The Effects of Online Homeschooling on Children, Parents, and Teachers of Grades 1-9 During the COVID-19 Pandemic.

BACKGROUND Beginning in the 2020 spring semester, due to the COVID-19 pandemic, all school-age children in China were homeschooled via live/recorded broadcasts, online group communication, and software-based homework submission. This study assessed the effects of and proper preparation for this educational approach. MATERIAL AND METHODS The homeschooling behaviors and feelings of school-age children were assessed with 2010 online surveys obtained separately from students, parents, and teachers of grades 1-9 in 15 Chinese provinces. Answers were compared among low- (grades 1-3), middle- (grades 4-6), and high- (grades 7-9) grade groups. The chi-square test was used to identify significant differences between groups. RESULTS We found that 76% of the respondents thought the homeschooling style was acceptable. However, teachers were concerned that students' interest, focus, and academic performance would decline. Sixty-nine percent of the parents reported their children had more than 3 hours of daily screen time, and 82% of students had less than 2 hours of daily outdoor activity. Ninety-five percent of the parents were concerned about their children's eyesight. Additionally, 17.6% of the students were suspected to have emotional or behavioral problems according to the parent-rated Strengths and Difficulties Questionnaire (SDQ) results. The Self-Rating Anxiety Scale (SAS) results of parents and teachers showed higher levels of anxiety than usual. CONCLUSIONS Students should continue the going-to-school rhythm at home to cope with changes caused by the COVID-19 pandemic. Integrated grade-specific approaches are needed. Because long screen time and insufficient outdoor activities can severely affect children's eyesight, appropriate eye-protection measures should be implemented.

[Developmental level of joint attention ability in children aged 16-30 months and related influencing factors].

OBJECTIVE: To investigate the developmental level of joint attention ability in children aged 16-30 months and factors influencing the developmental level. METHODS: A questionnaire survey was performed among 1 675 children aged 16-30 months who visited the Department of Child Health Care in Guangdong Women and Children's Hospital between September and December, 2016 to investigate their joint attention ability and related influencing factors. RESULTS: Of the 1 675 children, 1 579 (94.27%) had reactive joint attention ability at the age of 16-30 months, and 1 428 (85.25%) had active joint attention ability. The percentages of children with reactive joint attention ability and active joint attention ability in boys were lower than in girls (P<0.001). Mother's age, father's occupation, annual family income, way of conception, intended or unintended pregnancy, and mode of delivery were factors influencing the total score of joint attention ability and the scores of reactive/active joint attention ability (P<0.05). CONCLUSIONS: Most children have reactive joint attention ability and active joint attention ability at the age of 16-30 months. During this period of age, boys tend to have poorer joint attention ability than girls. Mother's age, father's occupation, annual family income, way of conception, intended or unintended pregnancy, and mode of delivery are associated with the development of joint attention.

Development of an interpretable machine learning-based intelligent system of exercise prescription for cardio-oncology preventive care: A study protocol.

Background: Cardiovascular disease (CVD) and cancer are the first and second causes of death in over 130 countries across the world. They are also among the top three causes in almost 180 countries worldwide. Cardiovascular complications are often noticed in cancer patients, with nearly 20% exhibiting cardiovascular comorbidities. Physical exercise may be helpful for cancer survivors and people living with cancer (PLWC), as it prevents relapses, CVD, and cardiotoxicity. Therefore, it is beneficial to recommend exercise as part of cardio-oncology preventive care. Objective: With the progress of deep learning algorithms and the improvement of big data processing techniques, artificial intelligence (AI) has gradually become popular in the fields of medicine and healthcare. In the context of the shortage of medical resources in China, it is of great significance to adopt AI and machine learning methods for prescription recommendations. This study aims to develop an interpretable machine learning-based intelligent system of exercise prescription for cardio-oncology preventive care, and this paper presents the study protocol. Methods: This will be a retrospective machine learning modeling cohort study with interventional methods (i.e., exercise prescription). We will recruit PLWC participants at baseline (from 1 January 2025 to 31 December 2026) and follow up over several years (from 1 January 2027 to 31 December 2028). Specifically, participants will be eligible if they are (1) PLWC in Stage I or cancer survivors from Stage I; (2) aged between 18 and 55 years; (3) interested in physical exercise for rehabilitation; (4) willing to wear smart sensors/watches; (5) assessed by doctors as suitable for exercise interventions. At baseline, clinical exercise physiologist certificated by the joint training program (from 1 January 2023 to 31 December 2024) of American College of Sports Medicine and Chinese Association of Sports Medicine will recommend exercise prescription to each participant. During the follow-up, effective exercise prescription will be determined by assessing the CVD status of the participants. Expected outcomes: This study aims to develop not only an interpretable machine learning model to recommend exercise prescription but also an intelligent system of exercise prescription for precision cardio-oncology preventive care. Ethics: This study is approved by Human Experimental Ethics Inspection of Guangzhou Sport University. Clinical trial registration: http://www.chictr.org.cn, identifier ChiCTR2300077887.