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The purpose of this study was to determine the perceptions of students towards e-learning during the lock down. A descriptive cross-sectional study was conducted at Liaquat College of Medicine and Dentistry. MBBS and BDS students of all levels participated in the study with a sample size calculated as 377. A self-administered questionnaire was developed. After validation from the Medical Education Experts, pilot test was run on 30 participants before the administration of the questionnaire. The questionnaire was emailed to the participants for data collection. Reliability of the questionnaire was determined. Independent T-test was applied for determining the perceptions of students towards e-learning. Frequencies and percentages were also computed for demographics. Total 382 responses were received.137 males and 245 females participated in the study. 0.851 was calculated as Cronbach's alpha of the questionnaire. Overall, 77% students have negative perceptions towards e-learning. 76% of the students use mobile device for their e-learning. Students did not prefer e-teaching over face-to-face teaching during the lock down situation. Administration and faculty members should take necessary measures for improving e-teaching for better learning during lock down.

This study compares learner perceptions in a synchronous online versus face‐to‐face (F2F) learning context about four principles of communicative language teaching (CLT): promoting collaborative learning, using comprehensible input, considering affective factors, and providing corrective feedback. Data were obtained via online surveys from students in F2F language classes (n = 330) and synchronous online language classes (n = 315). The results generally show high levels of agreement between the two groups with statements pertaining to the implementation of all four principles, suggesting that overall, participants perceived the two learning contexts to be similar to one another. However, results reveal that for particular dimensions of these principles, students in the two contexts disagreed (small to medium effect sizes), indicating depressed levels of agreement for learners in the online context. We discuss how these areas of disagreement serve as an opportunity for enhancement of the implementation of specific components of CLT in online synchronous settings.

Scientific conferences are a key component of academic communication and development. During the COVID‐19 pandemic, in‐person conferences are rapidly moving online, yet these virtual events may not provide the same opportunities as in‐person conferences. If virtual meetings are to continue to provide effective communication and networking between researchers and stakeholders, they must be adapted to increase delegate engagement and enthusiasm. Here, we present a case study of a recent medium‐sized online conference. We assessed the behavior and engagement of delegates with different components of the meeting using data from website analytics and postconference surveys. Behavior was variable across the available events; talks were particularly popular but engagement with social and networking opportunities was variable. Our conclusions have been summarized in six recommendations to support future online conference organizers in enhancing engagement with their events. Here, we present a case study of a recent medium‐sized online conference. We assessed the behavior and engagement of delegates with different components of the meeting using data from website analytics and postconference surveys. Behavior was variable across the available events, with talks being particularly popular but engagement with social and networking opportunities was variable.

Purpose Normative scores (norms) allow for comparisons between population(s) of interest and the general population, which is useful for burden of disease studies and cost-effectiveness analysis. The primary aim of this study was to estimate US visual analogue scale (EQ VAS) and utility-based norms for the EQ-5D-5L using the face-to-face sample. The secondary aim was to compare norms estimated in the face-to-face and online populations. Methods This study estimated population norms from two general population surveys: (a) face-to-face and (b) online. In these surveys, respondents provided their health state using the EQ-5D-5L health classifier and the EQ VAS. Descriptive statistics, including mean, standard deviation (SD), 95% confidence interval, and median for the 5L utility and EQ VAS were estimated for each sample and across relevant respondent characteristics to serve as the basis for US EQ-5D-5L norms Results Face-to-face sample respondents ( n  = 1134) were representative of the US adult general population. In this sample, mean (SD) utility decreased with increasing age until age 45 or greater (age 45–54: 0.816 (0.249) age 55–64: 0.815 (0.243) age 65–74: 0.824 (0.217) age 75 + : 0.811 (0.218)). With increasing age, more problems were reported on all dimensions except anxiety/depression; a smaller proportion of respondents age 65 and older reported problems with anxiety/depression (23.8%) as compared to the youngest respondents (42.1%). Online ( n  = 2018) mean utility and EQ VAS values were consistently lower than the face-to-face sample. Conclusions The availability of US EQ-5D-5L norms facilitates interpretation and understanding of general population and patient health.

Background Although social isolation has been associated with a higher mortality risk, little is known about the potential different impacts of face-to-face and non-face-to-face isolation on mortality. We examined the prospective associations of four types of social isolation, including face-to-face isolation with co-inhabitants and non-co-inhabitants, non-face-to-face isolation, and club/organization isolation, with all-cause and cause-specific mortality separately. Methods This prospective cohort study included 30,430 adults in Guangzhou Biobank Cohort Study (GBCS), who were recruited during 2003–2008 and followed up till Dec 2019. Results During an average of 13.2 years of follow-up, 4933 deaths occurred during 396,466 person-years. Participants who lived alone had higher risks of all-cause (adjusted hazard ratio (AHR) 1.24; 95% confidence interval (CI) 1.04-1.49) and cardiovascular disease (CVD) (1.61; 1.20–2.03) mortality than those who had ≥ 3 co-habitant contact after adjustment for thirteen potential confounders. Compared with those who had ≥ 1 time/month non-co-inhabitant contact, those without such contact had higher risks of all-cause (1.60; 1.20–2.00) and CVD (1.91; 1.20–2.62) mortality. The corresponding AHR (95% CI) in participants without telephone/mail contact were 1.27 (1.14–1.42) for all-cause, 1.30 (1.08–1.56) for CVD, and 1.37 (1.12–1.67) for other-cause mortality. However, no association of club/organization contact with the above mortality and no association of all four types of isolation with cancer mortality were found. Conclusions In this cohort study, face-to-face and non-face-to-face isolation were both positively associated with all-cause, CVD-, and other-cause (but not cancer) mortality. Our finding suggests a need to promote non-face-to-face contact among middle-aged and older adults.

To disseminate, educate, and validate psychiatric clinical practice guidelines, the Effectiveness of Guidelines for Dissemination and Education in Psychiatric Treatment (EGUIDE) project was launched in 2016. In this study, we investigated whether the web‐based courses offered by this project would be as effective as the face‐to‐face courses. We analyzed and compared survey answers about overall participant satisfaction with the course and answers regarding clinical knowledge of schizophrenia and major depressive disorder between 170 participants who took the web‐based courses in 2020 and 689 participants who took the face‐to‐face courses from 2016 to 2019. The web‐based course participants completed the survey questions about satisfaction with the web‐based courses. The web‐based courses were conducted using a combination of web services to make it as similar as possible to the face‐to‐face courses. The degree of satisfaction assessed by the general evaluation of the web‐based courses was higher than what was expected from the face‐to‐face courses. The degree of satisfaction was similar for the courses on schizophrenia and major depressive disorder. In addition, there were no significant differences in overall satisfaction and clinical knowledge between web‐based and face‐to‐face courses. In conclusion, the web‐based courses on clinical practice guidelines provided by the EGUIDE project were rated as more satisfying than the face‐to‐face course that the participants expected to take and no differences in the effectiveness of either course. The results suggest that, after the COVID‐19 pandemic, it would be possible to disseminate this educational material more widely by adopting web‐based courses additionally face‐to‐face courses. We examined how the participants evaluated the web‐based courses on clinical practice guidelines provided by the EGUIDE project and how it differed from the face‐to‐face courses that were provided in the past. The web‐based courses were rated as more satisfying than the face‐to‐face course that the participants expected to take and no differences in the effectiveness of either course.

Previous studies have shown promising results in identifying individuals with autism spectrum disorder (ASD) by applying machine learning (ML) to eye-tracking data collected while participants viewed varying images (ie, pictures, videos, and web pages). Although gaze behavior is known to differ between face-to-face interaction and image-viewing tasks, no study has investigated whether eye-tracking data from face-to-face conversations can also accurately identify individuals with ASD.BACKGROUNDPrevious studies have shown promising results in identifying individuals with autism spectrum disorder (ASD) by applying machine learning (ML) to eye-tracking data collected while participants viewed varying images (ie, pictures, videos, and web pages). Although gaze behavior is known to differ between face-to-face interaction and image-viewing tasks, no study has investigated whether eye-tracking data from face-to-face conversations can also accurately identify individuals with ASD.The objective of this study was to examine whether eye-tracking data from face-to-face conversations could classify children with ASD and typical development (TD). We further investigated whether combining features on visual fixation and length of conversation would achieve better classification performance.OBJECTIVEThe objective of this study was to examine whether eye-tracking data from face-to-face conversations could classify children with ASD and typical development (TD). We further investigated whether combining features on visual fixation and length of conversation would achieve better classification performance.Eye tracking was performed on children with ASD and TD while they were engaged in face-to-face conversations (including 4 conversational sessions) with an interviewer. By implementing forward feature selection, four ML classifiers were used to determine the maximum classification accuracy and the corresponding features: support vector machine (SVM), linear discriminant analysis, decision tree, and random forest.METHODSEye tracking was performed on children with ASD and TD while they were engaged in face-to-face conversations (including 4 conversational sessions) with an interviewer. By implementing forward feature selection, four ML classifiers were used to determine the maximum classification accuracy and the corresponding features: support vector machine (SVM), linear discriminant analysis, decision tree, and random forest.A maximum classification accuracy of 92.31% was achieved with the SVM classifier by combining features on both visual fixation and session length. The classification accuracy of combined features was higher than that obtained using visual fixation features (maximum classification accuracy 84.62%) or session length (maximum classification accuracy 84.62%) alone.RESULTSA maximum classification accuracy of 92.31% was achieved with the SVM classifier by combining features on both visual fixation and session length. The classification accuracy of combined features was higher than that obtained using visual fixation features (maximum classification accuracy 84.62%) or session length (maximum classification accuracy 84.62%) alone.Eye-tracking data from face-to-face conversations could accurately classify children with ASD and TD, suggesting that ASD might be objectively screened in everyday social interactions. However, these results will need to be validated with a larger sample of individuals with ASD (varying in severity and balanced sex ratio) using data collected from different modalities (eg, eye tracking, kinematic, electroencephalogram, and neuroimaging). In addition, individuals with other clinical conditions (eg, developmental delay and attention deficit hyperactivity disorder) should be included in similar ML studies for detecting ASD.CONCLUSIONSEye-tracking data from face-to-face conversations could accurately classify children with ASD and TD, suggesting that ASD might be objectively screened in everyday social interactions. However, these results will need to be validated with a larger sample of individuals with ASD (varying in severity and balanced sex ratio) using data collected from different modalities (eg, eye tracking, kinematic, electroencephalogram, and neuroimaging). In addition, individuals with other clinical conditions (eg, developmental delay and attention deficit hyperactivity disorder) should be included in similar ML studies for detecting ASD.

Abstract Study Objectives In a randomized controlled noninferiority trial, we compared face-to-face and telemedicine delivery (via the AASM SleepTM platform) of cognitive-behavioral therapy (CBT) for insomnia for improving insomnia/sleep and daytime functioning at posttreatment and 3-month follow-up. A secondary objective compared the modalities on treatment credibility, satisfaction, and therapeutic alliance. Methods A total of 65 adults with chronic insomnia (46 women, 47.2 ± 16.3 years of age) were randomized to 6 sessions of CBT for insomnia delivered individually via AASM SleepTM (n = 33, CBT-TM) or face-to-face (n = 32, CBT-F2F). Participants completed sleep diaries, the Insomnia Severity Index (ISI), and daytime functioning measures at pretreatment, posttreatment, and 3-month follow-up. Treatment credibility, satisfaction, and therapeutic alliance were compared between treatment modalities. The ISI was the primary noninferiority outcome. Results Based on a noninferiority margin of four points on the ISI and, after adjusting for confounders, CBT-TM was noninferior to CBT-F2F at posttreatment (β = 0.54, SE = 1.10, 95% CI = 1.64 to 2.72) and follow-up (β = 0.34, SE = 1.10, 95% CI = 1.83 to 2.53). Daytime functioning measures, except the physical composite scale of the SF-12, were significantly improved at posttreatment and follow-up, with no difference between treatment formats. CBT-TM sessions were, on average, nearly 10 min shorter, yet participant ratings of therapeutic alliance were similar to CBT-F2F. Conclusions Telemedicine delivery of CBT for insomnia is not inferior to face-to-face for insomnia severity and yields similar improvements on other sleep and daytime functioning outcomes. Further, telemedicine allows for more efficient treatment delivery while not compromising therapeutic alliance. Clinical Trial Registration Number NCT03293745

This study aims to identify the independent influence of face-to-face contact (FFC) and non-face-to-face contact (NFFC) on the subsequent decline in self-rated health and mental health status by age. A total of 12,000 participants were randomly selected among residents in the study area, and 1751 of them responded to both the 2016 and 2018 mail surveys. The participants were subsequently classified into three age groups (25–49: Young adults; 50–64: Mid-aged adults; and 65–84: Older adults). Social contact was assessed by computing the frequencies of FFC and NFFC. Multiple logistic regression analysis showed the risk of social contact on the decline in self-rated health and World Health Organization-Five Well-Being Index. Both FFC and NFFC were significantly associated with maintaining mental health; however, the impacts of FFC on mental health were more significant than that of NFFC among older adults and young adults. Compared with the no contact group, FFC was significantly associated with maintaining self-rated health in mid-aged adults. The influence of FFC and NFFC on health differed by age group.

Educational life worldwide has been shaken by the closure of schools due to the outbreak of the coronavirus pandemic. The ripple effects have been felt in the way both teachers and students have adapted to the constraints imposed by the new online form of education. The present study focuses exclusively on the beneficiaries of the educational process and aims to find out their perceptions of face-to-face and e-learning and their desire to return, or not, to the traditional form of education. These perceptions are represented by 604 students of the Politehnica University of Timisoara, who were asked to respond anonymously to an 8-question questionnaire between December 2020 and February 2021. The results show the respondents’ levels of desire to return to school (especially of those who have only benefited from e-learning) and their degree of involvement during online classes. The results also specify the advantages and disadvantages of the two forms of education from a double perspective, namely that of first-year students (beneficiaries of e-learning exclusively), and of upper-year students (beneficiaries of both face-to-face and e-learning). The study points out key information about e-learning from the students’ perspectives, which should be considered to understand the ongoing changes of the educational process and to solve its specific problems, thus ensuring its sustainability.