scholarly journals Toward understanding the impact of mHealth features for people with HIV: a latent class analysis of PositiveLinks usage

2019 ◽  
Author(s):  
Chelsea E Canan ◽  
Tabor E Flickinger ◽  
Marika Waselewski ◽  
Alexa Tabackman ◽  
Logan Baker ◽  
...  
Keyword(s):  
Latent Class Analysis ◽  
Clinical Outcomes ◽  
Viral Suppression ◽  
Latent Class ◽  
Class Analysis ◽  
Ryan White ◽  
Usage Patterns ◽  
Community Board ◽  
Living With Hiv ◽  
The Impact

Abstract PositiveLinks (PL) is a multi-feature smartphone-based platform to improve engagement-in-care and viral suppression (VS) among clinic patients living with HIV. Features include medication reminders, mood/stress check-ins, a community board, and secure provider messaging. Our goal was to examine how PL users interact with the app and determine whether usage patterns correlate with clinical outcomes. Patients (N = 83) at a university-based Ryan White clinic enrolled in PL from June 2016 to March 2017 and were followed for up to 12 months. A subset (N = 49) completed interviews after 3 weeks of enrollment to explore their experiences with and opinions of PL. We differentiated PL members based on 6-month usage of app features using latent class analysis. We explored characteristics associated with class membership, compared reported needs and preferences by class, and examined association between class and VS. The sample of 83 PL members fell into four classes. “Maximizers” used all app features frequently (27%); “Check-in Users” tended to interact only with daily queries (22%); “Moderate All-Feature Users” used all features occasionally (33%); and “As-Needed Communicators” interacted with the app minimally (19%). VS improved or remained high among all classes after 6 months. VS remained high at 12 months among Maximizers (baseline and 12-month VS: 100%, 94%), Check-in Users (82%, 100%), and Moderate All-Feature Users (73%, 94%) but not among As-Needed Communicators (69%, 60%). This mixed-methods study identified four classes based on PL usage patterns that were distinct in characteristics and clinical outcomes. Identifying and characterizing mHealth user classes offers opportunities to tailor interventions appropriately based on patient needs and preferences as well as to provide targeted alternative support to achieve clinical goals.

scholarly journals Identifying patterns of retention in care and viral suppression using latent class analysis among women living with HIV in Florida 2015–2017

AIDS Care ◽  
2020 ◽  
Vol 33 (1) ◽  
pp. 131-135
Author(s):  
Rahel Dawit ◽  
Diana M. Sheehan ◽  
Semiu O. Gbadamosi ◽  
Kristopher P. Fennie ◽  
Tan Li ◽  
...  
Keyword(s):  
Latent Class Analysis ◽  
Viral Suppression ◽  
Latent Class ◽  
Retention In Care ◽  
Class Analysis ◽  
Women Living With Hiv ◽  
Living With Hiv

scholarly journals Comorbidity phenotypes and risk of mortality in patients with ischaemic heart disease in the UK

Heart ◽  
2020 ◽  
Vol 106 (11) ◽  
pp. 810-816 ◽  
Author(s):  
Francesca Crowe ◽  
Dawit T Zemedikun ◽  
Kelvin Okoth ◽  
Nicola Jaime Adderley ◽  
Gavin Rudge ◽  
...  
Keyword(s):  
Heart Disease ◽  
Latent Class Analysis ◽  
Ischaemic Heart Disease ◽  
Latent Class ◽  
Health Improvement ◽  
Class Analysis ◽  
Musculoskeletal Conditions ◽  
Risk Of Mortality ◽  
The Uk ◽  
The Impact

ObjectivesThe objective of this study is to use latent class analysis of up to 20 comorbidities in patients with a diagnosis of ischaemic heart disease (IHD) to identify clusters of comorbidities and to examine the associations between these clusters and mortality.MethodsLongitudinal analysis of electronic health records in the health improvement network (THIN), a UK primary care database including 92 186 men and women aged ≥18 years with IHD and a median of 2 (IQR 1–3) comorbidities.ResultsLatent class analysis revealed five clusters with half categorised as a low-burden comorbidity group. After a median follow-up of 3.2 (IQR 1.4–5.8) years, 17 645 patients died. Compared with the low-burden comorbidity group, two groups of patients with a high-burden of comorbidities had the highest adjusted HR for mortality: those with vascular and musculoskeletal conditions, HR 2.38 (95% CI 2.28 to 2.49) and those with respiratory and musculoskeletal conditions, HR 2.62 (95% CI 2.45 to 2.79). Hazards of mortality in two other groups of patients characterised by cardiometabolic and mental health comorbidities were also higher than the low-burden comorbidity group; HR 1.46 (95% CI 1.39 to 1.52) and 1.55 (95% CI 1.46 to 1.64), respectively.ConclusionsThis analysis has identified five distinct comorbidity clusters in patients with IHD that were differentially associated with risk of mortality. These analyses should be replicated in other large datasets, and this may help shape the development of future interventions or health services that take into account the impact of these comorbidity clusters.

Patterns of substance use and arrest among hospitalized people living with HIV: A latent class analysis

2017 ◽  
Vol 171 ◽  
pp. e189-e190 ◽  
Author(s):  
Karen Shiu ◽  
Ahnalee Marie Brincks ◽  
Daniel J. Feaster ◽  
Jemima A. Frimpong ◽  
Lauren Gooden ◽  
...  
Keyword(s):  
Substance Use ◽  
Latent Class Analysis ◽  
Latent Class ◽  
People Living With Hiv ◽  
Class Analysis ◽  
Living With Hiv

scholarly journals Using Latent Class Analysis to Identify Different Risk Patterns for Patients With Masked Hypertension

2021 ◽  
Vol 8 ◽  
Author(s):  
Ming Fu ◽  
Xiangming Hu ◽  
Shixin Yi ◽  
Shuo Sun ◽  
Ying Zhang ◽  
...  
Keyword(s):  
High Risk ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Latent Class Model ◽  
Fasting Blood Glucose ◽  
Low Risk ◽  
Biological Information ◽  
Masked Hypertension ◽  
Class Analysis ◽  
The Impact

Background: There is controversy whether masked hypertension (MHT) requires additional intervention. The aim of this study is to evaluate whether MHT accompanied with high-risk metabolic syndrome (MetS), as the subphenotype, will have a different prognosis from low-risk MetS.Methods: We applied latent class analysis to identify subphenotypes of MHT, using the clinical and biological information collected from High-risk Cardiovascular Factor Screening and Chronic Disease Management Programme. We modeled the data, examined the relationship between subphenotypes and clinical outcomes, and further explored the impact of antihypertensive medication.Results: We included a total of 140 patients with MHT for analysis. The latent class model showed that the two-class (high/low-risk MetS) model was most suitable for MHT classification. The high-risk MetS subphenotype was characterized by larger waist circumference, lower HDL-C, higher fasting blood glucose and triglycerides, and prevalence of diabetes. After four years of follow-up, participants in subphenotype 1 had a higher non-major adverse cardiovascular event (MACE) survival probability than those in subphenotype 2 (P = 0.016). There was no interaction between different subphenotypes and the use of antihypertensive medications affecting the occurrence of MACE.Conclusions: We have identified two subphenotypes in MHT that have different metabolic characteristics and prognosis, which could give a clue to the importance of tracing the clinical correlation between MHT and metabolic risk factors. For patients with MHT and high-risk MetS, antihypertensive therapy may be insufficient.

Stretched Earlobe Piercings Negatively Impact Casual Observer Perceptions

2019 ◽  
Vol 35 (03) ◽  
pp. 299-305
Author(s):  
Nicholas Fung ◽  
Masaru Ishii ◽  
Pauline Huynh ◽  
Michelle Juarez ◽  
Kristin Bater ◽  
...  
Keyword(s):  
Latent Class Analysis ◽  
Web Sites ◽  
Latent Class ◽  
Social Stigma ◽  
Public Access ◽  
Class Analysis ◽  
Bootstrap Analysis ◽  
Casual Observer ◽  
Body Modifications ◽  
The Impact

AbstractPatients with stretched earlobes seek reconstruction to mitigate social stigma. To date, there have been no studies measuring the impact of stretched earlobe piercings on casual observer perceptions. One-hundred seventy-three casual observers were enrolled via public-access web sites. Participants were randomly shown frontal and profile views of six subjects with stretched earlobe piercings and four controls. Participants evaluated photos for first impressions using a survey containing choices regarding personal attributes. Latent class analysis was performed to categorize observer ratings. Analysis of variance (ANOVA), bootstrap analysis, and permutations testing were used to evaluate the relationship between perceived attractiveness, success, and approachability scoring and stretched earlobe status. Latent class analysis categorized responses into three classes: positive, negative, and neutral. Patients with stretched earlobe piercings were significantly less likely to be classified as positive by observers without body modifications (i.e., tattoos and piercings) in comparison to control photos (30.9 and 40.1%, p = 0.007) and more likely to be classified as negative (38.5 and 28.1%, p = 0.002). These changes were abolished when photos were evaluated by observers with body modifications (p > 0.05). ANOVA revealed that stretched earlobe piercings and observer body modification status have a significant effect on rated approachability (F [1,1726] = 4.08, p = 0.04) and successfulness (F[1,1726] = 9.67, p = 0.002; F [1,1726] = 70.33, p < 0.0005). No significance was found for rated attractiveness (p > 0.05). Patients with stretched earlobe piercings were more likely to be classified as having negative affect display and being less approachable and successful compared with controls when evaluated by observers without body modifications. This effect was abolished when photos were evaluated by observers with body modifications. These findings validate patient motivations for seeking stretched earlobe repair.

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