The Impact of Promotion and Advertising: A Latent Class Approach

2000 ◽  
Vol 32 (3) ◽  
pp. 441-457 ◽  
Author(s):  
Timothy J. Richards
Keyword(s):  
Latent Class Analysis ◽  
Latent Class ◽  
Demographic Characteristics ◽  
Class Analysis ◽  
Market Segments ◽  
Segment Model ◽  
Analysis Technique ◽  
Marketing Activities ◽  
Marketing Variables ◽  
The Impact

AbstractTypically, marketers define market segments by their demographic characteristics, assuming that these segments represent consumers with relatively homogeneous buying patterns. A more managerially useful definition, however, groups consumers of similar behavior directly and then seeks to find demographic commonalities among them. This study uses a latent class analysis technique to segment consumers based on their responsiveness to a set of marketing variables, finding that a multiple-segment model provides a better fit to the data, and that these segments differ significantly in their responsiveness. By targeting marketing activities to their most responsive segments, the efficiency of commodity promotion can be dramatically improved.

Latent class analysis and individuals' preferences mapping: the new consumption orientations and perspectives for craft beer in North-West Italy

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Stefano Massaglia ◽  
Valentina Maria Merlino ◽  
Simone Blanc ◽  
Aurora Bargetto ◽  
Danielle Borra
Keyword(s):  
Latent Class Analysis ◽  
Large Scale ◽  
Latent Class ◽  
Consumer Preferences ◽  
Demographic Characteristics ◽  
Class Analysis ◽  
Content Type ◽  
North West ◽  
Craft Beer ◽  
Definition Of

PurposeIn Italy, the craft beer (CB) market has undergone a trend of exponential growth in recent years, showing, at the same time, differences among different geographical areas. This research aimed to define the consumer preferences towards different CB attributes by involving a sample of individuals from Piedmont (from North-West Italy). Furthermore, the experimentation was designed to distinguish heterogeneous individuals' consumption profiles each characterised by different CB preferences, drinking habits and socio-demographic characteristics.Design/methodology/approachThe exploration of individuals' preferences towards 12 CB quality attributes was made throughout a choice experiment based on the Best-Worst Scaling (BWS) methodology approach. In addition, the BWS results were employed in the latent class analysis to identify the best sample segmentation in relation to attributes preferences.FindingsThe “Brand knowledge”, “I have already tried it” were the most important attributes for CB choice. On the contrary, the “Type of packaging” and “Price” were the least important for CB choice. The “Loyal”, “Attentive to quality composition” and “Territorial brand” clusters were defined in function of CB consumers preferences and described in terms of individuals consumption habits and socio-demographic characteristics.Originality/valueThe BWS methodology allowed the definition of a preference index for each selected CB attributes. These indications could have concrete importance on production and marketing choices in an increasingly extended and globalised market, also at large-scale distribution level. Furthermore, the definition of different consumption profiles allowed to highlight the heterogeneity of consumption (preferences and habits) towards CB.

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.

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.

scholarly journals The Impacts Of Socio-Economic Challenge On Long-Term Physical and Mental Health In Retirement Age

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 1057-1058
Author(s):  
Ilan Kwon ◽  
Sojung Park ◽  
BoRin Kim ◽  
ByeongJu Ryu
Keyword(s):  
Mental Health ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Later Life ◽  
The United States ◽  
Class Analysis ◽  
Physical And Mental Health ◽  
Term Care ◽  
The Impact

Abstract Despite consistent evidence on the negative effect of social and economic challenges on health, little is known about the pattern of economic difficulties people experience and the impact of those challenging patterns on long-term health in later life. This study used the national data, Mid Life in the United States (MIDUS 3 in 2013-2014), to identify the different patterns of socio-economic challenges that older Americans (50-64 ages old) experienced during the Recession in 2008 and to examine the impact of past challenging experiences on physical and mental health in their later life. Socio-economic challenges included twenty-six items such as losing or moving a job, missing rent, selling or losing a home, bankruptcy, having debts, and cutting spending. We conducted the latent class analysis and regression while controlling other social determinant factors (e.g., education, employment status, poverty, etc.). The latent class analysis result found five patterns during the Recession: people who experienced various difficulties during the Recession, who moved their jobs, who experienced financial difficulties, who bought a home with decreased debts, and who experienced no difficulty. Compared to people with no challenging experience, those who needed to move their jobs but could make debt off during the Recession reported physically healthier, but not mentally healthier in later life. Interestingly, among this group, women reported more long-term physical health problems than men. The findings suggest the close connection between physical and mental health and the importance of long-term care for mental health among older adults in recovering from socio-economic challenges.

A Common Methodology

2016 ◽  
Vol 7 (2) ◽  
pp. 74-87
Author(s):  
Sunny L. Munn
Keyword(s):  
Cluster Analysis ◽  
Organizational Culture ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Organizational Structures ◽  
Work Life ◽  
Class Analysis ◽  
Analysis Methodology ◽  
The Common ◽  
The Impact

Organizational structures are comprised of an organizational culture created by the beliefs, values, traditions, policies and processes carried out by the organization. The work-life system in which individuals use work-life initiatives to achieve a work-life balance can be influenced by the type of organizational culture within one's workplace, for example a structured, rigid culture in which employees are afraid to ask questions versus a flexible, open culture where discussion is encouraged. Grouping methodologies such as cluster analysis or latent class analysis can be used to create typologies of organizational culture. The focus of this paper is to deconstruct the common methodology of cluster analysis used to identify typologies of organizational culture in the NSCW Study and the NOS Study, which set out to identify the impact of organizational culture on the use and existence of work-life benefits for individuals and organizations, respectively (Munn, 2012). The paper discusses the cluster analysis methodology in detail as well as another grouping methodology – latent class analysis - as a means to understanding the place of organizational culture in work-life research. The theoretical contributions of using cluster analysis to create typologies of organizational culture and the implications for workforce research are discussed.

scholarly journals Latent Class Analysis of Multiple Health Risk Behaviors among Australian University Students and Associations with Psychological Distress

Nutrients ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 425 ◽  
Author(s):  
Melinda J. Hutchesson ◽  
Mitch J. Duncan ◽  
Stina Oftedal ◽  
Lee M. Ashton ◽  
Christopher Oldmeadow ◽  
...  
Keyword(s):  
Psychological Distress ◽  
University Students ◽  
Health Risk ◽  
Health Behaviors ◽  
Latent Class Analysis ◽  
Risk Behaviors ◽  
Latent Class ◽  
Health Risk Behaviors ◽  
Demographic Characteristics ◽  
Class Analysis

University students have high rates of health risk behaviors and psychological distress. This study explores patterns of health behaviors among a sample of Australian university students, and determines whether patterns of health behaviors are associated with psychological distress and demographic characteristics. Cross-sectional data from the University of Newcastle Student Healthy Lifestyle Survey 2019 were analyzed. Fruit and vegetable intake, sugar-sweetened beverage intake, physical activity, sitting time, smoking, alcohol intake, drug use, sleep and psychological distress were assessed. Latent class analysis (LCA) was used to identify patterns of health risk behaviors, and latent class regression to explore associations between psychological distress and demographic characteristics with health behavior classes. Analysis included 1965 students (mean age 25.8 ± 8.6 years, 70.7% female). Three patterns of health behaviors were identified: healthier (48.6%), moderate (40.2%) and unhealthy (11.2%) lifestyle classes. Students in the moderate and unhealthy lifestyle classes had higher odds of moderate (OR 1.43 and 2.37) and high/very high psychological distress risk (OR 2.71 and 11.69). Students in the unhealthy and moderate lifestyle classes had a higher odds of being male, younger, enrolled in transition to university and English language courses, Aboriginal or Torres Strait Islander descent and to report some financial difficulty. Study findings may be used to inform the design of mental health interventions for university students that target key health risk behaviors.

scholarly journals Profiles of Depressive Symptoms Among Men Who Have Sex With Men and Transgender Women During the COVID-19 Outbreak in Mexico: A Latent Class Analysis

2021 ◽  
Vol 9 ◽  
Author(s):  
Diego Cerecero-Garcia ◽  
Heleen Vermandere ◽  
Ietza Bojorquez ◽  
José Gómez-Castro ◽  
José Arturo Sánchez-Ochoa ◽  
...  
Keyword(s):  
Mental Health ◽  
Depressive Symptoms ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Depression Scale ◽  
Transgender Women ◽  
Economic Stress ◽  
Class Analysis ◽  
Sex With Men ◽  
The Impact

The impact of the COVID-19 outbreak on mental health among HIV high-risk populations is not known. We assess the prevalence of depressive symptoms (DS) and explore the association with characteristics related to the COVID-19 pandemic. We conducted an online survey among 881 men who have sex with men (MSM) and transgender women (TGW) assessing the presence of DS using the Center for Epidemiological Studies Depression Scale (CESD-10); results were compared with previously self-reported DS and national data. We applied latent class analysis (LCA) to identify classes of participants with similar COVID-19 related characteristics. The overall prevalence of significant DS was 53.3%. By LCA posterior probabilities we identified three classes: (1) minimal impact of COVID-19 (54.1%), (2) objective risk for COVID-19 (41.5%), and (3) anxiety and economic stress caused by COVID-19 (4.4%). Multivariate logistic regression showed that compared with those in class one, the odds to have significant DS were almost five times higher for those in class three. Our findings suggest high levels of depression among MSM and TGW in Mexico during the COVID-19 pandemic and highlight the need for the provision of targeted psychological interventions to minimize the impacts of COVID-19 on the mental health.

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