Application of latent class analysis in assessing the awareness, attitude, practice and satisfaction of paediatricians on sleep disorder management in children in Italy

Nosetti, Luana; Paglietti, Maria Giovanna; Brunetti, L.; Masini, Luigi; Grutta, Stefania La; Cilluffo, Giovanna; Ferrante, Giuliana; Zaffanello, Marco; Verrillo, Elisabetta; Pavone, Martino; Niespolo, Alessandra Cristina; Broggi, Giacomo; Cutrera, Renato

doi:10.1371/journal.pone.0228377

Cited by 11 publications

(7 citation statements)

References 45 publications

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“…The above person-centered approach is an effective psychometric method when the latent variable in question is categorical [54][55][56]. The participant can be classified into distinct categories, bearing similar perceptions, attitudes, or mental structures.…”

Section: Scope and Research Questionsmentioning

confidence: 99%

Attitudes towards the Use of Educational Robotics: Exploring Pre-Service and In-Service Early Childhood Teacher Profiles

et al. 2021

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The introduction of STEM education, and specifically the implementation of educational robotics (ER), has drawn researchers’ attention and has shown that teachers play a crucial role in leading this innovation. The present study concerns in-service and pre-service early childhood teachers, focusing on their perceptions and attitudes about ER use in daily teaching practice. The data were collected via a questionnaire (N = 201) and explored using latent class analysis, which detected distinct clusters/profiles of participants based on their pattern of responses. Two clusters were identified: Cluster1 was relatively homogeneous, including those who share a positive attitude towards ER, while Cluster2 was heterogeneous, comprising participants with inconsistent responses and expressing negative and skeptical thinking. The cluster memberships were associated with external covariates, such as age, years of teaching experience, and variables measuring their technological competencies. The results showed that teaching experience and age were negatively associated with cluster1-membership, while educational robotics knowledge was positively associated. The findings are interpretable, and the implications for education are discussed considering the current literature.

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Section: Scope and Research Questionsmentioning

confidence: 99%

Attitudes towards the Use of Educational Robotics: Exploring Pre-Service and In-Service Early Childhood Teacher Profiles

et al. 2021

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“…Of note, a multidimensional approach has proven to be more effective in clarifying the intrinsic heterogeneity of other respiratory disorders such as asthma and wheezing in childhood. In this context, clustering statistical methods are suitable for categorizing a heterogeneous population into subpopulations who share some aspects of a disease [12]. In particular, Latent Class Analysis (LCA) is a "hypothesis-free" approach, which assigns patients to classes based on their homogeneous characteristics, rather than them being arbitrarily assigned to classes by the researchers [13].…”

Section: Introductionmentioning

confidence: 99%

Identification of bronchiolitis profiles in Italian children through the application of latent class analysis

et al. 2020

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Background Bronchiolitis is the primary infection of the lower respiratory tract in children under 2 years of age. Although it is generally considered a single nosological entity, recent studies suggested remarkable clinical heterogeneity. To date, no studies have identified classes of children with bronchiolitis within the Italian population. This study aimed to identify discrete profiles of Italian children hospitalized with bronchiolitis using a clustering approach and to compare findings with those obtained in international cohorts. Methods This was a retrospective single-centre study conducted on children aged ≤2 years hospitalised with bronchiolitis (n = 401) at the Department of Infectious Diseases and the University Department of General Pediatrics in “Giovanni Di Cristina” Pediatric Hospital of Palermo, Italy, between November 2012 and May 2019. Bronchiolitis profiles were determined by latent class analysis, classifying children based on clinical characteristics at admission and viral aetiology. Results Three profiles were identified. Class 1 (49%) was composed of 45% male children; all children were aged ≤6 months at hospitalization; 77% were infected with RSV; 100% had respiratory distress, 11% had apnea and none had cough. Class 2 (77%) was mainly composed of male subjects (51%); 19% were aged > 6 months at admission; 37% were infected with RSV; 12% had respiratory distress, 5% had apnea and 90% had cough. Class 3 (19%) included the largest proportion of male subjects (94%) and was mostly composed of children aged > 6 months at the time of admission (68%); 70% had cough, 12% showed respiratory distress and none presented with apnoea. Children in Class 1 were more frequently born near the epidemic season (p = 0.028); breastfeeding duration was significantly longer for children in Class 3 (p = 0.004). Conclusions The study identified distinct clinical profiles of bronchiolitis by a clustering approach in a single-centre study of children hospitalised for bronchiolitis in Italy. The three bronchiolitis profiles share some similarities with those identified in international studies using the same statistical approach. These findings may help to increase the understanding of the phenotypic variability that typically characterizes bronchiolitis, with relevant implications for future research.

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“…The current study reports data from the first part of the project. The use of a data-driven approach, such as latent class analysis (LCA), would be helpful at this purpose by assigning respondents into classes based on their responses to questionnaire items, without any interference from the researcher (14)(15)(16).…”

Section: Introductionmentioning

confidence: 99%

Barriers and incentives for Italian paediatricians to become smoking cessation promoters: a GARD-Italy Demonstration Project

et al. 2020

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Background: Paediatricians rarely devote any time to screening and treatment for parental tobacco use. The present project is part of a Global Alliance against Chronic Respiratory Diseases (GARD)-Italy Demonstration Project, aimed to increase the skills of primary care physicians and paediatricians as "promoter of smoking cessation". The aims of this study were: (I) to identify latent classes of barriers and incentives for smoking cessation counseling among paediatricians using latent class analysis (LCA); (II) to investigate risk factors for inclusion into the identified classes.Methods: In 2018, 1,500 Italian paediatricians were invited to complete an online survey on passive smoke exposure in children. LCA was used to discover underlying response patterns, and to identify respondent groups with similar attitudes toward passive smoke exposure in children. Multinomial logistic regression helped investigate which explanatory variables influenced inclusion into a class. A P value <0.05 was considered significant.Results: The overall response rate was 71% (n=1,071/1,500). Three classes were identified: Class 1 "passive" (n=226, 21.10%); Class 2 "unmotivated" (n=124, 11.58%); and Class 3 "proactive" (n=721, 67.32%).Assuming Class 3 as reference, ever having been a smoker was borderline associated (P=0.052) with increased probability of inclusion into Class 1 (OR =1.43, 95% CI, 1.00-2.06). Having 6-15 or ≥15 years of work experience versus having less than five years was associated with decreased probability of being in the "passive" class (OR =0.46, 95% CI, 0.22-0.96 and OR =0.49, 95% CI, 0.27-0.87, respectively), as was discussing parents' addiction to alcohol/drugs (OR =0.50, 95% CI, 0.33-0.76). Conclusions: We identified three profiles among Italian paediatricians related to barriers and incentives for smoking cessation promotion. Tailored educational interventions for paediatricians are required to promote smoking cessation programs.

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Application of latent class analysis in assessing the awareness, attitude, practice and satisfaction of paediatricians on sleep disorder management in children in Italy

Cited by 11 publications

References 45 publications

Attitudes towards the Use of Educational Robotics: Exploring Pre-Service and In-Service Early Childhood Teacher Profiles

Attitudes towards the Use of Educational Robotics: Exploring Pre-Service and In-Service Early Childhood Teacher Profiles

Identification of bronchiolitis profiles in Italian children through the application of latent class analysis

Barriers and incentives for Italian paediatricians to become smoking cessation promoters: a GARD-Italy Demonstration Project

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