Literature DB >> 12627174

Computerization of a dietary history interview in a running cohort; evaluation within the Amsterdam Growth and Health Longitudinal Study.

I Bakker1, J W R Twisk, W van Mechelen, G B M Mensink, H C G Kemper.   

Abstract

OBJECTIVE: In nutritional research, a growing interest in the use of computer-assisted cross-check dietary history interview methods exists in order to improve cost-effectiveness. The introduction of such a method in an ongoing longitudinal study was evaluated with special emphasis on the effect on interviewer bias.
DESIGN: A study for the interviewer bias within and the agreement between a previously used paper-based face-to-face cross-check dietary history interview method and a newly developed interviewer-administered computer-assisted version of this interview method.
SUBJECTS: The interviewer bias of 436 face-to-face interviews is compared with that of 352 computer-assisted interviews. A subset of 82 subjects underwent a face-to-face interview at the mean age of 27 and 32 y and a computer-assisted interview at their mean age of 36 y. Energy, three macronutrients (protein, fat and carbohydrate), two micronutrients (calcium and iron) and alcohol intakes obtained by these three measurements are compared to analyse the agreement between the two interview methods.
RESULTS: ANOVA showed no interviewer bias for all seven analysed nutrients within the data from the computer-assisted interview, while for the face-to-face interview method, several nutrients varied significantly among the interviewers. Five different measures, used to analyse the agreement (differences, Pearson's correlation, ICC, square weighted kappa and Bland-Altman plots), showed no relevant differences between the two cross-check dietary history interview methods.
CONCLUSIONS: It is concluded that the computer-assisted interview caused a reduction of interviewer bias and is of similar quality to the face-to-face interview method. Computerization of a paper-based interview can be implemented in a running cohort if a change in method is unavoidable.

Entities:  

Mesh:

Year:  2003        PMID: 12627174     DOI: 10.1038/sj.ejcn.1601566

Source DB:  PubMed          Journal:  Eur J Clin Nutr        ISSN: 0954-3007            Impact factor:   4.016


  4 in total

Review 1.  Computer-assisted versus oral-and-written dietary history taking for diabetes mellitus.

Authors:  Igor Wei; Yannis Pappas; Josip Car; Aziz Sheikh; Azeem Majeed
Journal:  Cochrane Database Syst Rev       Date:  2011-12-07

2.  Smoking and quantitative ultrasound parameters in the calcaneus in 36-year-old men and women.

Authors:  Claire M Bernaards; Jos W R Twisk; Jan Snel; Willem van Mechelen; Paul Lips; Han C G Kemper
Journal:  Osteoporos Int       Date:  2004-02-28       Impact factor: 4.507

3.  Leemoo, a dietary assessment and nutritional planning software, using fuzzy logic.

Authors:  Hanieh-Sadat Ejtahed; Mohammad Mahdi Sarsharzadeh; Parvin Mirmiran; Golaleh Asghari; Emad Yuzbashian; Fereidoun Azizi
Journal:  Int J Endocrinol Metab       Date:  2013-10-11

4.  The ANIBES Study on Energy Balance in Spain: design, protocol and methodology.

Authors:  Emma Ruiz; José Manuel Ávila; Adrián Castillo; Teresa Valero; Susana del Pozo; Paula Rodriguez; Javier Aranceta Bartrina; Ángel Gil; Marcela González-Gross; Rosa M Ortega; Lluis Serra-Majem; Gregorio Varela-Moreiras
Journal:  Nutrients       Date:  2015-02-04       Impact factor: 5.717

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.