Using Latent Class Analysis to Identify Different Clinical Profiles Among Patients With Advanced Heart Failure

Blum, Moritz; McKendrick, Karen; Gelfman, Laura P.; Pinney, S.; Goldstein, Nathan E.

doi:10.1016/j.jpainsymman.2022.10.011

Cited by 8 publications

(3 citation statements)

References 43 publications

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“…Estimation of individual part-worth utilities for the choice-based conjoint analysis was conducted using the ChoiceModelR package [53] in RStudio (Version 1.1.456) using the Hierarchical Bayes Estimation approach. A latent class cluster analysis (LCA) with age and sex as covariates was used to identify groups of individuals based on the three core dimensions of food-related lifestyles.. To carry out the latent class analysis, we used the gsem [54] function from the STATA software environment (StataCorp LLC, College Station, TX, USA), Version 17.0. To analyse differences between clusters in their sociodemographic characteristics, non-core dimensions of food-related lifestyles, and health characteristics, the chi-square test and an analysis of variance were used.…”

Section: Discussionmentioning

confidence: 99%

Consumers’ Preferences towards Bread Characteristics Based on Food-Related Lifestyles: Insights from Slovenia

Kušar,

Pravst,

Pivk Kupirovič

et al. 2023

Foods

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Consumers’ recognition and understanding of food characteristics can have an important role when making purchase decisions. The current study analysed consumer preferences for bread, an important food in the diets of Central European countries. The study included a conjoint experiment on a representative sample of 547 adult consumers in Slovenia. The following bread attributes: functional ingredients (chia seeds, linseed, quinoa, and Tartary buckwheat); nutritional claims (low salt, high fibre, and high protein); and other claims (organic, free from additives, flour from Slovenia, and wholegrain) were studied. The results showed the strongest relative importance for functional ingredients (a mean relative importance of 83.9%). In addition, a deeper insight into consumer preference was investigated by a recently developed modular instrument for food-related lifestyles. Latent class cluster analysis (LCA) enabled the identification of four consumer segments (uninvolved, conservative, health-conscious, and moderate) with different preferences toward selected functional ingredients, nutrition, and other claims. The results provide insights that allow for a better understanding of consumer preferences for functional ingredients and claims, and new perspectives for bread marketing to different consumer segments based on food-related lifestyles. Identifying the drivers that affect bread purchasing and consumption can support reformulation activities and product promotion in the direction of reinforcing healthier food choices.

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Section: Discussionmentioning

confidence: 99%

Consumers’ Preferences towards Bread Characteristics Based on Food-Related Lifestyles: Insights from Slovenia

Kušar,

Pravst,

Pivk Kupirovič

et al. 2023

Foods

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“…This method maximizes differences between categories while minimizing differences within categories (Mori et al., 2020). LCA is widely applied in fields such as identifying psychological health issues like anxiety and depression in populations, as well as chronic diseases like stroke and heart failure (Blum et al., 2023; Clancy et al., 2023; Liu, Liu, et al., 2021).…”

Section: Introductionmentioning

confidence: 99%

Latent class analysis of the sleep quality of night shift nurses and impact of shift‐related factors on the occupational stress and anxiety

Yuan,

Fang

2024

Journal of Advanced Nursing

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AimsThe objective of this study is to explore the various latent categories within the sleep quality of night shift nurses and to investigate whether shift‐related factors predispose nurses to higher levels of occupational stress and anxiety.DesignThis is a cross‐sectional study.MethodsFrom November to December 2020, registered nurses from 18 tertiary hospitals and 16 secondary hospitals in Chongqing were selected through convenience sampling for this study. Latent class analysis was used to investigate the sleep quality of nurses working night shifts. Furthermore, univariate analysis and logistic multivariate analysis were utilized to identify the contributing factors to occupational stress and anxiety.ResultsThe four latent categories of Pittsburgh Sleep Quality Index for night shift nurses were identified as ‘Low Sleep Disorder Group’ (56.34%), ‘Moderate Sleep Disorder Group’ (37.27%), ‘High Sleep Disorder Non‐Reliant on Sleeping medication Group’ (4.89%) and ‘High Sleep Disorder Reliant on Sleeping medication Group’ (1.50%). The results showed that having a night‐shift frequency of 3–4 times per month, night‐shift durations of 9–12 h, sleep time delay after night shift (≥2 h), total sleep time after night shift less than 4 h were shift‐related factors that increased the levels of occupational stress and anxiety.ConclusionThe sleep quality of night shift nurses demonstrates heterogeneity and can be classified into four latent categories. Higher frequency of night shifts, extended work hours and insufficient rest time are all associated with increased levels of occupational stress and anxiety.ImpactBy identifying the four latent categories of sleep quality among night shift nurses, this study sheds light on the relationship between sleep patterns and levels of occupational stress and anxiety. These findings have important implications for healthcare institutions in the management of nurse well‐being and work schedules.Patient or Public ContributionNo patient or public contribution.

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“…By exploring how these burdens overlap, clinicians can better provide person-centered care for subgroups with overlapping burdens. 5 For example, depending on the overlapping burdens, specific patient subgroups may benefit from tailoring symptom and medication management, focusing on physical and occupational therapy to improve functional limitations, and inquiring about potential associated social and home needs.…”

Section: Introductionmentioning

confidence: 99%

Phenotypes of Symptom, Function, and Medication Burden in Older Adults with Nondialysis Advanced Kidney Disease

Ma,

Berkowitz,

Olsen

et al. 2023

Kidney360

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Background: Older adults with advanced chronic kidney disease (CKD, stages 4 and 5) have significant symptoms, polypharmacy, and functional difficulties and prior studies evaluated these burdens separately. Identifying subgroups with similar patterns of burdens could help clinicians optimize care for these individuals. Methods: We conducted a secondary analysis of 377 older participants (≥ 70 years old) with stage 4 and 5 CKD at high risk of hospitalization enrolled in a national Veterans Affairs (VA) prospective cohort study. Adults on dialysis or with prior kidney transplant were excluded. We used latent class analysis (LCA) to identify participants with similar patterns across symptoms, medication burden, and function. Sixteen variables were included: symptoms (anxiety, depression, appetite, pain, shortness of breath, fatigue, dizziness, leg weakness, constipation, stiffness using the Symptom Burden Score), polypharmacy (≥ 10 medications and potentially inappropriate medications), and function (activities of daily living (ADL), physical and cognitive instrumental activities of daily living (IADLs), falls in the last year). We also compared 12 month hospitalization and mortality between the three classes. Results: Three classes of participants with similar functional impairment, medication burden, and symptom phenotypes were identified. The largest participant class (N=208) primarily had difficulties with physical IADLs and polypharmacy. The second participant class (N=99) had shortness of breath, constipation, and dizziness. The third participant class (N=70) had complex needs with daily pain, psychological symptoms (anxiety and depression), functional limitations (ADLs and physical and cognitive IADLs), and polypharmacy. The three classes had significantly different levels of comorbidities, financial stress, and social support. There were no significant differences in mortality and hospitalization among the three classes. Conclusion: There are distinct classes of older adults with advanced CKD who have physical and psychological symptoms, functional impairment, and medication burden. Tailoring care for this population should include a multidisciplinary team to address these overlapping symptoms, medication, and functional needs.

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Using Latent Class Analysis to Identify Different Clinical Profiles Among Patients With Advanced Heart Failure

Cited by 8 publications

References 43 publications

Consumers’ Preferences towards Bread Characteristics Based on Food-Related Lifestyles: Insights from Slovenia

Consumers’ Preferences towards Bread Characteristics Based on Food-Related Lifestyles: Insights from Slovenia

Latent class analysis of the sleep quality of night shift nurses and impact of shift‐related factors on the occupational stress and anxiety

Phenotypes of Symptom, Function, and Medication Burden in Older Adults with Nondialysis Advanced Kidney Disease

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