Self-modeling(SM)and self-control(SC)feedback can be presented as two solutions for learning improvement.Therefore,the aim of the present study was to investigate the effects of SM and SC feedback on 100-m freestyle p...Self-modeling(SM)and self-control(SC)feedback can be presented as two solutions for learning improvement.Therefore,the aim of the present study was to investigate the effects of SM and SC feedback on 100-m freestyle performance of professional swimmers and waterpolo players.25 elite male swimmers and waterpolo players,were randomly assigned to four groups:swimmer group with SM,swimmer group with SM and SC feedback,waterpolo players group with SM,and waterpolo players group with SM and SC feedback.100-m freestyle times and performance were recorded.SM and SC feedback for the participants were utilized at the acquisition stage.The device used included a Lenovo B570 laptop and an Exilim ZR200 canon camcorder.SM and SC feedback presented to the swimmers and waterpolo players led to improved speed and results,and the effect of presenting SM with SC feedback to swimmers had better results.In conclusion,the present study indicates that SC modeling of watching video is a suitable method for professional swimmers.Water polo trainers can also use SM and SC feedback to enhance their players'swimming technique.展开更多
目的探讨基于健康行动过程取向(health action process approach,HAPA)理论的有氧运动干预方案在糖尿病肾病(diabetic nephropathy,DN)患者中的应用效果。方法采用便利抽样法,选取2023年1月-2024年6月南京中医药大学附属医院收治的DN住...目的探讨基于健康行动过程取向(health action process approach,HAPA)理论的有氧运动干预方案在糖尿病肾病(diabetic nephropathy,DN)患者中的应用效果。方法采用便利抽样法,选取2023年1月-2024年6月南京中医药大学附属医院收治的DN住院患者为研究对象,基于随机数字表法将其分为对照组和干预组,对照组实施常规护理,干预组在对照组的基础上实施为期3个月的基于HAPA理论的有氧运动干预方案。比较2组患者干预前后的生化指标、运动自我效能量表、自评抑郁量表、糖尿病生活质量得分。结果最终93例患者完成研究,其中对照组47例、干预组46例。干预后,干预组患者空腹血糖、餐后2 h血糖、糖化血红蛋白、肾小球滤过率、尿微量白蛋白各项指标优于对照组,差异有统计学意义(P<0.05);运动自我效能得分高于对照组,差异有统计学意义(P<0.05);糖尿病生活质量总得分及各维度得分均低于对照组,差异有统计学意义(P<0.05);2组患者抑郁水平差异无统计学意义(P>0.05)。结论基于HAPA理论的有氧运动方案有助于DN患者血糖控制、延缓肾功能下降,提高其运动自我效能和生活质量水平。展开更多
目的构建留守与非留守中学生自伤的风险预测模型,为制定针对性的干预措施提供科学依据。方法2021年9月―2023年6月采用多阶段抽样方法,在留守儿童分布相对集中的6个省份中抽取14623名<18岁的中学生(留守8471名,非留守6152名)作为研...目的构建留守与非留守中学生自伤的风险预测模型,为制定针对性的干预措施提供科学依据。方法2021年9月―2023年6月采用多阶段抽样方法,在留守儿童分布相对集中的6个省份中抽取14623名<18岁的中学生(留守8471名,非留守6152名)作为研究对象。通过问卷调查收集研究对象的一般情况、创伤性事件和自伤发生情况。分析不同特征留守与非留守中学生自伤的发生情况。采用R 4.3.0软件按照7∶3的比例分别将留守与非留守中学生随机划分为训练集与测试集,构建logistic回归分析模型和随机森林模型,通过受试者工作特征曲线、灵敏度、特异度等指标评估模型性能。结果中学生自伤总体发生率为25.7%,留守中学生自伤发生率高于非留守中学生(χ^(2)=59.266,P<0.001)。Logistic回归分析模型分析结果显示,留守与非留守中学生预测模型训练集的曲线下面积(area under the curve,AUC)分别为0.745和0.756,测试集的AUC分别为0.721和0.726,Hosmer-Lemshow拟合优度检验P>0.05。随机森林模型中,留守中学生自伤的主要预测因素为经历创伤性事件、家庭氛围、和父亲/母亲关系等,模型的灵敏度、特异度、阳性预测值、阴性预测值和F1指数分别为0.740、0.591、0.822、0.470和0.779,Brier分数为0.212,训练集和测试集的AUC分别为0.800和0.729。非留守中学生则以经历创伤性事件、家庭氛围、父母感情状况等为主,模型的灵敏度、特异度、阳性预测值、阴性预测值和F1指数分别为0.785、0.519、0.850、0.411和0.816,Brier分数为0.188,训练集和测试集的AUC分别为0.845和0.724。结论留守中学生自伤风险高于非留守中学生,二者的预测因素虽有不同,但存在高度重叠,其中创伤经历和家庭因素是关键预测变量。两种模型对自伤的识别能力良好,但随机森林模型综合性能更优,本研究构建的预测模型可为早期识别高危人群提供科学依据。展开更多
文摘Self-modeling(SM)and self-control(SC)feedback can be presented as two solutions for learning improvement.Therefore,the aim of the present study was to investigate the effects of SM and SC feedback on 100-m freestyle performance of professional swimmers and waterpolo players.25 elite male swimmers and waterpolo players,were randomly assigned to four groups:swimmer group with SM,swimmer group with SM and SC feedback,waterpolo players group with SM,and waterpolo players group with SM and SC feedback.100-m freestyle times and performance were recorded.SM and SC feedback for the participants were utilized at the acquisition stage.The device used included a Lenovo B570 laptop and an Exilim ZR200 canon camcorder.SM and SC feedback presented to the swimmers and waterpolo players led to improved speed and results,and the effect of presenting SM with SC feedback to swimmers had better results.In conclusion,the present study indicates that SC modeling of watching video is a suitable method for professional swimmers.Water polo trainers can also use SM and SC feedback to enhance their players'swimming technique.
文摘目的构建留守与非留守中学生自伤的风险预测模型,为制定针对性的干预措施提供科学依据。方法2021年9月―2023年6月采用多阶段抽样方法,在留守儿童分布相对集中的6个省份中抽取14623名<18岁的中学生(留守8471名,非留守6152名)作为研究对象。通过问卷调查收集研究对象的一般情况、创伤性事件和自伤发生情况。分析不同特征留守与非留守中学生自伤的发生情况。采用R 4.3.0软件按照7∶3的比例分别将留守与非留守中学生随机划分为训练集与测试集,构建logistic回归分析模型和随机森林模型,通过受试者工作特征曲线、灵敏度、特异度等指标评估模型性能。结果中学生自伤总体发生率为25.7%,留守中学生自伤发生率高于非留守中学生(χ^(2)=59.266,P<0.001)。Logistic回归分析模型分析结果显示,留守与非留守中学生预测模型训练集的曲线下面积(area under the curve,AUC)分别为0.745和0.756,测试集的AUC分别为0.721和0.726,Hosmer-Lemshow拟合优度检验P>0.05。随机森林模型中,留守中学生自伤的主要预测因素为经历创伤性事件、家庭氛围、和父亲/母亲关系等,模型的灵敏度、特异度、阳性预测值、阴性预测值和F1指数分别为0.740、0.591、0.822、0.470和0.779,Brier分数为0.212,训练集和测试集的AUC分别为0.800和0.729。非留守中学生则以经历创伤性事件、家庭氛围、父母感情状况等为主,模型的灵敏度、特异度、阳性预测值、阴性预测值和F1指数分别为0.785、0.519、0.850、0.411和0.816,Brier分数为0.188,训练集和测试集的AUC分别为0.845和0.724。结论留守中学生自伤风险高于非留守中学生,二者的预测因素虽有不同,但存在高度重叠,其中创伤经历和家庭因素是关键预测变量。两种模型对自伤的识别能力良好,但随机森林模型综合性能更优,本研究构建的预测模型可为早期识别高危人群提供科学依据。
