Impact of Package Descriptors on Young Adults' Perceptions of Cigarillos

2020 ◽  
Vol 6 (2) ◽  
pp. 118-135
Author(s):  
Abigail T. Evans ◽  
Jess Wilhelm ◽  
Haneen Abudayyeh ◽  
Lexie Perreras ◽  
Amy M. Cohn
Keyword(s):  
United States ◽  
Young Adults ◽  
Linear Regression ◽  
Perceived Risk ◽  
Regression Models ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk ◽  
Standard Errors ◽  
Linear Regression Models ◽  
Black And White

Objectives: In this study, we measured the effects of cigarillo packaging colors and flavor descriptors on appeal and perceived risk among young adults. Methods: United States-based young adults (ages 18-24) recruited via Amazon Mechanical Turk were randomized to view one of 7 images of cigarillo packages that varied in color (Black and White [B&W], brown, red) and flavor descriptor (none, tobacco, apple). Respondents rated the product's appeal, risk, and addictiveness. Differences in ratings by study condition were assessed using linear regression models with bootstrapped standard errors. Results: There were 2818 participants, and 26.5% reported having ever used a little cigar or cigarillo. Brown and red packaging were rated as more appealing (vs B&W) across 4 dimensions (all ps < .05). Compared to no flavor descriptor, tobacco flavor was rated as more "Attention-Grabbing" (b = 0.21, p = .010) and apple flavor was rated higher on all 8 measures of appeal (all ps < .05) and perceived as less addictive (b = -0.13, p = .024). Conclusions: Colors and flavor descriptors on cigarillo packaging increased appeal and decreased perceived addictiveness. Restricting color and flavor descriptors on packaging may reduce their appeal.

User Preferences for Bicycle Infrastructure in Communities with Emerging Cycling Cultures

2019 ◽  
Vol 2673 (12) ◽  
pp. 89-102 ◽  
Author(s):  
Calvin Clark ◽  
Patricia Mokhtarian ◽  
Giovanni Circella ◽  
Kari Watkins
Keyword(s):  
United States ◽  
Linear Regression ◽  
Regression Models ◽  
User Preferences ◽  
Linear Regression Models ◽  
Bicycle Infrastructure

Non-motorized travel modes, particularly cycling, are experiencing a resurgence in many United States (U.S.) states as well as in other countries. Still, most studies focus on bicyclists’ behaviors in areas with strong bicycling cultures. This paper discusses the findings of a survey (N = 1,178) deployed in six communities in Alabama and Tennessee, U.S., where cycling is not (yet) popular nor widely adopted. The analysis includes linear regression models built on respondents’ reactions to images of bicycling infrastructure and their perceptions of being comfortable, safe, and willing to try cycling on the displayed roadway type. Findings indicate a preference for more separated bicycle infrastructure types along with options that exclude on-street parking. Segmented models indicate that, compared with potential cyclists, the preferences of regular utilitarian cyclists can vary more than those of recreational/occasional cyclists. Results from this study provide useful insights into ways to maximize the return on investments, and design bike infrastructure that can attract patronage and be most successful in areas lacking a substantial bicycling population.

scholarly journals Tobacco Use Behaviors and Perceptions of Parental Smokers in the Emergency Department Setting

2019 ◽  
Vol 12 ◽  
pp. 1179173X1984139 ◽  
Author(s):  
E Melinda Mahabee-Gittens ◽  
Ashley L Merianos ◽  
Lara Stone ◽  
Meredith E Tabangin ◽  
Jane C Khoury ◽  
...  
Keyword(s):  
Emergency Department ◽  
Linear Regression ◽  
Tobacco Smoke ◽  
Regression Models ◽  
Urgent Care ◽  
Smoking Bans ◽  
Linear Regression Models ◽  
Older Children ◽  
Black And White ◽  
Child Age

Background: More information is needed about modifiable child tobacco smoke exposure (TSE) patterns in racially diverse parental smokers to tailor interventions designed to help parents quit smoking and reduce their child’s TSE. Our objectives were to determine whether there were differences in smoking and TSE patterns based on parental race and child age and whether these patterns differed based on child age within black and white parental smokers. Secondary objectives were to assess the relationship between parental perceptions about the effects of smoking and the benefits of quitting on their child based on child age, race, and reported TSE patterns and to examine biochemically verified TSE levels by child age, race, and parent-reported TSE patterns. Methods: Participants (N = 415) were non-Hispanic black and non-Hispanic white parental smokers, mean age (standard deviation [SD]) = 31.2 (7.2) years, who visited the Pediatric Emergency Department (PED) or Urgent Care (UC) with their child, mean age (SD) = 4.7 (4.6) years. Parents reported sociodemographics, smoking, and child TSE patterns. We conducted chi-square tests, independent t-tests, and general linear regression models to answer our primary objectives and linear regression models to answer our secondary objectives. Results: Parents were 56.1% non-Hispanic black; 87.5% women; mean (SD) number of cigarettes smoked/day was 10.5(6.8). A higher proportion of parents with younger children <3 years old reported smoking bans compared with parents with older children ⩾3 to <18 years old (41.3% vs 19.7%, P < .0001). Subsequent analyses revealed this pattern for both black and white parents. A total of 212 (51%) of children had biochemical assessment of TSE; 89.6% had detectable TSE. Younger children had significantly higher cotinine levels than older children independent of their race ( P < .001). Conclusions: Children of parental smokers who visit the PED/UC were highly tobacco smoke exposed. Both black and white parental smokers with younger children were more likely to enforce smoking bans, but younger children had higher TSE levels than older children. Interventions that target this group of parental smokers with younger children may be more effective than interventions geared to all parental smokers.

scholarly journals Heart rate variability and psychosocial symptoms in adolescents and young adults with cancer

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0259385
Author(s):  
Mallory R. Taylor ◽  
Michelle M. Garrison ◽  
Abby R. Rosenberg
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Young Adults ◽  
Linear Regression ◽  
Regression Models ◽  
Secondary Analysis ◽  
Adolescents And Young Adults ◽  
Linear Regression Models ◽  
Common Diagnosis ◽  
Patient Reported

Background Heart Rate Variability (HRV) is a valid, scalable biomarker of stress. We aimed to examine associations between HRV and psychosocial outcomes in adolescents and young adults (AYAs) with cancer. Methods This was a secondary analysis of baseline data from a randomized trial testing a resilience intervention in AYAs with cancer. Two widely used HRV metrics, the standard deviation of normal to normal beats (SDNN) and root mean square of successive differences (RMSSD), were derived from electrocardiograms. Patient-reported outcome (PRO) survey measures included quality of life, anxiety, depression, distress, and resilience. Linear regression models were used to test associations between HRV and PRO scores. The Wilcoxon rank sum test was used to test differences in median HRV values among participant subgroups. Results Among the n = 76 patients with available electrocardiograms, the mean age was 16 years (SD 3y), 63% were white, and leukemia/lymphoma was the most common diagnosis. Compared to healthy adolescents, AYAs with cancer had lower median HRV (SDNN [Females: 31.9 (12.8–50.7) vs 66.4 (46.0–86.8), p<0.01; Males: 29.9 (11.5–47.9) vs 63.2 (48.4–84.6), p<0.01]; RMSSD [Females: 28.2 (11.1–45.5) vs 69.0 (49.1–99.6), p<0.01; Males: 27.9 (8.6–48.6) vs 58.7 (44.8–88.2), p<0.01]). There was no statistically significant association between PRO measures and SDNN or RMSSD in either an unadjusted or adjusted linear regression models. Conclusion In this secondary analysis, we did not find an association between HRV and psychosocial PROs among AYAs with cancer. HRV measures were lower than for healthy adolescents. Larger prospective studies in AYA biopsychosocial research are needed.

scholarly journals Association rules and regression linear model of the groundwater population by the evaluation of uranium

2019 ◽  
Vol 270 ◽  
pp. 04017
Author(s):  
Iing Lukman ◽  
Natalina
Keyword(s):  
United States ◽  
Linear Regression ◽  
Association Rules ◽  
United States Of America ◽  
Regression Models ◽  
The United States ◽  
Total Alkalinity ◽  
Linear Regression Models ◽  
Five Factors ◽  
Groundwater Samples

The uranium available more on groundwater samples of certain types on the total alkalinity were relatively the same. But, the content of the uranium was higher in the samples. The multiple linear regression for pH as a dependent variable showed that the pH negatively correlated to the uranium, but the uranium was not significant for the linear regression model. The data of groundwater population from the samples of 127 with 12 variables of measurement of the Energy Department of the United States of America resulted in those association rules and linear regression models. The data has five factors of Producing horizon namely Ogallala Formation (TPO), Dockum Formation (TRD), Quartermaster Group (POQ), Whitehorse and Cloud Chief Group (PGWC), El Reno Group and Blaine Formation (PGEB). The step-wise linear regression for each of the five producing horizon codes was fitted to the data. Then, the regression models for each variable of producing horizon were obtained if pH was the dependent variable. If the Uranium was a dependent variable, then the regression models obtained were four only, with the model for PGEB was not able to be made. When pH as a dependent variable, it was depended upon Boron, Total alkalinity, and Bicarbonate.

Correlation of self-reported pain severity and healthcare expenditures in older United States adults

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
David R. Axon ◽  
Tyler Pesqueira ◽  
Briana Jarrell ◽  
Dominic Dicochea
Keyword(s):  
United States ◽  
Linear Regression ◽  
Healthcare Costs ◽  
Regression Models ◽  
Prescription Medication ◽  
Pain Severity ◽  
Moderate Pain ◽  
Linear Regression Models ◽  
Healthcare Expenditures ◽  
Extreme Pain

Abstract Objectives Healthcare expenditures of older United States (US) adults with different pain severity levels are important to investigate given the increasing prevalence of pain in this population. This study assessed the correlation of healthcare expenditures among older US adults with different pain severities, hypothesizing that expenditures would increase as pain severity increased. Methods This retrospective cross-sectional database study used 2018 Medical Expenditure Panel Survey (MEPS) data and included US adults aged ≥50 with self-reported pain in the past four weeks and positive healthcare costs. Adjusted linear regression models with logarithmically transformed expenditure data compared differences in: total; office-based; outpatient; emergency room; inpatient; other; and prescription medication expenditures, between those with little, moderate, quite a bit, and extreme pain. Analyses were weighted to account for the complex MEPS design and to obtain nationally representative estimates. The a priori alpha level was 0.05. Results The eligible sample of 5,123 individuals produced a weighted study population of 57,134,711 US adults aged ≥50 with pain (little = 53.1%, moderate = 21.6%, quite-a-bit = 18.5%, extreme = 6.8%). In adjusted linear regression models, compared to little pain, extreme pain had the greatest level of costs, followed by quite a bit pain and moderate pain, for total, office-based, and prescription medication costs. For instance, compared to little pain, total healthcare costs were 78% greater for those with extreme pain, 51% greater for quite a bit pain, and 37% greater for moderate pain. However, this pattern was not observed for outpatient, emergency room, inpatient, and other costs, where ≥1 comparison for each cost category was not statistically significant. Conclusions This study found total healthcare costs increased as pain severity increased, yet this was not always the case when analyzing subcategories of healthcare costs. Further research is needed to investigate why some types of healthcare costs are greater with increasing pain severity, yet others are not.

Racial differences in perceived risk in participants enrolled in the American College of Radiology (ACRIN-6654) arm of the National Lung Screening Trial (NLST).

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 1563-1563 ◽  
Author(s):  
Christopher Lathan ◽  
Pallavi Kumar ◽  
Ilana F Gareen ◽  
Jeremy Gorelick ◽  
JoRean Sicks ◽  
...  
Keyword(s):  
Smoking Cessation ◽  
Linear Regression ◽  
Racial Differences ◽  
Perceived Risk ◽  
Risk Perceptions ◽  
Smoking Status ◽  
Smoking History ◽  
Linear Regression Models ◽  
Black And White ◽  
Incidence And Mortality

1563 Background: Blacks in the U.S. have higher incidence and mortality rates of lung cancer (LC) compared to whites. Previous work in small studies suggests that blacks have lower perceived risk of LC which may influence smoking cessation behavior. However, racial disparities in risk perceptions (RP) of LC and smoking related diseases (SRD) in heavy smokers have not been studied. We examined LC and SRD risk perceptions among black and white ACRIN NLST participants. Methods: The 10-item Smoking Risk Perceptions Scale (SRPS) for LC and SRD was administered to NLST participants, from 4 ACRIN sites, with a minimum 30 pack-year smoking history at 1 year following baseline screening chest x-ray or low dose computerized tomography (LDCT). We 1) validated the SRPS in black and white participants separately using exploratory and confirmatory factor analyses, 2) used 2-way ANOVAs to compare RP of black and white participants and 3) used multivariable linear regression models to identify factors associated with RP. Results: Among 1742 white and 194 black participants, the 10 SRPS items loaded onto two factors (absolute and relative risk; Cronbach’s alpha=0.92 and 0.95 for white and black participants, respectively). Black participants had significantly lower RP compared to white participants (SRPS range= 10-50, mean diff. 3.48, 95% CI 2.29-4.68, p<0.01). Factors significantly associated with lower RP in a multivariate linear regression were black race (β=4.59, p < 0.001), former smoking status (β=3.82, p<0.001), male gender (β=1.35, p<0.001), lower education (β=1.16, p =0.010), and older age (years, β = 0.15, p<0.001). Conclusions: We validated the SRPS in black and white ACRIN-6654/NLST participants. Blacks had significantly lower perceptions of LC and SRD risk compared to whites, even after adjusting for study arm, sociodemographics, and smoking status. Sociodemographic factors and smoking status were independently associated with lower RP. These findings confirm that black current and former smokers are at risk of underestimating their smoking-related risk, which may contribute to lower rates of adherence to screening and smoking cessation recommendations.

FAKTOR DETERMINAN PENYALURAN KREDIT BANK PERSERO

2018 ◽  
Vol 23 (1) ◽  
pp. 60-71
Author(s):  
Wigiyanti Masodah
Keyword(s):  
Interest Rate ◽  
Linear Regression ◽  
Interest Rates ◽  
Regression Models ◽  
Linear Regression Models ◽  
Negative Impacts ◽  
Main Activity ◽  
The Impact ◽  
The Given ◽  
Multiple Linear Regression Models

Offering credit is the main activity of a Bank. There are some considerations when a bank offers credit, that includes Interest Rates, Inflation, and NPL. This study aims to find out the impact of Variable Interest Rates, Inflation variables and NPL variables on credit disbursed. The object in this study is state-owned banks. The method of analysis in this study uses multiple linear regression models. The results of the study have shown that Interest Rates and NPL gave some negative impacts on the given credit. Meanwhile, Inflation variable does not have a significant effect on credit given. Keywords: Interest Rate, Inflation, NPL, offered Credit.

Linear Regression Models for Interval-Valued Data using Log-transformation

2020 ◽  
Author(s):  
Nykolas Mayko Maia Barbosa ◽  
João Paulo Pordeus Gomes ◽  
César Lincoln Cavalcante Mattos ◽  
Diêgo Farias Oliveira
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Linear Regression Models ◽  
Log Transformation ◽  
Interval Valued

THE PREDICTIVE CONTENT OF DISAGGREGATED NORMAL INCOME: An Empirical Study in the JSX

2003 ◽  
Vol 5 (3) ◽  
pp. 363 ◽  
Author(s):  
Slamet Sugiri
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Stock Exchange ◽  
Manufacturing Firms ◽  
Single Step ◽  
Model Parameters ◽  
Linear Regression Models ◽  
Operating Income ◽  
Predictive Content ◽  
Multiple Step

The main objective of this study is to examine a hypothesis that the predictive content of normal income disaggregated into operating income and nonoperating income outperforms that of aggregated normal income in predicting future cash flow. To test the hypothesis, linear regression models are developed. The model parameters are estimated based on fifty-five manufacturing firms listed in the Jakarta Stock Exchange (JSX) up to the end of 1997.This study finds that empirical evidence supports the hypothesis. This evidence supports arguments that, in reporting income from continuing operations, multiple-step approach is preferred to single-step one.

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