Teaching and learning musical instruments through ICT: the impact of the COVID-19 pandemic lockdown

The COVID-19 lockdown in education institutions required music teachers to use ICTto continue teaching. This research study, with the use of a Likert type online questionnaire, analyses the ICT activities carried out during this period and the learning conceptions they reflect. The questionnaire consisted of the description of activities which varied, depending on the learning promoted (reproductive or constructive), the learning outcomes (verbal, procedural, or attitudinal), the type of assessment to which the activities were directed, and the presence of cooperative activities. The teachers had to indicate the frequency with which they carried out these activities. The questionnaire was completed by 254 instrumental music teachers from different types of institutions and different levels. The main study outcome was that teachers used reproductive activities more frequently than constructive ones. We also found that most activities were those favouring verbal learning and assessment. The cooperative activities were the least frequent. Finally, through a cluster analysis, we identified three teaching profiles depending on the frequency and type of ICT used: Passive, Active, and Interpretative. The variable that produced the most consistent differences was previous ICT useThis work was supported by Ministerio de Ciencia e Innovacion of Spain (PID2020-114177RB-I00). Guadalupe Lopez- Iñiguez was also supported by the Senior Researcher grant “Expanding reflexivity of professional education in music in times of crises” awarded by the Jenny and Antti Wihuri Foundation in Finlan

Identification and validation of clinical phenotypes with prognostic implications in patients admitted to hospital with COVID-19: a multicentre cohort study

REIPI-SEIMC COVID-19 group and COVID@HULP group.[Background] The clinical presentation of COVID-19 in patients admitted to hospital is heterogeneous. We aimed to determine whether clinical phenotypes of patients with COVID-19 can be derived from clinical data, to assess the reproducibility of these phenotypes and correlation with prognosis, and to derive and validate a simplified probabilistic model for phenotype assignment. Phenotype identification was not primarily intended as a predictive tool for mortality.[Methods] In this study, we used data from two cohorts: the COVID-19@Spain cohort, a retrospective cohort including 4035 consecutive adult patients admitted to 127 hospitals in Spain with COVID-19 between Feb 2 and March 17, 2020, and the COVID-19@HULP cohort, including 2226 consecutive adult patients admitted to a teaching hospital in Madrid between Feb 25 and April 19, 2020. The COVID-19@Spain cohort was divided into a derivation cohort, comprising 2667 randomly selected patients, and an internal validation cohort, comprising the remaining 1368 patients. The COVID-19@HULP cohort was used as an external validation cohort. A probabilistic model for phenotype assignment was derived in the derivation cohort using multinomial logistic regression and validated in the internal validation cohort. The model was also applied to the external validation cohort. 30-day mortality and other prognostic variables were assessed in the derived phenotypes and in the phenotypes assigned by the probabilistic model.[Findings] Three distinct phenotypes were derived in the derivation cohort (n=2667)—phenotype A (516 [19%] patients), phenotype B (1955 [73%]) and phenotype C (196 [7%])—and reproduced in the internal validation cohort (n=1368)—phenotype A (233 [17%] patients), phenotype B (1019 [74%]), and phenotype C (116 [8%]). Patients with phenotype A were younger, were less frequently male, had mild viral symptoms, and had normal inflammatory parameters. Patients with phenotype B included more patients with obesity, lymphocytopenia, and moderately elevated inflammatory parameters. Patients with phenotype C included older patients with more comorbidities and even higher inflammatory parameters than phenotype B. We developed a simplified probabilistic model (validated in the internal validation cohort) for phenotype assignment, including 16 variables. In the derivation cohort, 30-day mortality rates were 2·5% (95% CI 1·4–4·3) for patients with phenotype A, 30·5% (28·5–32·6) for patients with phenotype B, and 60·7% (53·7–67·2) for patients with phenotype C (log-rank test p<0·0001). The predicted phenotypes in the internal validation cohort and external validation cohort showed similar mortality rates to the assigned phenotypes (internal validation cohort: 5·3% [95% CI 3·4–8·1] for phenotype A, 31·3% [28·5–34·2] for phenotype B, and 59·5% [48·8–69·3] for phenotype C; external validation cohort: 3·7% [2·0–6·4] for phenotype A, 23·7% [21·8–25·7] for phenotype B, and 51·4% [41·9–60·7] for phenotype C).[Interpretation] Patients admitted to hospital with COVID-19 can be classified into three phenotypes that correlate with mortality. We developed and validated a simplified tool for the probabilistic assignment of patients into phenotypes. These results might help to better classify patients for clinical management, but the pathophysiological mechanisms of the phenotypes must be investigated.[Funding] Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation, and Fundación SEIMC/GeSIDA.Funding: Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation, and Fundación SEIMC/GeSIDA.Peer reviewe

Compulsive Buying Behavior : Clinical Comparison with Other Behavioral Addictions

Compulsive buying behavior (CBB) has been recognized as a prevalent mental health disorder, yet its categorization into classification systems remains unsettled. The objective of this study was to assess the sociodemographic and clinic variables related to the CBB phenotype compared to other behavioral addictions. Three thousand three hundred and twenty four treatment-seeking patients were classified in five groups: CBB, sexual addiction, Internet gaming disorder, Internet addiction, and gambling disorder. CBB was characterized by a higher proportion of women, higher levels of psychopathology, and higher levels in the personality traits of novelty seeking, harm avoidance, reward dependence, persistence, and cooperativeness compared to other behavioral addictions. Results outline the heterogeneity in the clinical profiles of patients diagnosed with different behavioral addiction subtypes and shed new light on the primary mechanisms of CBB

Unexpected online gambling disorder in late-life : a case report

Background: The lifetime prevalence of problem or Gambling disorder (GD) in the elderly (i.e., those over 60 years old) is reported to range from 0.01 to 10.9%. Research has identified several specific risk factors and vulnerabilities in the elderly. Since the late 1990s, an increase in online GD has been observed in the youth population, whereas casinos, slot machines, and bingo seem to be the activities of choice among the elderly. Interestingly, online GD has not been described in the elderly to date. Case Description: We report an 83-year-old man who started online casino gambling from the age of 80 years, leading to debts that exceeded €30,000. He underwent a full clinical and neuropsychological assessment, without any evidence of cognitive impairment or any associated neurodegenerative disease. However, he had risk factors for GD, including adjustment disorder, stressful life events, previous offline casino GD when 50 years old, and dysfunctional personality traits. The change to online GD may have been due to his isolation, movement difficulties, and his high level of education, which facilitated his access to the Internet. Care management focused on individual cognitive-behavioral therapy. Conclusion: The prevalence of online GD may be underestimated among the elderly, and may increase among isolated old people with movement difficulties and ready access to the Internet. However, late-life GD should be considered a diagnosis of elimination, requiring a full medical, psychiatric (including suicide risk), and cognitive assessment. Specific therapeutic approaches need to be proposed and developed

Internet gaming disorder and online gambling disorder: Clinical and personality correlates

The recent growth of Internet use has led to an increase of potentially problematic behaviors that can be engaged online, such as online gambling or Internet gaming. The aim of this study is to better conceptualize Internet gaming disorder (IGD) by comparing it with gambling disorder (GD) patients who only gamble online (online GD). Methods A total of 288 adult patients (261 online GD and 27 IGD) completed self-reported questionnaires for exploring psychopathological symptoms, food addiction (FA), and personality traits. Results Both clinical groups presented higher psychopathological scores and less functional personality traits when compared with a normative Spanish population. However, when comparing IGD to online GD, some singularities emerged. First, patients with IGD were younger, more likely single and unemployed, and they also presented lower age of disorder onset. In addition, they displayed lower somatization and depressive scores together with lower prevalence of tobacco use but higher FA scores and higher mean body mass index. Finally, they presented lower novelty seeking and persistence traits. Discussion GD is fully recognized as a behavioral addiction, but IGD has been included in the Appendix of DSM-5 as a behavioral addiction that needs further study. Our findings suggest that IGD and online GD patients share some emotional distress and personality traits, but patients with IGD also display some differential characteristics, namely younger age, lower novelty seeking scores and higher BMI, and FA scores. Conclusions IGD presents some characteristics that are not extensive to online GD. These specificities have potential clinical implications and they need to be further studied

The methodology of surveillance for antimicrobial resistance and healthcare-associated infections in Europe (SUSPIRE): a systematic review of publicly available information.

OBJECTIVES: Surveillance is a key component of any control strategy for healthcare-associated infections (HAIs) and antimicrobial resistance (AMR), and public availability of methodologic aspects is crucial for the interpretation of the data. We sought to systematically review publicly available information for HAIs and/or AMR surveillance systems organized by public institutions or scientific societies in European countries. METHODS: A systematic review of scientific and grey literature following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines was performed. Information on HAIs and/or AMR surveillance systems published until 31 October 2016 were included. RESULTS: A total of 112 surveillance systems were detected; 56 from 20 countries were finally included. Most exclusions were due to lack of publicly available information. Regarding AMR, the most frequent indicator was the proportion of resistant isolates (27 of 34 providing information, 79.42%); only 18 (52.9%) included incidence rates; the data were only laboratory based in 33 (78.5%) of the 42 providing this information. Regarding HAIs in intensive care units, all 22 of the systems providing data included central line-associated bloodstream infections, and 19 (86.3%) included ventilator-associated pneumonia and catheter-associated urinary tract infections; incidence density was the most frequent indicator. Regarding surgical site infections, the most frequent procedures included were hip prosthesis, colon surgery and caesarean section (21/22, 95.5%). CONCLUSIONS: Publicly available information about the methods and indicators of the surveillance system is frequently lacking. Despite the efforts of European Centre for Disease Control and Prevention (ECDC) and other organizations, wide heterogeneity in procedures and indicators still exists