Psychometric Evaluation of the German Version of the Dietary Fat and Free Sugar-Short Questionnaire

Background: The Dietary Fat and free Sugar – Short Questionnaire (DFS) is a cost- and time-efficient self-report screening instrument to estimate dietary intake of saturated fat and free sugar. To date, only the English version has been psychometrically evaluated. We assessed the psychometric characteristics of the German version of the DFS in normal weight, overweight and obese individuals. Method: 65 adult participants completed a German translation of the DFS and a validated food frequency questionnaire (FFQ). We correlated participants’ percentage of energy intake from saturated fat and free sugar from the FFQ with the DFS scores. To establish test-retest reliability, participants completed the DFS a second time. To investigate convergent validity, we correlated participants DFS scores with self-reported eating behaviour and sensitivity to reward. Results: DFS scores correlated with percentage of energy from free sugar (rs = .443) and saturated fatty acids (rs = .258) but not with non-target nutrients. The correlation between DFS scores and percentage energy from free sugar was not moderated by BMI, whereas the correlation with percentage energy from saturated fat slightly decreased with BMI. Intra-class correlation was .801, suggesting excellent test-retest reliability. DFS scores correlated significantly with restraint of eating behaviour (rs = -.380) and feelings of hunger (rs =.275). Correlations of the DFS score with disinhibited eating and sensitivity to reward failed to be significant. Conclusion: Our results suggest that the German version of the DFS provides a reliable and valid estimation for the dietary saturated fat and free sugar intake of normal weight, overweight, and obese individuals.Peer reviewe

Computational mechanisms of belief updating in relation to psychotic-like experiences

Introduction Psychotic-like experiences (PLEs) may occur due to changes in weighting prior beliefs and new evidence in the belief updating process. It is still unclear whether the acquisition or integration of stable beliefs is altered, and whether such alteration depends on the level of environmental and belief precision, which reflects the associated uncertainty. This motivated us to investigate uncertainty-related dynamics of belief updating in relation to PLEs using an online study design. Methods We selected a sample (n = 300) of participants who performed a belief updating task with sudden change points and provided self-report questionnaires for PLEs. The task required participants to observe bags dropping from a hidden helicopter, infer its position, and dynamically update their belief about the helicopter's position. Participants could optimize performance by adjusting learning rates according to inferred belief uncertainty (inverse prior precision) and the probability of environmental change points. We used a normative learning model to examine the relationship between adherence to specific model parameters and PLEs. Results PLEs were linked to lower accuracy in tracking the outcome (helicopter location) (β = 0.26 ± 0.11, p = 0.018) and to a smaller increase of belief precision across observations after a change point (β = −0.003 ± 0.0007, p < 0.001). PLEs were related to slower belief updating when participants encountered large prediction errors (β = −0.03 ± 0.009, p = 0.001). Computational modeling suggested that PLEs were associated with reduced overall belief updating in response to prediction errors (βPE = −1.00 ± 0.45, p = 0.028) and reduced modulation of updating at inferred environmental change points (βCPP = −0.84 ± 0.38, p = 0.023). Discussion We conclude that PLEs are associated with altered dynamics of belief updating. These findings support the idea that the process of balancing prior belief and new evidence, as a function of environmental uncertainty, is altered in PLEs, which may contribute to the development of delusions. Specifically, slower learning after large prediction errors in people with high PLEs may result in rigid beliefs. Disregarding environmental change points may limit the flexibility to establish new beliefs in the face of contradictory evidence. The present study fosters a deeper understanding of inferential belief updating mechanisms underlying PLEs.Peer Reviewe

Computational mechanisms of belief updating in relation to psychotic-like experiences

Introduction: Psychotic-like experiences (PLEs) may occur due to changes in weighting prior beliefs and new evidence in the belief updating process. It is still unclear whether the acquisition or integration of stable beliefs is altered, and whether such alteration depends on the level of environmental and belief precision, which reflects the associated uncertainty. This motivated us to investigate uncertainty-related dynamics of belief updating in relation to PLEs using an online study design. Methods: We selected a sample (n = 300) of participants who performed a belief updating task with sudden change points and provided self-report questionnaires for PLEs. The task required participants to observe bags dropping from a hidden helicopter, infer its position, and dynamically update their belief about the helicopter's position. Participants could optimize performance by adjusting learning rates according to inferred belief uncertainty (inverse prior precision) and the probability of environmental change points. We used a normative learning model to examine the relationship between adherence to specific model parameters and PLEs. Results: PLEs were linked to lower accuracy in tracking the outcome (helicopter location) (beta = 0.26 +/- 0.11, p = 0.018) and to a smaller increase of belief precision across observations after a change point (beta = -0.003 +/- 0.0007, p < 0.001). PLEs were related to slower belief updating when participants encountered large prediction errors (beta = -0.03 +/- 0.009, p = 0.001). Computational modeling suggested that PLEs were associated with reduced overall belief updating in response to prediction errors (beta(PE) = -1.00 +/- 0.45, p = 0.028) and reduced modulation of updating at inferred environmental change points (beta(CPP) = -0.84 +/- 0.38, p = 0.023). Discussion: We conclude that PLEs are associated with altered dynamics of belief updating. These findings support the idea that the process of balancing prior belief and new evidence, as a function of environmental uncertainty, is altered in PLEs, which may contribute to the development of delusions. Specifically, slower learning after large prediction errors in people with high PLEs may result in rigid beliefs. Disregarding environmental change points may limit the flexibility to establish new beliefs in the face of contradictory evidence. The present study fosters a deeper understanding of inferential belief updating mechanisms underlying PLEs