Measuring patient engagement: development and psychometric properties of the Patient Health Engagement (PHE) Scale

Teacher-Rated Executive Functions, Gender and Relative Age: Independent and Interactive Effects on Observed Fundamental Motor Skills in Kindergarteners

Fundamental motor skills (FMS) of children can be affected by different variables, such as executive functions (EF), gender and relative age. However, the effects of these variables on FMS have been scarce studied, especially in early childhood, and show inconsistent results. To clarify these relationships, this study was carried out. Its aim was to analyze whether EF, gender and relative age influenced FMS in 43 Spanish kindergarteners. A multimethod and mixed methods approach was used. Kindergarteners' teachers completed the Childhood Executive Functioning Inventory to know the children level of EF (working memory and inhibition control). Kindergarteners' parents complimented ad hoc questionnaire reporting the children gender and birth data (to know their relative age). A Nomothetic/Punctual/Multidimensional observational design was used to observe children FMS in their habitual motor sessions at school. Two-way ANOVAs were performed to know the independent and interactive effects of working memory level (lower/higher), inhibition control level (lower/higher), gender (boys/girls) and relative age (according to the birth semester in the year) on FMS. Results showed these variables have independent and interactive effects on some FMS, but not on others. FMS influenced by these variables vary depending what independent variable(s) is/are considered. Therefore, it can be concluded that the influences of teacher-rated EF, gender and relative age on observed FMS in kindergarteners are complex and specific. Results obtained must be taken into to design and implement instructional and intervention strategies, as well as educational and sport policy changes, especially in early childhood, when FMS are more malleable.

Responsible Artificial Intelligence (AI) for Value Formation and Market Performance in Healthcare: the Mediating Role of Patient's Cognitive Engagement

The Healthcare sector has been at the forefront of the adoption of artificial intelligence (AI) technologies. Owing to the nature of the services and the vulnerability of a large section of end-users, the topic of responsible AI has become the subject of widespread study and discussion. We conduct a mixed-method study to identify the constituents of responsible AI in the healthcare sector and investigate its role in value formation and market performance. The study context is India, where AI technologies are in the developing phase. The results from 12 in-depth interviews enrich the more nuanced understanding of how different facets of responsible AI guide healthcare firms in evidence-based medicine and improved patient centered care. PLS-SEM analysis of 290 survey responses validates the theoretical framework and establishes responsible AI as a third-order factor. The 174 dyadic data findings also confirm the mediation mechanism of the patient's cognitive engagement with responsible AI-solutions and perceived value, which leads to market performance.

Intertwined Facets of Subjective Time

For decades, researchers in the behavioral sciences have studied how humans judge time accurately. Now they are looking more closely at the conditions in which they fail to do so and why, with the aim of testing the limits of a potential internal timing system (i.e., an internal clock). Recent behavioral studies have thus focused on time distortions, in particular those caused by emotion. They have also begun to examine the awareness of the passage of time and its relation with the perception of durations in different temporal ranges, from a few seconds to several minutes.