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.
Keywords: dietary assessment method; e-learning; hybrid learning methods; innovative process; professional community; training methods.
Copyright © 2022 Le Donne, Piccinelli, Sette, Martone, Catasta, Censi, Comendador Azcarraga, D’Addezio, Ferrari, Mistura, Pettinelli, Saba, Barbina, Guerrera, Carbone, Mazzaccara and Turrini.