The purpose of this paper was to develop a predictor model for an online nutrition course on sugar reduction. The proposed model is based on health knowledge, healthy behavior, social support, self-efficacy, attitude and the health belief model in relation to people’s behavior within a Facebook group. Subsequently, the model can be used to design a robust online training course for human resources, thereby reducing the training costs which managers have experienced as being expensive.
A single pre-post experimental group design was used. Pre and post data were collected from 100 Facebook users using an online questionnaire, within a three-week intervention.
The results show a significant difference between pre- and post-test scores of health knowledge and healthy behavior, indicating an effective intervention. In addition, perceived barriers, attitude, self-efficacy and emotional support were significant predictors of the healthy behavior model, predicting 70 percent of healthy behavior. However, knowledge had no significant relationship with any of the three dependent variables (self-efficacy, attitude and healthy behavior) proposed.
This model has proved to be an effective intervention which can be used in online training of human resources, because the content of the training is known from the predictor model, thereby greatly reducing the training cost, since everything is done online. Moreover, the provided model and predictors show that the content to be delivered in the training program is not knowledge but perceived barriers, attitude, self-efficacy and emotional support.
This study is one of the first to propose an integrative model that suggests attitude and self-efficacy as key predictors of healthy behavior whereas knowledge is not.
No potential conflict of interest was reported by the authors. This research did not receive any specific grant from funding agencies in the public, commercial, or nonprofit sectors.
Weng, C., Matere, I.M., Rathinasabapathi, A. and Chu, A.Z. (2019), "The myth of knowledge within a robust nutrition online training course", Online Information Review, Vol. 44 No. 1, pp. 162-180. https://doi.org/10.1108/OIR-05-2019-0168Download as .RIS
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