Denominator Issues for Personally Generated Data in Population Health Monitoring.
作者信息
Chunara Rumi, Wisk Lauren E, Weitzman Elissa R
机构信息
Department of Computer Science and Engineering, New York University Tandon School of Engineering, Brooklyn, New York; College of Global Public Health, New York University, New York, New York.
Division of Adolescent/Young Adult Medicine, Boston Children's Hospital, Boston, Massachusetts; Department of Pediatrics, Harvard Medical School, Harvard University, Boston, Massachusetts.
出版信息
Am J Prev Med. 2017 Apr;52(4):549-553. doi: 10.1016/j.amepre.2016.10.038. Epub 2016 Dec 21.
Abstract
摘要
相似文献
1
Denominator Issues for Personally Generated Data in Population Health Monitoring.人口健康监测中个人生成数据的分母问题。
Am J Prev Med. 2017 Apr;52(4):549-553. doi: 10.1016/j.amepre.2016.10.038. Epub 2016 Dec 21.
2
Bias.偏差。
J Epidemiol Community Health. 2004 Aug;58(8):635-41. doi: 10.1136/jech.2003.008466.
3
Optimizing telephone-based population sampling.优化基于电话的人群抽样
Ann Epidemiol. 2006 Apr;16(4):273-4. doi: 10.1016/j.annepidem.2005.04.016. Epub 2005 Sep 26.
4
Unobtrusive Measures.非介入性措施
Medsurg Nurs. 2017 Jan-Feb;26(1):59, 61.
5
Sampling issues in qualitative research.定性研究中的抽样问题。
Nurse Res. 2004;12(1):7-19. doi: 10.7748/nr2004.07.12.1.7.c5927.
6
Seven strategies for successful surveys.
J Pediatr Health Care. 2006 May-Jun;20(3):210-3. doi: 10.1016/j.pedhc.2006.02.004.
7
Ranking of cities according to public health criteria: pitfalls and opportunities.根据公共卫生标准对城市进行排名：陷阱与机遇
Am J Public Health. 2004 Apr;94(4):546-9. doi: 10.2105/ajph.94.4.546.
8
Responses to survey research: transparency and representativeness are key.对调查研究的回应：透明度和代表性是关键。
Clin Ther. 2007 Mar;29(3):466-8. doi: 10.1016/s0149-2918(07)80084-1.
9
Last observation carried forward.末次观察值结转
Tidsskr Nor Laegeforen. 2019 May 23;139(9). doi: 10.4045/tidsskr.19.0061. Print 2019 May 28.
10
The trustworthiness of surveys.调查的可信度。
Nutrition. 2004 Oct;20(10):949. doi: 10.1016/j.nut.2004.06.018.
引用本文的文献
1
Associations Between Patient-Reported Outcome Measures of Physical and Psychological Functioning and Willingness to Share Social Media Data for Research Among Adolescents With a Chronic Rheumatic Disease: Cross-Sectional Survey.慢性风湿性疾病青少年患者报告的身体和心理功能结局测量与愿意分享社交媒体数据用于研究之间的关联：横断面调查
JMIR Pediatr Parent. 2023 Dec 6;6:e46555. doi: 10.2196/46555.
2
Search Term Identification Methods for Computational Health Communication: Word Embedding and Network Approach for Health Content on YouTube.计算健康传播中的搜索词识别方法：YouTube上健康内容的词嵌入与网络方法
JMIR Med Inform. 2022 Aug 30;10(8):e37862. doi: 10.2196/37862.
3
Building Public Health Surveillance 3.0: Emerging Timely Measures of Physical, Economic, and Social Environmental Conditions Affecting Health.构建公共卫生监测 3.0：新兴的及时措施，用于衡量影响健康的物理、经济和社会环境条件。
Am J Public Health. 2022 Oct;112(10):1436-1445. doi: 10.2105/AJPH.2022.306917. Epub 2022 Aug 4.
4
Estimating the global and regional burden of meningitis in children caused by type b: A systematic review and meta-analysis.估计乙型脑膜炎在儿童中的全球和区域负担：系统评价和荟萃分析。
J Glob Health. 2022 Mar 5;12:04014. doi: 10.7189/jogh.12.04014. eCollection 2022.
5
Effects of Patient-Generated Health Data: Comparison of Two Versions of Long-Term Mobile Personal Health Record Usage Logs.患者生成的健康数据的影响：两种版本的长期移动个人健康记录使用日志的比较。
Healthcare (Basel). 2021 Dec 28;10(1):53. doi: 10.3390/healthcare10010053.
6
Psychoeducational Messaging to Reduce Alcohol Use for College Students With Type 1 Diabetes: Internet-Delivered Pilot Trial.针对 1 型糖尿病大学生的减少饮酒的心理教育信息传递：互联网交付的试点试验。
J Med Internet Res. 2021 Sep 30;23(9):e26418. doi: 10.2196/26418.
7
Rapid deployment of a community engagement study and educational trial via social media: implementation of the UC-COVID study.通过社交媒体快速开展社区参与研究和教育试验：UC-COVID 研究的实施。
Trials. 2021 Aug 2;22(1):513. doi: 10.1186/s13063-021-05467-3.
8
Rapid Deployment of A Community Engagement Study And Educational Trial Via Social Media: Implementation of The UC-COVID Study.通过社交媒体快速开展社区参与研究和教育试验：加州大学 COVID 研究的实施
Res Sq. 2021 May 7:rs.3.rs-359099. doi: 10.21203/rs.3.rs-359099/v1.
9
Comparison of Social Media, Syndromic Surveillance, and Microbiologic Acute Respiratory Infection Data: Observational Study.社交媒体、症状监测和微生物学急性呼吸道感染数据的比较：观察性研究。
JMIR Public Health Surveill. 2020 Apr 24;6(2):e14986. doi: 10.2196/14986.
10
Pharmaceutical Perspective: How Digital Biomarkers and Contextual Data Will Enable Therapeutic Environments.药学视角：数字生物标志物和背景数据如何推动治疗环境发展。
Digit Biomark. 2017 Aug 17;1(1):73-81. doi: 10.1159/000479951. eCollection 2017 Sep-Dec.
本文引用的文献
1
Incorporating Patient-Reported Outcomes Into Health Care To Engage Patients And Enhance Care.将患者报告的结果纳入医疗保健，以促使患者参与并改善护理。
Health Aff (Millwood). 2016 Apr;35(4):575-82. doi: 10.1377/hlthaff.2015.1362.
2
Influmeter - an online tool for self-reporting of influenza-like illness in Denmark.丹麦流感样疾病自我报告的在线工具：Influmeter。
Infect Dis (Lond). 2016 Apr;48(4):322-327. doi: 10.3109/23744235.2015.1122224. Epub 2015 Dec 11.
3
Combining Search, Social Media, and Traditional Data Sources to Improve Influenza Surveillance.结合搜索、社交媒体和传统数据源以改善流感监测。
PLoS Comput Biol. 2015 Oct 29;11(10):e1004513. doi: 10.1371/journal.pcbi.1004513. eCollection 2015 Oct.
4
Flu Near You: Crowdsourced Symptom Reporting Spanning 2 Influenza Seasons.你身边的流感：跨越两个流感季节的众包症状报告
Am J Public Health. 2015 Oct;105(10):2124-30. doi: 10.2105/AJPH.2015.302696. Epub 2015 Aug 13.
5
Estimating influenza attack rates in the United States using a participatory cohort.使用参与性队列研究估算美国的流感发病率。
Sci Rep. 2015 Apr 2;5:9540. doi: 10.1038/srep09540.
6
A new initiative on precision medicine.一项关于精准医学的新倡议。
N Engl J Med. 2015 Feb 26;372(9):793-5. doi: 10.1056/NEJMp1500523. Epub 2015 Jan 30.
7
What can digital disease detection learn from (an external revision to) Google Flu Trends?数字疾病检测能从（外部修订版的）谷歌流感趋势中学到什么？
Am J Prev Med. 2014 Sep;47(3):341-7. doi: 10.1016/j.amepre.2014.05.020. Epub 2014 Jul 2.
8
Determinants of follow-up participation in the Internet-based European influenza surveillance platform Influenzanet.基于互联网的欧洲流感监测平台Influenzanet中随访参与的决定因素。
J Med Internet Res. 2014 Mar 10;16(3):e78. doi: 10.2196/jmir.3010.
9
Could behavioral medicine lead the web data revolution?行为医学能引领网络数据革命吗？
JAMA. 2014 Apr 9;311(14):1399-400. doi: 10.1001/jama.2014.1505.
10
Why we need crowdsourced data in infectious disease surveillance.为什么我们需要传染病监测中的众包数据。
Curr Infect Dis Rep. 2013 Aug;15(4):316-9. doi: 10.1007/s11908-013-0341-5.
Zotero 插件