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Augmented reality (AR) technologies could enhance learning in several ways. The quality of an AR-based educational platform is a combination of key features that manifests in usability, usefulness, and enjoyment for the learner. In this paper, we present a multidimensional model to measure the quality of an AR-based application as perceived by students. The model is specified by a second-order factor (perceived quality) and three dimensions: ergonomic quality, learning quality, and hedonic quality. The purpose of this model is to embody previous research into a coherent framework for the evaluation of AR-based educational platforms and to provide guidance for researchers and practitioners. The model was empirically validated on a Chemistry learning scenario and the results confirm the importance of both the learning and hedonic quality. [ABSTRACT FROM PUBLISHER]

Background/Objectives: Dystonia is a neurological movement disorder characterized by involuntary muscle contractions that lead to abnormal movements and postures; it has a major impact on patients' health-related quality of life (HRQoL). The aim of this study was to examine the HRQoL of Romanian patients with dystonia using the EQ-5D-5L instrument. Methods: Responses to the EQ-5D-5L and the visual analogue scale (VAS) were collected alongside demographic and clinical characteristics. Health profiles were analyzed via the metrics of the EQ-5D-5L, severity levels, and age groups. Using Shannon's indexes, we calculated informativity both for patients' health profile as a whole and each individual dimension. Level sum scores (LSS) of the EQ-5D-5L were calculated and compared with scores from the EQ-5D-5L index and VAS. The HRQoL measures were analyzed through demographic and clinical characteristics. Descriptive statistics, Spearman correlation, and non-parametric tests (Mann–Whitney U or Kruskall–Wallis H) were used. The level of agreement between HRQoL measures was assessed using their intraclass correlation coefficient (ICC) and Bland–Altman plots. Results: A sample of 90 patients was used, around 75.6% of whom were female patients, and the mean age at the beginning of the survey was 58.7 years. The proportion of patients reporting "no problems" in all five dimensions was 10%. The highest frequency reported was "no problems" in self-care (66%), followed by "no problems" in mobility (41%). Shannon index and Shannon evenness index values showed higher informativity for pain/discomfort (2.07 and 0.89, respectively) and minimal informativity for self-care (1.59 and 0.68, respectively). The mean EQ-5D-5L index, LSS, and VAS scores were 0.74 (SD = 0.26), 0.70 (SD = 0.24), and 0.61 (SD = 0.21), respectively. The Spearman correlations between HRQoL measures were higher than 0.60. The agreement between the EQ-5D-5L index and LSS values was excellent (ICC = 0.970, 95% CI = 0.934–0.984); the agreement was poor-to-good between the EQ-5D-5L index and VAS scores (ICC = 683, 95% CI = 0.388–0.820), and moderate-to-good between the LSS and VAS scores (ICC = 0.789, 95% CI = 0.593–0.862). Conclusions: Our results support the utilization of the EQ-5D-5L instrument in assessing the HRQoL of dystonia patients, and empirical results suggest that the EQ-5D-5L index and LSS measure may be used interchangeably. The findings from this study highlight that HRQoL is complex in patients with dystonia, particularly across different age groups. [ABSTRACT FROM AUTHOR]

The vINCI technology represents an innovative instrument developed specifically but not exclusively for older adults by technology researchers together with a medical team specialized in geriatrics and gerontology. It was designed to be independently and effortlessly used by older adults in the comfort and safety of their own environment. It is a modular and flexible platform that can integrate a large array of various sensors and can easily adapt to specific healthcare needs. The pilot study tested sensors and standardized instruments capable of evaluating several care-related parameters and of generating personalized feedback for the user dedicated to optimizing physical activity level, social interaction, and health-related quality of life. Moreover, the system was able to detect and signal events and health-related aspects that would require medical assistance. This paper presents how the innovative vINCI technology improves quality of life in older adults. This is evidenced by the results obtained following the clinical validation of the vINCI technology by older adults admitted to the Ana Aslan National Institute of Gerontology and Geriatrics (NIGG) in Bucharest. [ABSTRACT FROM AUTHOR]