scholarly journals Chiropractic students’ perceptions of barriers and facilitators to joining a professional association”

2019 ◽  
Vol 27 (1) ◽  
Author(s):  
Stanley I. Innes ◽  
Norman Stomski ◽  
Jean Theroux
Keyword(s):  
Logistic Regression ◽  
Health Professional ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Professional Associations ◽  
Professional Association ◽  
Barriers And Facilitators ◽  
Preliminary Survey ◽  
Components Analysis ◽  
Chiropractic Students

Abstract Background In Australia, about 1 in 3 chiropractors choose not to belong to either of the two professional associations and this is considerably lower compared to other health professional organisations in this country. The reasons for this remain unknown. We sought to explore possible reasons by asking chiropractic students their perceptions of barriers and facilitators to joining a professional association. However, we were unable to identify validated survey instruments that could be used to obtain information about reasons for joining health professional associations. Aim Therefore, the objectives of this study were to: 1) develop a survey instrument that captures information about what influences chiropractic students in joining professional association; and 2) identify factors that promote association membership among chiropractic students. Methods A literature review was undertaken to identify known determinants of professional association membership and were used to construct a preliminary survey instrument, which comprised 47 items. Six fourth-year chiropractic students assessed the preliminary survey instrument’s content validity. Principal components analysis was used to establish the structure of the scales. Cronbach’s alpha was derived to determine whether all items in each scale tapped a discrete construct. Logistic regression was used to examine the association between the scale scores and having joined a chiropractic professional association. Results In March 2019, 348 chiropractic students from Murdoch University (71.0%) responded to a voluntary, anonymous questionnaire. Principal components analysis resulted in the retention of 21 items that strongly loaded onto 6 factors. Internal consistency was found to be adequate. The results of the logistic regression analysis demonstrated that only “development of the profession” was significantly associated with have joined a professional chiropractic association (p = 0.049, OR = 2.22; 95% CI = 1.26–3.40). Conclusion Chiropractic organisations can probably most effectively increase membership numbers through raising awareness of their contribution to the development of the profession.

scholarly journals Landowner Motivations for Owning Woodland on the Tennessee Northern Cumberland Plateau

2011 ◽  
Vol 35 (1) ◽  
pp. 39-43 ◽  
Author(s):  
Brandon R. Kaetzel ◽  
Donald G. Hodges ◽  
J. Mark Fly
Keyword(s):  
Logistic Regression ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Multinomial Logistic Regression ◽  
Cumberland Plateau ◽  
The Past ◽  
Resource Managers ◽  
Components Analysis ◽  
Private Forestland ◽  
Nipf Landowners

Abstract There has been a dearth of evidence in recent years by which to assess what motivation landowners have for owning woodland. Only recently, in the past 5 years, has there been a fresh attempt to answer this question. It has become increasingly important to understand landowner motivations for owning woodland with the substantial increase of nonindustrial private forestland (NIPF) landowners and the decreasing sizes of tracts of land. This report uses results of a 2005 survey on the Tennessee Northern Cumberland Plateau to assess what motivations landowners have for owning their woodland. Principal components analysis is used to assign motivation categories, and multinomial logistic regression is used to assess what characteristics classify landowners into their respective motivation categories. Results show that landowners can be classified into one of three motivation categories: privacy, utility, and heritage. This knowledge is beneficial to resource managers as they attempt to disseminate information to landowners on how to best achieve their objectives.

scholarly journals Principal components analysis of diet and alternatives for identifying the combination of foods that are associated with the risk of disease: a simulation study

2014 ◽  
Vol 112 (1) ◽  
pp. 61-69 ◽  
Author(s):  
Ioannis Bakolis ◽  
Peter Burney ◽  
Richard Hooper
Keyword(s):  
Logistic Regression ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Multiple Testing ◽  
Propensity Scores ◽  
Disease Association ◽  
Nutritional Epidemiology ◽  
False Discovery ◽  
Risk Of Disease ◽  
Components Analysis

Dietary patterns derived empirically using principal components analysis (PCA) are widely employed for investigating diet–disease relationships. In the present study, we investigated whether PCA performed better at identifying such associations than an analysis of each food on a FFQ separately, referred to here as an exhaustive single food analysis (ESFA). Data on diet and disease were simulated using real FFQ data and by assuming a number of food intakes in combination that were associated with the risk of disease. In each simulation, ESFA and PCA were employed to identify the combinations of foods that are associated with the risk of disease using logistic regression, allowing for multiple testing and adjusting for energy intake. ESFA was also separately adjusted for principal components of diet, foods that were significant in the unadjusted ESFA and propensity scores. For each method, we investigated the power with which an association between diet and disease could be identified, and the power and false discovery rate (FDR) for identifying the specific combination of food intakes. In some scenarios, ESFA had greater power to detect a diet–disease association than PCA. ESFA also typically had a greater power and a lower FDR for identifying the combinations of food intakes that are associated with the risk of disease. The FDR of both methods increased with increasing sample size, but when ESFA was adjusted for foods that were significant in the unadjusted ESFA, FDR were controlled at the desired level. These results question the widespread use of PCA in nutritional epidemiology. The adjusted ESFA identifies the combinations of foods that are causally linked to the risk of disease with low FDR and surprisingly good power.

Diagnoses Generated by Numerical Taxonomic Methods Applied to Standard Blood Variables

1980 ◽  
Vol 19 (04) ◽  
pp. 205-209
Author(s):  
L. A. Abbott ◽  
J. B. Mitton
Keyword(s):  
Liver Cirrhosis ◽  
Renal Disease ◽  
Principal Components Analysis ◽  
Discriminant Function ◽  
Principal Components ◽  
Discriminant Function Analysis ◽  
Chronic Renal Disease ◽  
Function Analysis ◽  
Infectious Hepatitis ◽  
Components Analysis

Data taken from the blood of 262 patients diagnosed for malabsorption, elective cholecystectomy, acute cholecystitis, infectious hepatitis, liver cirrhosis, or chronic renal disease were analyzed with three numerical taxonomy (NT) methods : cluster analysis, principal components analysis, and discriminant function analysis. Principal components analysis revealed discrete clusters of patients suffering from chronic renal disease, liver cirrhosis, and infectious hepatitis, which could be displayed by NT clustering as well as by plotting, but other disease groups were poorly defined. Sharper resolution of the same disease groups was attained by discriminant function analysis.

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