous vein reflux (53%); incompetent saphenofemoral junction was associated with combined above and below-knee great saphenous vein reflux (72%). Isolated small saphenous vein reflux was associated with saphenopopliteal junction incompetence (61%), although the majority of all small saphenous vein reflux limbs had a competent saphenopopliteal junction (57%). Conclusion Superficial venous reflux does not necessarily originate from a saphenous junction. Large prospective studies with interval duplex ultrasonography are required to unravel the natural history of primary chronic venous disease.

scholarly journals Regularized Latent Class Analysis for Polytomous Item Responses: An Application to SPM-LS Data

2020 ◽  
Author(s):  
Alexander Robitzsch
Keyword(s):  
Latent Class Analysis ◽  
Latent Class ◽  
Latent Class Model ◽  
Simulated Data ◽  
Latent Class Models ◽  
Class Analysis ◽  
Polytomous Item ◽  
Item Responses ◽  
Polytomous Item Responses ◽  
Raven's Standard Progressive Matrices

The last series of Raven's standard progressive matrices (SPM-LS) test were studied with respect to its psychometric properties in a series of recent papers. In this paper, the SPM-LS dataset is analyzed with regularized latent class models (RLCM). For dichotomous item response data, an alternative estimation approach for RLCMs is proposed. For polytomous item responses, different alternatives for performing regularized latent class analysis are proposed. The usefulness of the proposed methods is demonstrated in a simulated data illustration and for the SPM-LS dataset. For the SPM-LS dataset, it turned out the regularized latent class model resulted in five partially ordered latent classes.

scholarly journals 86Segmenting persistently high-cost individuals into actionable groups

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Paul Ronksley ◽  
James Wick ◽  
Dave Campbell ◽  
Reed Beall ◽  
Brenda Hemmelgarn ◽  
...  
Keyword(s):  
Latent Class Analysis ◽  
Latent Class ◽  
Population Level ◽  
Latent Class Models ◽  
Community Dwelling ◽  
Local Context ◽  
Medication Cost ◽  
Class Analysis ◽  
Targeted Interventions ◽  
Clinical Diagnoses

Abstract Background Despite growing evidence describing high cost patients, decision-makers struggle to implement effective strategies to improve care and curb spending in this population. Using a multi-phased approach, we aimed to classify high cost patients into homogeneous subgroups amenable to targeted interventions. Methods We linked population-level administrative health data in Alberta, Canada from 2012-2017. We defined “persistently high-cost” as those in the top 1% of cumulative inpatient, outpatient and medication cost in at least two consecutive years. We used latent class analysis to separate this persistent high-cost population into potentially actionable subgroups. Results Of the 3,795,067 adults residing in Alberta, 21,361 were ‘persistently high-cost’. Latent class models identified 10 high-cost subgroups: individuals with CKD (19.3% of persistent high-cost individuals), those undergoing joint surgery/replacement and rehabilitation (18.6%), individuals with IBD (11.6%), patients receiving biologics for autoimmune conditions (11.3%), patients receiving high cost drugs for other conditions (11.1%), community-dwelling individuals with multimorbid chronic conditions (9.0%), individuals with schizophrenia (6.8%), individuals with other mental health issues (6.2%), rural individuals with COPD (3.4%), and frail elderly in institutional settings (2.7%). Conclusions Latent class analysis was able to identify 10 persistently high-cost groups based on meaningful differences in health care spending, demographics, and clinical diagnoses. Key messages This taxonomy will inform the identification of interventions shown to improve care and reduce cost for each subgroup in addition to consultation with key stakeholders to identify and reflect on key barriers and facilitators to implementing identified interventions within the local context.

scholarly journals How to incentivise doctor attendance in Bangladesh: a latent class analysis of a discrete choice experiment

2021 ◽  
Author(s):  
Blake Angell ◽  
Mushtaq Khan ◽  
Mir Raihanul Islam ◽  
Kate Mandeville ◽  
Nahitun Naher ◽  
...  
Keyword(s):  
Latent Class Analysis ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Latent Class ◽  
Latent Class Models ◽  
Disciplinary Action ◽  
Class Analysis ◽  
Sustainable Solutions ◽  
Incentive Payments

AbstractObjectiveTo elicit preferences of doctors over interventions to address doctor absenteeism in rural facilities in Bangladesh, a pervasive form of corruption across the country.MethodsWe conducted a discrete choice experiment with 308 doctors across four tertiary hospitals in Dhaka, Bangladesh. Four attributes of rural postings were included based on a literature review, qualitative research and a consensus-building workshop with policymakers and key health-system stakeholders: relationship with the community, security measures, attendance-based policies, and incentive payments. Respondents’ choices were analysed with mixed multinomial logistic and latent class models and were used to simulate the likely uptake of jobs under different policy packages.ResultsAll attributes significantly impacted doctor choices (p<0.01). Doctors strongly preferred jobs at rural facilities where there was a supportive relationship with the community (β=0.93), considered good attendance in education and training (0.77) or promotion decisions (0.67), with functional security (0.67) and higher incentive payments (0.5 per 10% increase of base salary). Jobs with disciplinary action for poor attendance were disliked by respondents (-.63). Latent class analysis identified three groups of doctors that differed in their uptake of jobs. Scenario modelling identified intervention packages that differentially impacted doctor behaciour and combinations that could feasibly improve doctors’ attendance.ConclusionBangladeshi doctors have strong but varied preferences over interventions to overcome absenteeism. Some were unresponsive to intervention but a substantial number appear amenable to change. Designing policy packages that consider these differences and target particular doctors could begin to generate sustainable solutions to doctor absenteeism in rural Bangladesh.

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