scholarly journals Síntomas respiratorios: En busca de patrones normales de síntomas en preescolares, escolares y adolescentes

2021 ◽  
pp. 1-2
Author(s):  
Violeta Martínez-Alcántara
Keyword(s):  
General Population ◽  
Respiratory Symptoms ◽  
Latent Profile Analysis ◽  
Latent Class ◽  
Profile Analysis ◽  
Principal Component ◽  
Mixed Effects ◽  
Specific Symptom ◽  
Linear Mixed Effects ◽  
The Family

<b>Aim:</b> To study the pattern of respiratory symptoms in children in the general population. <b>Method:</b> We followed a cohort of children for up to 2 years through parents completing weekly online questionnaires in the Child-Is-Ill study («Kind-en-Ziekmeting» in Dutch); the study was running 2012–2015. Inclusion criteria were «an ordinary child» (according to the parents) and &#x3c;18 years old at inclusion. We especially encouraged participation of post-infancy children. Age at inclusion, sex, smoking exposure, allergy in the family, and frequent infections in the family were noted. Pearson’s correlation, principal component analysis, latent class analysis, latent profile analysis, linear regression, and linear mixed effects regression were used in the statistical analyses. <b>Results:</b> Data were collected on 55,524 childweeks in 755 children (50% girls; median age, 7 years; interquartile range, 4–11 years, 97% ≥2 years at inclusion), with reported symptom(s) in 8,425 childweeks (15%), leading to school absenteeism in 25%, doctor’s visits in 12%, and parental sick leave in 8%; symptoms lasting ≥3 weeks were rare (2% of episodes). Linear mixed effects regression showed significant, but only limited, effects of season on the proportion of «symptom(s) reported» per individual child. Only runny nose showed a significant, but very small, age effect. However, the variability between the children was considerable. There were no obvious subgroups of children with specific symptom combinations. <b>Conclusion:</b> In any randomly chosen week, the vast majority of children (85%) in our – mainly –post-infancy cohort derived from the general population did not have any symptom, even in the younger age group, even in winter. The children showed considerable variability; no clear subgroups of symptom patterns could be identified, underlining the difficult position of healthcare providers. These results support our opinion that post-infancy children in the general population should not be evaluated as if they are infants when they have recurrent respiratory symptoms. If they clearly deviate from the above-described most common pattern, it is wise to keep an eye on potential, maybe even rare, serious underlying causes.

scholarly journals Respiratory Symptoms in Post-infancy Children. A Dutch Pediatric Cohort Study

2020 ◽  
Vol 8 ◽  
Author(s):  
Esther de Vries ◽  
Roeland W. N. M. van Hout
Keyword(s):  
General Population ◽  
Respiratory Symptoms ◽  
Latent Profile Analysis ◽  
Latent Class ◽  
Profile Analysis ◽  
Principal Component ◽  
Mixed Effects ◽  
Specific Symptom ◽  
Linear Mixed Effects ◽  
The Family

Aim: To study the pattern of respiratory symptoms in children in the general population.Method: We followed a cohort of children for up to 2 years through parents completing weekly online questionnaires in the Child-Is-Ill study (“Kind-en-Ziekmeting” in Dutch); the study was running 2012–2015. Inclusion criteria were “an ordinary child” (according to the parents) and &lt;18 years old at inclusion. We especially encouraged participation of post-infancy children. Age at inclusion, sex, smoking exposure, allergy in the family, and frequent infections in the family were noted. Pearson's correlation, principal component analysis, latent class analysis, latent profile analysis, linear regression, and linear mixed effects regression were used in the statistical analyses.Results: Data were collected on 55,524 childweeks in 755 children (50% girls; median age, 7 years; interquartile range, 4–11 years, 97% ≥2 years at inclusion), with reported symptom(s) in 8,425 childweeks (15%), leading to school absenteeism in 25%, doctor's visits in 12%, and parental sick leave in 8%; symptoms lasting ≥3 weeks were rare (2% of episodes). Linear mixed effects regression showed significant, but only limited, effects of season on the proportion of “symptom(s) reported” per individual child. Only runny nose showed a significant, but very small, age effect. However, the variability between the children was considerable. There were no obvious subgroups of children with specific symptom combinations.Conclusion: In any randomly chosen week, the vast majority of children (85%) in our—mainly—post-infancy cohort derived from the general population did not have any symptom, even in the younger age group, even in winter. The children showed considerable variability; no clear subgroups of symptom patterns could be identified, underlining the difficult position of healthcare providers. These results support our opinion that post-infancy children in the general population should not be evaluated as if they are infants when they have recurrent respiratory symptoms. If they clearly deviate from the above-described most common pattern, it is wise to keep an eye on potential, maybe even rare, serious underlying causes.

Patterns of stigma toward schizophrenia among the general population: A latent profile analysis

2013 ◽  
Vol 60 (6) ◽  
pp. 595-605 ◽  
Author(s):  
Alexandre A Loch ◽  
Yuan-Pang Wang ◽  
Francisco B Guarniero ◽  
Fabio L Lawson ◽  
Michael P Hengartner ◽  
...  
Keyword(s):  
General Population ◽  
Latent Profile Analysis ◽  
Profile Analysis ◽  
Latent Profile

scholarly journals Phenotyping Chronic Pelvic Pain Based on Latent Class Modeling of Physical Examination

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
B. W. Fenton ◽  
S. F. Grey ◽  
M. Reichenbach ◽  
M. McCarroll ◽  
V. Von Gruenigen
Keyword(s):  
Physical Examination ◽  
Pelvic Pain ◽  
Chronic Pelvic Pain ◽  
Latent Profile Analysis ◽  
Latent Class ◽  
Profile Analysis ◽  
Wall Region ◽  
Uterosacral Ligaments ◽  
Pain Pressure Threshold ◽  
Latent Profile

Introduction. Defining clinical phenotypes based on physical examination is required for clarifying heterogeneous disorders such as chronic pelvic pain (CPP). The objective of this study was to determine the number of classes within 4 examinable regions and then establish threshold and optimal exam criteria for the classes discovered. Methods. A total of 476 patients meeting the criteria for CPP were examined using pain pressure threshold (PPT) algometry and standardized numeric scale (NRS) pain ratings at 30 distinct sites over 4 pelvic regions. Exploratory factor analysis, latent profile analysis, and ROC curves were then used to identify classes, optimal examination points, and threshold scores. Results. Latent profile analysis produced two classes for each region: high and low pain groups. The optimal examination sites (and high pain minimum thresholds) were for the abdominal wall region: the pair at the midabdomen (PPT threshold depression of > 2); vulvar vestibule region: 10:00 position (NRS > 2); pelvic floor region: puborectalis (combined NRS > 6); vaginal apex region: uterosacral ligaments (combined NRS > 8). Conclusion. Physical examination scores of patients with CPP are best categorized into two classes: high pain and low pain. Standardization of the physical examination in CPP provides both researchers and general gynecologists with a validated technique.

scholarly journals Basic Reproduction Number of the 2019 Novel Coronavirus Disease in the Major Endemic Areas of China: A Latent Profile Analysis

2021 ◽  
Vol 9 ◽  
Author(s):  
Honglv Xu ◽  
Yi Zhang ◽  
Min Yuan ◽  
Liya Ma ◽  
Meng Liu ◽  
...  
Keyword(s):  
Basic Reproduction Number ◽  
Latent Profile Analysis ◽  
Latent Class ◽  
Reproduction Number ◽  
Profile Analysis ◽  
Hunan Province ◽  
Initial Value ◽  
Endemic Areas ◽  
Novel Coronavirus ◽  
Latent Profile

Objective: The aim of this study is to analyze the latent class of basic reproduction number (R0) trends of the 2019 novel coronavirus disease (COVID-19) in the major endemic areas of China.Methods: The provinces that reported more than 500 cases of COVID-19 till February 18, 2020 were selected as the major endemic areas. The Verhulst model was used to fit the growth rate of cumulative confirmed cases. The R0 of COVID-19 was calculated using the parameters of severe acute respiratory syndrome (SARS) and COVID-19. The latent class of R0 was analyzed using the latent profile analysis (LPA) model.Results: The median R0 calculated from the SARS and COVID-19 parameters were 1.84–3.18 and 1.74–2.91, respectively. The R0 calculated from the SARS parameters was greater than that calculated from the COVID-19 parameters (Z = −4.782 to −4.623, p &lt; 0.01). Both R0 can be divided into three latent classes. The initial value of R0 in class 1 (Shandong Province, Sichuan Province, and Chongqing Municipality) was relatively low and decreased slowly. The initial value of R0 in class 2 (Anhui Province, Hunan Province, Jiangxi Province, Henan Province, Zhejiang Province, Guangdong Province, and Jiangsu Province) was relatively high and decreased rapidly. Moreover, the initial R0 value of class 3 (Hubei Province) was in the range between that of classes 1 and 2, but the higher R0 level lasted longer and decreased slowly.Conclusion: The results indicated that the overall R0 trend is decreased with the strengthening of comprehensive prevention and control measures of China for COVID-19, however, there are regional differences.

scholarly journals Latent Profile Analyses of Depressive Symptoms in Younger and Older Oncology Patients

Assessment ◽  
2018 ◽  
Vol 27 (7) ◽  
pp. 1383-1398 ◽  
Author(s):  
Rebecca M. Saracino ◽  
Heining Cham ◽  
Barry Rosenfeld ◽  
Christian J. Nelson
Keyword(s):  
Depressive Symptoms ◽  
Older Patients ◽  
Latent Profile Analysis ◽  
Latent Class ◽  
Profile Analysis ◽  
Depression Scale ◽  
Epidemiological Studies ◽  
Class Differences ◽  
Patients With Cancer ◽  
Latent Profile

The aging of America will include a significant increase in the number of older patients with cancer, many of whom will experience significant depressive symptoms. Although geriatric depression is a well-studied construct, its symptom presentation in the context of cancer is less clear. Latent profile analysis was conducted on depressive symptoms in younger (40-64 years) and older (≥65 years) patients with cancer ( N = 636). The sample was clinically heterogeneous (i.e., included all stages, dominated by advanced stage disease). Participants completed questionnaires including the Center for Epidemiological Studies Depression Scale, which was used for the latent profile analysis. A four-class pattern was supported for each age group. However, the four-class pattern was significantly different between the younger and older groups in terms of the item means within each corresponding latent class; differences were primarily driven by severity such that across classes, older adults endorsed milder symptoms. An unexpected measurement issue was uncovered regarding reverse-coded items, suggesting that they may generate unreliable scores on the Center for Epidemiological Studies Depression Scale for a significant subset of patients. The results indicate that cancer clinicians can expect to see depressive symptoms along a continuum of severity for patients of any age, with less severe symptoms among older patients.

Multilevel Latent Class Profile Analysis: An Application to Stage-Sequential Patterns of Alcohol Use in a Sample of Canadian Youth

2021 ◽  
Vol 44 (1) ◽  
pp. 50-60
Author(s):  
Yunah Lee ◽  
Youngsun Kim ◽  
Scott T. Leatherdale ◽  
Hwan Chung
Keyword(s):  
Latent Class ◽  
Profile Analysis ◽  
Heavy Drinking ◽  
Sequential Patterns ◽  
Drinking Patterns ◽  
Canadian Youth ◽  
The Family ◽  
Drinking Behaviors ◽  
Using Data ◽  
Health Canada

Recently, latent class analysis (LCA) and its variants have been proposed to identify subgroups of individuals who follow similar sequential patterns of latent class membership for longitudinal study. A primary assumption underlying the family of LCA is that individual observations are independent. In many applications, however, particularly in research on adolescent substance use, individuals are often dependent because of multilevel data structure, where the unit of observation (e.g., students) is nested in higher level units (e.g., schools). In this study, we propose multilevel latent class profile analysis (MLCPA), which will allow us to analyze the longitudinal data with a multilevel structure under the framework of LCA. We apply an MLCPA using data from the COMPASS study, a 9-year study funded by the Canadian Institutes of Health Research and Health Canada, in order to identify representative sequential drinking patterns of Canadian youth and investigate whether these sequential patterns vary across schools. The MLCPA identified three common student-level drinking behaviors: non-drinker, ever lifetime, and binge drinker. The sequence of drinking behaviors can be classified into one of three longitudinal sequential patterns: non-drinking stayer, light drinking advancer, and heavy drinking advancer. In addition, MLCPA uncovered two latent clusters ( low-use school and high-use school) out of 64 schools in Ontario and Alberta based on the prevalences of sequential drinking patterns.

scholarly journals Heterogeneity of social anxiety in treatment-seeking adults who stutter: A latent profile analysis

2021 ◽  
Author(s):  
Tomosumi Haitani ◽  
Naomi Sakai ◽  
Koichi Mori ◽  
Tomohito Houjou
Keyword(s):  
Social Anxiety ◽  
Latent Profile Analysis ◽  
Latent Class ◽  
Profile Analysis ◽  
Demographic Data ◽  
Data Communication ◽  
Anxiety Scale ◽  
Situational Factors ◽  
Adults Who Stutter ◽  
Latent Profile

Purpose: Adults who stutter (AWS) often experience social anxiety. Social anxiety is explained by several situational factors, one of which is a factor for telephone, which is unique to AWS. This unique social anxiety, which has not been observed in individuals with social anxiety disorder (SAD), may lead to heterogeneity or distinct subtypes of AWS. The present study aimed to investigate the heterogeneity of social anxiety in AWS in terms of feared social situations.Methods: Social anxiety was measured using the fear/anxiety scale of the Liebowitz Social Anxiety Scale (LSAS). The scores of the five subscales in the LSAS in 562 AWS were analyzed using latent profile analysis. First, the number of latent classes (subtypes) was determined through statistical criteria and interpretability. Next, the profiles of social anxiety, demographic data, communication attitudes, and the overall severity of social anxiety of the subtypes were investigated.Results: Five latent class solutions led to good classifications. About one-quarter of AWS (156) were included in a subtype with sub-clinical levels of overall severity of social anxiety but severe social anxiety in telephone situations. Among them, 100 AWS showed severe social anxiety only in telephone situations. Psychosocial factors, including employment status and communication attitude, were related to extracted subtypes.Conclusions: Some AWS have severe social anxiety specific to telephone situations, which is not proportional to the overall severity of social anxiety. The telephone-specific subtype of social anxiety has not been empirically extracted in principal diagnosis of SAD and can be unique in AWS.

Conceptualizations of the Family Context: New Insights Gained by Capturing Daily Variability in Cohesion and Conflict

2019 ◽  
Author(s):  
David M. Lydon-Staley ◽  
Emily J. LoBraico ◽  
Bethany C. Bray ◽  
Gregory Fosco
Keyword(s):  
Problem Behaviors ◽  
Family Conflict ◽  
Internalizing Symptoms ◽  
Family Cohesion ◽  
Latent Profile Analysis ◽  
Profile Analysis ◽  
Well Being ◽  
Family Context ◽  
The Family

In this study, we evaluate whether the use of dynamic characteristics of the family provides new and important information when conceptualizing the family context of adolescents. Using 21 days of daily diary data from adolescents (N=151; 61.59% female; mean age = 14.60 years) in two-caregiver households, we quantified between-family differences in the extent to which their experiences of family cohesion and conflict fluctuate from day to day. We included these estimates of consistency in family cohesion and conflict, along with traditional survey assessments of dispositional family cohesion and conflict, in a latent profile analysis to identify subgroups of families with distinct combinations of dispositional and consistency in family cohesion and conflict. We next assessed how these profiles were differentially associated with emotion regulation, internalizing symptoms, problem behaviors, and well-being at baseline and at a 12-month follow-up. Results revealed four distinct family profiles with unique associations with outcomes. By considering both dispositional and consistency in family cohesion and family conflict and how these four factors cluster within families to differing degrees, we better capture the richness of the family context and highlight the implications for understanding its role in adolescent well-being.

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