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Food safety attitudes in college students: a structural equation modeling analysis of a conceptual model.

ABSTRACT: College students are one of the most at-risk population groups for food poisoning, due to risky food safety behaviors. Using the Likert Scale, undergraduate students were asked to participate in a Food Safety Survey which was completed by 499 students ages 18-25. Data was analyzed using SPSS and AMOS statistical software. Four conceptual definitions regarding food safety were defined as: general food safety, bacterial food safety, produce food safety, and politics associated with food safety. Knowledge seems to be an important factor in shaping students attitudes regarding general and bacterial safety. Ethnicity plays a role in how people view the politics of food safety, and the safety of organic foods.

SUBMITTER: Booth R

PROVIDER: S-EPMC3635197 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature

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Food safety attitudes in college students: a structural equation modeling analysis of a conceptual model.

Booth Rachelle R Hernandez Magaly M Baker Erica L EL Grajales Tevni T Pribis Peter P

Nutrients 20130130 2

College students are one of the most at-risk population groups for food poisoning, due to risky food safety behaviors. Using the Likert Scale, undergraduate students were asked to participate in a Food Safety Survey which was completed by 499 students ages 18-25. Data was analyzed using SPSS and AMOS statistical software. Four conceptual definitions regarding food safety were defined as: general food safety, bacterial food safety, produce food safety, and politics associated with food safety. Kn ...[more]

PMID: 23364131

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Project description:Background/Study Context: Conceptual frameworks are analytic models at a high level of abstraction. Their operationalization can inform randomized trial design and sample size considerations.MethodsThe Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) conceptual framework was empirically tested using structural equation modeling (N=2,802). ACTIVE was guided by a conceptual framework for cognitive training in which proximal cognitive abilities (memory, inductive reasoning, speed of processing) mediate treatment-related improvement in primary outcomes (everyday problem-solving, difficulty with activities of daily living, everyday speed, driving difficulty), which in turn lead to improved secondary outcomes (health-related quality of life, health service utilization, mobility). Measurement models for each proximal, primary, and secondary outcome were developed and tested using baseline data. Each construct was then combined in one model to evaluate fit (RMSEA, CFI, normalized residuals of each indicator). To expand the conceptual model and potentially inform future trials, evidence of modification of structural model parameters was evaluated by age, years of education, sex, race, and self-rated health status.ResultsPreconceived measurement models for memory, reasoning, speed of processing, everyday problem-solving, instrumental activities of daily living (IADL) difficulty, everyday speed, driving difficulty, and health-related quality of life each fit well to the data (all RMSEA < .05; all CFI > .95). Fit of the full model was excellent (RMSEA = .038; CFI = .924). In contrast with previous findings from ACTIVE regarding who benefits from training, interaction testing revealed associations between proximal abilities and primary outcomes are stronger on average by nonwhite race, worse health, older age, and less education (p < .005).ConclusionsEmpirical data confirm the hypothesized ACTIVE conceptual model. Findings suggest that the types of people who show intervention effects on cognitive performance potentially may be different from those with the greatest chance of transfer to real-world activities.

Dataset Information

Food safety attitudes in college students: a structural equation modeling analysis of a conceptual model.

Publications

Food safety attitudes in college students: a structural equation modeling analysis of a conceptual model.

Similar Datasets

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