scholarly journals Personal, Social, and Game-Related Correlates of Active and Non-Active Gaming Among Dutch Gaming Adolescents: Survey-Based Multivariable, Multilevel Logistic Regression Analyses

2014 ◽  
Vol 2 (1) ◽  
pp. e4 ◽  
Author(s):  
Monique Simons ◽  
Emely de Vet ◽  
Mai JM Chinapaw ◽  
Michiel de Boer ◽  
Jacob C Seidell ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Multilevel Logistic Regression ◽  
Regression Analyses ◽  
Active Gaming

scholarly journals Does the Structural Organisation of Lower-Secondary Education in Switzerland Influence Students’ Opportunities of Transition to Upper- Secondary Education? A Multilevel Analysis

2017 ◽  
Vol 43 (1) ◽  
pp. 63-88 ◽  
Author(s):  
Katja Scharenberg ◽  
Karin Wohlgemuth ◽  
Sandra Hupka-Brunner
Keyword(s):  
Logistic Regression ◽  
Secondary Education ◽  
Multilevel Analysis ◽  
Multilevel Logistic Regression ◽  
Regression Analyses ◽  
Integrated Models ◽  
Upper Secondary Education ◽  
Structural Organisation ◽  
Upper Secondary ◽  
Lower Secondary Education

Abstract The Swiss cantonal education systems account for the structural organisation of lower-secondary education (streamed, cooperative or integrated models). We examined whether structural cantonal variations affect students’ transition to upper-secondary education. Analyses drew on data from the TREE study. Multilevel logistic regression analyses indicated that students in cantons with a cooperative or integrated model had, by trend, a higher chance of gaining access to upper-secondary education. The effect was confounded with the language regions.

scholarly journals Barriers to accessing healthcare among women in Ghana: a multilevel modelling

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Abdul-Aziz Seidu ◽  
Eugene Kofuor Maafo Darteh ◽  
Ebenezer Agbaglo ◽  
Louis Kobina Dadzie ◽  
Bright Opoku Ahinkorah ◽  
...  
Keyword(s):  
Sustainable Development ◽  
Logistic Regression ◽  
Health Insurance ◽  
Sustainable Development Goals ◽  
Contextual Factors ◽  
Multilevel Logistic Regression ◽  
Regression Analyses ◽  
The Sustainable Development ◽  
Lower Odds ◽  
Development Goals

Abstract Background Women’s health remains a global public health concern, as enshrined in the Sustainable Development Goals. This study, therefore, sought to assess the individual and contextual factors associated with barriers to accessing healthcare among women in Ghana. Methods The study was conducted among 9370 women aged 15–49, using data from the 2014 Ghana Demographic and Health Survey. Barrier to healthcare, derived from four questions— whether a woman faced problems in getting money, distance, companionship, and permission to see a doctor—was the outcome variable. Descriptive and multilevel logistic regression analyses were carried out. The fixed effect results of the multilevel logistic regression analyses were reported using adjusted odds ratios at a 95% confidence interval. Results More than half (51%) of the women reported to have at least one form of barrier to accessing healthcare. Women aged 45–49 (AOR = 0.65, CI: 0.49–0.86), married women (AOR = 0.71, CI:0.58–0.87), those with a higher level of education (AOR = 0.51, CI: 0.37–0.69), those engaged in clerical or sales occupation (AOR = 0.855, CI: 0.74–0.99), and those who were covered by health insurance (AOR = 0.59, CI: 0.53–0.66) had lower odds of facing barriers in accessing healthcare. Similarly, those who listened to radio at least once in a week (AOR =0.77, CI: 0.66–0.90), those who watched television at least once a week (AOR = 0.75, CI: 0.64–0.87), and women in the richest wealth quintile (AOR = 0.47, CI: 0.35–0.63) had lower odds of facing barriers in accessing healthcare. However, women who were widowed (AOR = 1.47, CI: 1.03–2.10), those in the Volta Region (AOR 2.20, CI: I.38–3.53), and those in the Upper West Region (AOR =2.22, CI: 1.32–3.74) had the highest odds of facing barriers to healthcare accessibility. Conclusion This study shows that individual and contextual factors are significant in predicting barriers in healthcare access in Ghana. The factors identified include age, marital status, employment, health insurance coverage, frequency of listening to radio, frequency of watching television, wealth status, and region of residence. These findings highlight the need to pay critical attention to these factors in order to achieve the Sustainable Development Goals 3.1, 3.7, and 3.8. It is equally important to strengthen existing strategies to mitigate barriers to accessing healthcare among women in Ghana.

scholarly journals Interpreting a standardized and normalized measure of neighborhood socioeconomic status for a better understanding of health differences

2021 ◽  
Vol 79 (1) ◽  
Author(s):  
Masayoshi Oka
Keyword(s):  
Logistic Regression ◽  
Health Condition ◽  
Multilevel Logistic Regression ◽  
Regression Analyses ◽  
Standardized Measures ◽  
Neighborhood Socioeconomic Status ◽  
Health Differences ◽  
Deprived Neighborhoods ◽  
Two Measures ◽  
Neighborhood Ses

Abstract Background Standardization and normalization of continuous covariates are used to ease the interpretation of regression coefficients. Although these scaling techniques serve different purposes, they are sometimes used interchangeably or confused for one another. Therefore, the objective of this study is to demonstrate how these scaling techniques lead to different interpretations of the regression coefficient in multilevel logistic regression analyses. Methods Area-based socioeconomic data at the census tract level were obtained from the 2015–2019 American Community Survey for creating two measures of neighborhood socioeconomic status (SES), and a hypothetical data on health condition (favorable versus unfavorable) was constructed to represent 3000 individuals living across 300 census tracts (i.e., neighborhoods). Two measures of neighborhood SES were standardized by subtracting its mean and dividing by its standard deviation (SD) or by dividing by its interquartile range (IQR), and were normalized into a range between 0 and 1. Then, four separate multilevel logistic regression analyses were conducted to assess the association between neighborhood SES and health condition. Results Based on standardized measures, the odds of having unfavorable health condition was roughly 1.34 times higher for a one-SD change or a one-IQR change in neighborhood SES; these reflect a health difference of individuals living in relatively high SES (relatively affluent) neighborhoods and those living in relatively low SES (relatively deprived) neighborhoods. On the other hand, when these standardized measures were replaced by its respective normalized measures, the odds of having unfavorable health condition was roughly 3.48 times higher for a full unit change in neighborhood SES; these reflect a health difference of individuals living in highest SES (most affluent) neighborhoods and those living in lowest SES (most deprived) neighborhoods. Conclusion Multilevel logistic regression analyses using standardized and normalized measures of neighborhood SES lead to different interpretations of the effect of neighborhood SES on health. Since both measures are valuable in their own right, interpreting a standardized and normalized measure of neighborhood SES will allow us to gain a more rounded view of the health differences of individuals along the gradient of neighborhood SES in a certain geographic location as well as across different geographic locations.

Perceived Effectiveness of Random Testing for Alcohol and Drugs in the Australian Aviation Community

2012 ◽  
Vol 2 (2) ◽  
pp. 72-81
Author(s):  
Christina M. Rudin-Brown ◽  
Eve Mitsopoulos-Rubens ◽  
Michael G. Lenné
Keyword(s):  
Logistic Regression ◽  
Online Survey ◽  
Random Testing ◽  
Regression Analyses ◽  
Perceived Effectiveness ◽  
Student Pilots ◽  
Alcohol And Drugs ◽  
Positive Attitudes ◽  
One Year ◽  
Alcohol And Other Drugs

Random testing for alcohol and other drugs (AODs) in individuals who perform safety-sensitive activities as part of their aviation role was introduced in Australia in April 2009. One year later, an online survey (N = 2,226) was conducted to investigate attitudes, behaviors, and knowledge regarding random testing and to gauge perceptions regarding its effectiveness. Private, recreational, and student pilots were less likely than industry personnel to report being aware of the requirement (86.5% versus 97.1%), to have undergone testing (76.5% versus 96.1%), and to know of others who had undergone testing (39.9% versus 84.3%), and they had more positive attitudes toward random testing than industry personnel. However, logistic regression analyses indicated that random testing is more effective at deterring AOD use among industry personnel.

scholarly journals Impact of digitally acquired peer diagnostic input on diagnostic confidence in outpatient cases: A pragmatic randomized trial

2020 ◽  
Author(s):  
Elaine C Khoong ◽  
Valy Fontil ◽  
Natalie A Rivadeneira ◽  
Mekhala Hoskote ◽  
Shantanu Nundy ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Randomized Trial ◽  
Odds Ratio ◽  
Primary Outcome ◽  
Mixed Effects ◽  
Regression Analyses ◽  
Diagnostic Confidence ◽  
Diagnostic Uncertainty ◽  
Intervention Impact ◽  
High Uncertainty

Abstract Objective The study sought to evaluate if peer input on outpatient cases impacted diagnostic confidence. Materials and Methods This randomized trial of a peer input intervention occurred among 28 clinicians with case-level randomization. Encounters with diagnostic uncertainty were entered onto a digital platform to collect input from ≥5 clinicians. The primary outcome was diagnostic confidence. We used mixed-effects logistic regression analyses to assess for intervention impact on diagnostic confidence. Results Among the 509 cases (255 control; 254 intervention), the intervention did not impact confidence (odds ratio [OR], 1.46; 95% confidence interval [CI], 0.999-2.12), but after adjusting for clinician and case traits, the intervention was associated with higher confidence (OR, 1.53; 95% CI, 1.01-2.32). The intervention impact was greater in cases with high uncertainty (OR, 3.23; 95% CI, 1.09- 9.52). Conclusions Peer input increased diagnostic confidence primarily in high-uncertainty cases, consistent with findings that clinicians desire input primarily in cases with continued uncertainty.

785 Reported Restful Sleep Predicting Emotional Distress: Does Exercise (and its modalities) moderate?

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A305-A306
Author(s):  
Jesse Moore ◽  
Ellita Williams ◽  
Collin Popp ◽  
Anthony Briggs ◽  
Judite Blanc ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Aerobic Exercise ◽  
Regression Models ◽  
Regression Analyses ◽  
Logistic Regression Models ◽  
The Past ◽  
Strengthening Exercise ◽  
Waking Up ◽  
The Relationship ◽  
Age And Sex

Abstract Introduction Literature shows that exercise moderates the relationship between sleep and emotional distress (ED.) However, it is unclear whether different types of exercise, such as aerobic and strengthening, affect this relationship differently. We investigated the moderating role of two types of exercise (aerobic and strengthening) regarding the relationship between ED and sleep. Methods Our analysis was based on data from 2018 National Health Interview Survey (NHIS), a nationally representative study in which 2,814 participants provided all data. Participants were asked 1) “how many days they woke up feeling rested over the past week”, 2) the Kessler 6 scale to determine ED (a score >13 indicates ED), and 3) the average frequency of strengthening or aerobic exercise per week. Logistic regression analyses were performed to determine if the reported days of waking up rested predicted level of ED. We then investigated whether strengthening or aerobic exercise differentially moderated this relationship. Covariates such as age and sex were adjusted in the logistic regression models. Logistic regression analyses were performed to determine if subjective reporting of restful sleep predicted level of ED. We investigated whether strengthening exercise or aerobic exercise differentially moderated this relationship. Covariates such as age and sex were adjusted in the logistic regression models. Results On average, participants reported 4.41 restful nights of sleep (SD =2.41), 3.43 strengthening activities (SD = 3.19,) and 8.47 aerobic activities a week (SD=5.91.) We found a significant association between days over the past week reporting waking up feeling rested and ED outcome according to K6, Χ2(1) = -741, p= <.001. The odds ratio signified a decrease of 52% in ED scores for each unit of restful sleep (OR = .48, (95% CI = .33, .65) p=<.001.) In the logistic regression model with moderation, aerobic exercise had a significant moderation effect, Χ2(1) = .03, p=.04, but strengthening exercise did not. Conclusion We found that restful sleep predicted reduction in ED scores. Aerobic exercise moderated this relationship, while strengthening exercise did not. Further research should investigate the longitudinal effects of exercise type on the relationship between restful sleep and ED. Support (if any) NIH (K07AG052685, R01MD007716, K01HL135452, R01HL152453)

Familial Interdependence, Socioeconomic Disadvantage, and the Formation of Familial Mentoring Relationships Within Black Families

2020 ◽  
pp. 074355842097912
Author(s):  
Janelle T. Billingsley ◽  
Ariana J. Rivens ◽  
Noelle M. Hurd
Keyword(s):  
Logistic Regression ◽  
Social Class ◽  
Mixed Method ◽  
Black Families ◽  
Socioeconomic Disadvantage ◽  
Mentoring Relationships ◽  
Regression Analyses ◽  
Disadvantaged Youth ◽  
Mentoring Relationship ◽  
Mixed Method Design

This study used an explanatory sequential mixed-method design to explore the association between familial interdependence and familial mentoring relationship presence within black families. This study also examined how socioeconomic disadvantage may moderate the association between familial interdependence and familial mentoring presence. A sample of 216 black youth (59% girls; 41% boys) were surveyed, and a subsample of 25 participants were interviewed along with one of their parents, and one nonparental familial adult with whom the youth reported feeling emotionally close to learn more about the enactment of familial interdependence and the formation of familial mentoring relationships across social class. Logistic regression analyses revealed that greater valuing of familial interdependence was associated with a greater likelihood of having a familial mentoring relationship, but this association was present only among nonsocioeconomically disadvantaged youth. Data collected from participant interviews were analyzed to better understand this pattern of findings. These analyses provided some preliminary insights into why familial interdependence may predict familial mentor formation only among nonsocioeconomically disadvantaged youth. Implications of study findings for the promotion of familial mentoring relationships within black families are discussed.

scholarly journals Prediction of 11-year incidence of psychophysically dependent status or death among community-dwelling younger elderlies: from an age-specified community-based cohort study (the NISSIN project)

2021 ◽  
Vol 26 (1) ◽  
Author(s):  
Satoe Okabayashi ◽  
Takashi Kawamura ◽  
Hisashi Noma ◽  
Kenji Wakai ◽  
Masahiko Ando ◽  
...  
Keyword(s):  
Older Adults ◽  
Logistic Regression ◽  
Cohort Study ◽  
Prediction Model ◽  
Nursing Care ◽  
Family Members ◽  
Limited Resource ◽  
Community Dwelling ◽  
Older Individuals ◽  
Regression Analyses

Abstract Background Predicting adverse health events and implementing preventative measures are a necessary challenge. It is important for healthcare planners and policymakers to allocate the limited resource to high-risk persons. Prediction is also important for older individuals, their family members, and clinicians to prepare mentally and financially. The aim of this study is to develop a prediction model for within 11-year dependent status requiring long-term nursing care or death in older adults for each sex. Methods We carried out age-specified cohort study of community dwellers in Nisshin City, Japan. The older adults aged 64 years who underwent medical check-up between 1996 and 2005 were included in the study. The primary outcome was the incidence of the psychophysically dependent status or death or by the end of the year of age 75 years. Univariable logistic regression analyses were performed to assess the associations between candidate predictors and the outcome. Using the variables with p-values less than 0.1, multivariable logistic regression analyses were then performed with backward stepwise elimination to determine the final predictors for the model. Results Of the 1525 female participants at baseline, 105 had an incidence of the study outcome. The final prediction model consisted of 15 variables, and the c-statistics for predicting the outcome was 0.763 (95% confidence interval [CI] 0.714–0.813). Of the 1548 male participants at baseline, 211 had incidence of the study outcome. The final prediction model consisted of 16 variables, and the c-statistics for predicting the outcome was 0.735 (95% CI 0.699–0.771). Conclusions We developed a prediction model for older adults to forecast 11-year incidence of dependent status requiring nursing care or death in each sex. The predictability was fair, but we could not evaluate the external validity of this model. It could be of some help for healthcare planners, policy makers, clinicians, older individuals, and their family members to weigh the priority of support.

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