FOODLIT-PRO: Food literacy domains, influential factors and determinants—A qualitative study

Poor eating habits are increasing the prevalence of weight-related issues, such as diabetes and cardiovascular diseases. Given the demand to improve individuals’ food knowledge and competencies aiming at healthier behaviours, the current investigation explores the concept of food literacy. Considering the lack of a shared understanding of food literacy, this study aims to explore food literacy’s domains, influential factors and determinants. Using a qualitative deductive-dominant content analysis, 30 experts from food-related fields were interviewed. The obtained outcomes were compared to available food literacy frameworks. Agreement among inter-raters was nearly perfect (k = 0.82). Yielding a total of 184 codes nested within 19 categories, identified domains were Origin, Safety, Choice and Decision, Select and Acquire, Plan, Preserve, Prepare, Cook, and Knowledge; influential factors included Nutrition, Psychological, Health, Learning Contexts, Policy, Industry, Sustainability, and Social and Cultural; External determinants were “Access to Food-Related Information”, “Perishable and/or Unreliable Food-Related Information”, “Family Dynamic and/or Identity”, and “Professionals’ Unpreparedness on Food-Related Expertise”, and Internal determinants included “Prioritise Food”, “Convenience and Practicality”, “Time and Financial Management”, “Previous Food-Related Habits”, and “Innate and Learned Flavour Preferences”. In conclusion, more than half of the identified attributes (62.5%) are corroborated by the current literature. However, the manifested content unmatched with the current frameworks of food literacy literature express food-literacy-related fields of action, knowledge, competencies, and determinants that have not yet been explored. As such, this study provides new and useful information concerning food literacy definition and development, by identifying its domains, factors of influence, and potential determinants. Moreover, this work paves the way for new measurements and interventions within this field

Health Action Process Approach (HAPA) as a Theoretical Framework to Understand Behavior Change

A theoretical framework to explain, predict, and modify health behaviors is presented which consists of various psychological constructs and a mediator mechanism. Risk perception, outcome expectancies, self-efficacy, intention, planning, and action control constitute the building blocks for a mediator model that is based on two processes: goal setting and goal pursuit. When it comes to the development of interventions to modify behaviors, one can target either the initial motivation phase or the subsequent volition phase. This is an open architecture framework allowing for various research designs and subsets of constructs. Hundreds of studies have been conducted based on this model. Three correlational and two intervention studies were chosen to illustrate the diversity of approaches targeting physical activity in Germany and Costa Rica, dental cleaning in India and Poland, and dust mask wearing in China. They differ in terms of the predictors that emerged as most relevant for behavior change

a cross-over longitudinal design

Background Frequent handwashing can prevent infections, but non-compliance to hand hygiene is pervasive. Few theory- and evidence-based interventions to improve regular handwashing are available. Therefore, two intervention modules, a motivational and a self-regulatory one, were designed and evaluated. Methods In a longitudinal study, 205 young adults, aged 18 to 26 years, were randomized into two intervention groups. The Mot-SelfR group received first a motivational intervention (Mot; risk perception and outcome expectancies) followed by a self-regulatory intervention (SelfR; perceived self-efficacy and planning) 17 days later. The SelfR-Mot group received the same two intervention modules in the opposite order. Follow-up data were assessed 17 and 34 days after the baseline. Results Both intervention sequences led to an increase in handwashing frequency, intention, self- efficacy, and planning. Also, overall gains were found for the self-regulatory module (increased planning and self-efficacy levels) and the motivational module (intention). Within groups, the self-regulatory module appeared to be more effective than the motivational module, independent of sequence. Conclusions Self-regulatory interventions can help individuals to exhibit more handwashing. Sequencing may be important as a motivation module (Mot) first helps to set the goal and a self-regulatory module (SelfR) then helps to translate this goal into actual behavior, but further research is needed to evaluate mechanisms

past behavior moderates the prediction of adherence

Background: Vaccination effectively prevents seasonal influenza. To promote vaccination adherence, it is necessary to understand the motivational process that underlies vaccination behavior. This was examined along with the moderating influence of past behavior on intention formation. Methods: German employees (N = 594) completed questionnaires at baseline and at 7-month followup. Regression analyses were conducted for mediation and moderated mediation. Results: Intention at Time 1 mediated the effect of risk perception, and positive and negative outcome expectancies on Time 2 vaccination. Past behavior moderated this effect: there was a mediation effect for risk perception and outcome expectancies only for those individuals who did not participate annually. Conclusions: Risk perception and outcome expectancies influenced intentions to receive vaccination, which in turn predicted participation. Hence, these social-cognitive variables could be targeted in vaccination campaigns to increase intentions. However, vaccination experience affected the formation of intentions and should be accounted for when developing interventions

Risk awareness, self-efficacy, and social support predict secure smartphone usage

It is widely acknowledged that non-compliance with smartphone security behaviors is widespread and may cause severe harm to people and devices. In addition to device-based security issues, there are psychological factors involved in these behaviors such as self-efficacy, risk awareness, and social support. The present study examines associations of these three factors with smartphone security behaviors and explores possible mechanisms among these variables. In a longitudinal survey with 192 Chinese college students (73.4% women, mean age 24.46 years, SD = 5.15), self-efficacy, risk awareness, and social support were assessed with psychometric scales at two points in time, 2 weeks apart. Hierarchical regression analyses were performed with follow-up smartphone security behaviors as the dependent variable, controlling for baseline values and demographic and IT-related covariates. Main effects of self-efficacy, risk awareness, and social support on smartphone security behaviors were identified. Moreover, a triple interaction among the three predictors emerged in a synergistic way, indicating that their combination yielded more favorable levels of secure smartphone use. The total model accounted for 50% of the behavioral variance, with all covariates included, and the triple interaction among self-efficacy, risk awareness, and social support accounted for 2.3% of variance. Results document that psychological factors are involved in smartphone security behaviors beyond demographic and IT-related covariates. Interventions could be designed to improve smartphone security behaviors not only by developing privacy-enhancing technologies but also by considering psychological factors such as self-efficacy, risk awareness, and social support