Dietary assessment training: The Italian IV SCAI study on 10-74 year-old individuals' food consumption.

dietary assessment method e-learning hybrid learning methods innovative process professional community training methods

Journal

Frontiers in nutrition
ISSN: 2296-861X
Titre abrégé: Front Nutr
Pays: Switzerland
ID NLM: 101642264

Informations de publication

Date de publication:
2022
Historique:
received: 27 05 2022
accepted: 15 07 2022
entrez: 5 9 2022
pubmed: 6 9 2022
medline: 6 9 2022
Statut: epublish

Résumé

Dietary surveys are conducted to examine the population's dietary patterns that require a complex system of databases, and rules for constructing the data matrix (precision, coding, deriving new variables, e.g., body mass index from individual's height and weight, classes, e.g., age-class, socio-economic status, physical activity, etc.). Management of the data collection requires specialized fieldworkers to allow for the collection of harmonized and standardized data. In this way, only statistical variability is envisaged and any eventual biases are due to probabilistic distribution but data are not affected by inaccuracy. Training the fieldworkers is a crucial part of each dietary survey. The idea to provide constant training throughout the whole survey period, from the preparatory phase to the data collection phase, relies on the necessity to train fieldworkers and monitor the skills acquired during the study, in addition to helping fieldworkers to gain the necessary experience. This study aims to relate the experience in conducting the course path to high specialized interviewers who carried out the cycle devoted to the 10-74 age class of the fourth nationwide food consumption study in Italy (IV SCAI ADULT) according to the European Food Safety Authority (EFSA) guide. A course path was structured in three steps corresponding to the preparation, pilot, and collection phases. The whole path achieved the goal of collecting data related to 12 individuals by each participant, with an overall success rate (successful trainees/total participants) of 16.8% (84 out of an initial 500). The study aimed to provide good quality data in the short term and a highly specialized community in the long term. Surveillance nutritional systems can count on a highly skilled community, so decision-making in public health nutrition and a sustainable and healthy food system can rely on this infrastructure.

Identifiants

pubmed: 36061894
doi: 10.3389/fnut.2022.954939
pmc: PMC9431366
doi:

Types de publication

Journal Article

Langues

eng

Pagination

954939

Informations de copyright

Copyright © 2022 Le Donne, Piccinelli, Sette, Martone, Catasta, Censi, Comendador Azcarraga, D’Addezio, Ferrari, Mistura, Pettinelli, Saba, Barbina, Guerrera, Carbone, Mazzaccara and Turrini.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Cinzia Le Donne (C)

CREA Research Centre for Food and Nutrition, Rome, Italy.

Raffaela Piccinelli (R)

CREA Research Centre for Food and Nutrition, Rome, Italy.

Stefania Sette (S)

CREA Research Centre for Food and Nutrition, Rome, Italy.

Deborah Martone (D)

CREA Research Centre for Food and Nutrition, Rome, Italy.

Giovina Catasta (G)

CREA Research Centre for Food and Nutrition, Rome, Italy.

Laura Censi (L)

CREA Research Centre for Food and Nutrition, Rome, Italy.

Francisco Javier Comendador Azcarraga (FJ)

CREA Research Centre for Food and Nutrition, Rome, Italy.

Laura D'Addezio (L)

CREA Research Centre for Food and Nutrition, Rome, Italy.

Marika Ferrari (M)

CREA Research Centre for Food and Nutrition, Rome, Italy.

Lorenza Mistura (L)

CREA Research Centre for Food and Nutrition, Rome, Italy.

Antonella Pettinelli (A)

CREA Research Centre for Food and Nutrition, Rome, Italy.

Anna Saba (A)

CREA Research Centre for Food and Nutrition, Rome, Italy.

Donatella Barbina (D)

National Institute of Health, Rome, Italy.

Debora Guerrera (D)

National Institute of Health, Rome, Italy.

Pietro Carbone (P)

National Institute of Health, Rome, Italy.

Alfonso Mazzaccara (A)

National Institute of Health, Rome, Italy.

Aida Turrini (A)

Independent Researcher (Former Council for Agricultural Research and Economics (CREA)), Scansano, Italy.

Classifications MeSH