Sample Bias in Web-Based Patient-Generated Health Data of Dutch Patients With Gastrointestinal Stromal Tumor: Survey Study

被引:0
|
作者
Dirkson, Anne [1 ]
den Hollander, Dide [2 ,3 ,4 ]
Verberne, Suzan [1 ]
Desar, Ingrid [4 ]
Husson, Olga [2 ,3 ,5 ]
van der Graaf, Winette T. A. [2 ,6 ]
Oosten, Astrid [6 ]
Reyners, Anna K. L. [7 ]
Steeghs, Neeltje [2 ]
van Loon, Wouter [8 ]
van Oortmerssen, Gerard [1 ,9 ]
Gelderblom, Hans [10 ]
Kraaij, Wessel [1 ,11 ]
机构
[1] Leiden Univ, Leiden Inst Adv Comp Sci, Niels Bohrweg 1, NL-2333 CA Leiden, Netherlands
[2] Netherlands Canc Inst, Dept Med Oncol, Amsterdam, Netherlands
[3] Netherlands Canc Inst, Dept Psychosocial Res & Epidemiol, Amsterdam, Netherlands
[4] Radboud Univ Nijmegen, Dept Med Oncol, Med Ctr, Nijmegen, Netherlands
[5] Erasmus MC, Dept Surg Oncol, Rotterdam, Netherlands
[6] Erasmus MC, Dept Med Oncol, Rotterdam, Netherlands
[7] Univ Groningen, Univ Med Ctr Groningen, Dept Med Oncol, Groningen, Netherlands
[8] Leiden Univ, Dept Methodol & Stat, Leiden, Netherlands
[9] Sarcoma Patient Advocacy Global Network, Wolfersheim, Germany
[10] Leiden Univ, Dept Med Oncol, Med Ctr, Leiden, Netherlands
[11] Netherlands Org Appl Sci Res, The Hague, Netherlands
关键词
social media; patient forum; sample bias; representativeness; pharmacovigilance; rare cancer; ADVERSE DRUG-REACTIONS; BREAST-CANCER; SOCIAL MEDIA; BIG DATA; ONLINE; DISCOVERY; PARTICIPATION; DETERMINANTS; ENGAGEMENT; INTERNET;
D O I
10.2196/36755
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: Increasingly, social media is being recognized as a potential resource for patient-generated health data, for example, for pharmacovigilance. Although the representativeness of the web-based patient population is often noted as a concern, studies in this field are limited. Objective: This study aimed to investigate the sample bias of patient-centered social media in Dutch patients with gastrointestinal stromal tumor (GIST). Methods: A population-based survey was conducted in the Netherlands among 328 patients with GIST diagnosed 2-13 years ago to investigate their digital communication use with fellow patients. A logistic regression analysis was used to analyze clinical and demographic differences between forum users and nonusers. Results: Overall, 17.9% (59/328) of survey respondents reported having contact with fellow patients via social media. Moreover, 78% (46/59) of forum users made use of GIST patient forums. We found no statistically significant differences for age, sex, socioeconomic status, and time since diagnosis between forum users (n=46) and nonusers (n=273). Patient forum users did differ significantly in (self-reported) treatment phase from nonusers (P=.001). Of the 46 forum users, only 2 (4%) were cured and not being monitored; 3 (7%) were on adjuvant, curative treatment; 19 (41%) were being monitored after adjuvant treatment; and 22 (48%) were on palliative treatment. In contrast, of the 273 patients who did not use disease-specific forums to communicate with fellow patients, 56 (20.5%) were cured and not being monitored, 31 (11.3%) were on curative treatment, 139 (50.9%) were being monitored after treatment, and 42 (15.3%) were on palliative treatment. The odds of being on a patient forum were 2.8 times as high for a patient who is being monitored compared with a patient that is considered cured. The odds of being on a patient forum were 1.9 times as high for patients who were on curative (adjuvant) treatment and 10 times as high for patients who were in the palliative phase compared with patients who were considered cured. Forum users also reported a lower level of social functioning (84.8 out of 100) than nonusers (93.8 out of 100; P=.008). Conclusions: Forum users showed no particular bias on the most important demographic variables of age, sex, socioeconomic status, and time since diagnosis. This may reflect the narrowing digital divide. Overrepresentation and underrepresentation of patients with GIST in different treatment phases on social media should be taken into account when sourcing patient forums for patient-generated health data. A further investigation of the sample bias in other web-based patient populations is warranted.
引用
收藏
页数:15
相关论文
共 50 条
  • [41] Influenza Screening via Deep Learning Using a Combination of Epidemiological and Patient-Generated Health Data: Development and Validation Study
    Choo, Hyunwoo
    Kim, Myeongchan
    Choi, Jiyun
    Shin, Jaewon
    Shin, Soo-Yong
    JOURNAL OF MEDICAL INTERNET RESEARCH, 2020, 22 (10)
  • [42] Telemedicine in Swedish primary health care-a web-based survey exploring patient satisfaction
    Rockler Meurling, Carl
    Adell, Elisabet
    Wolff, Moa
    Calling, Susanna
    Milos Nymberg, Veronica
    Bolmsjo, Beata Borgstrom
    BMC HEALTH SERVICES RESEARCH, 2023, 23 (01)
  • [43] Analysis of regression based on sampling weights in complex sample survey: Data from the korea youth risk behavior web-based survey
    Byeon, Haewon
    Jin, Heekyung
    Yu, Seonghun
    Cho, Sunghyoun
    International Journal of u- and e- Service, Science and Technology, 2015, 8 (10) : 65 - 74
  • [44] Sexual Function in Patients With Inflammatory Bowel Disease: Results of a Web-Based Health Survey
    Hagan, Matilda
    Jambaulikar, Guruprasad
    Osche-Gauvin, Katherine
    Schwartz, David
    Higginbotham, Tina
    Cross, Ray
    AMERICAN JOURNAL OF GASTROENTEROLOGY, 2014, 109 : S516 - S516
  • [45] Economic Burden and Health Care Access for Patients With Inflammatory Bowel Diseases in China: Web-Based Survey Study
    Yu, Qiao
    Zhu, Chunpeng
    Feng, Shuyi
    Xu, Liyi
    Hu, Shurong
    Chen, Hao
    Chen, Hanwen
    Yao, Sheng
    Wang, Xiaoying
    Chen, Yan
    JOURNAL OF MEDICAL INTERNET RESEARCH, 2021, 23 (01)
  • [46] A Comparison of Women's and Men's Web-Based Information-Seeking Behaviors About Gender-Related Health Information: Web-Based Survey Study of a Stratified German Sample
    Link, Elena
    Baumann, Eva
    JOURNAL OF MEDICAL INTERNET RESEARCH, 2023, 25
  • [47] Feasibility trial of collecting patient-generated health data using a wearable device and electronic patient-reported outcomes in cancer patients.
    Miyaji, Tempei
    Kawaguchi, Takashi
    Azuma, Kanako
    Suzuki, Shinya
    Sano, Yoko
    Akatsu, Moe
    Torii, Ayako
    Kamimura, Tadamasa
    Ozawa, Yuki
    Tsuchida, Akihiko
    Eriguchi, Daisuke
    Haraguchi, Mizuha
    Nishino, Makoto
    Tokuda, Yoshiki
    Nishi, Yoshiko
    Nishi, Motohide
    Takeya, Rintaro
    Inadome, Yumi
    Yamazaki, Tsutomu
    Yamaguchi, Takuhiro
    JOURNAL OF CLINICAL ONCOLOGY, 2018, 36 (15)
  • [48] Use of Web-Based Health Services in Individuals With and Without Symptoms of Hypochondria: Survey Study
    Eichenberg, Christiane
    Schott, Markus
    JOURNAL OF MEDICAL INTERNET RESEARCH, 2019, 21 (06)
  • [49] Machine Learning-Based COVID-19 Patients Triage Algorithm Using Patient-Generated Health Data from Nationwide Multicenter Database
    Min Sue Park
    Hyeontae Jo
    Haeun Lee
    Se Young Jung
    Hyung Ju Hwang
    Infectious Diseases and Therapy, 2022, 11 : 787 - 805
  • [50] Machine Learning-Based COVID-19 Patients Triage Algorithm Using Patient-Generated Health Data from Nationwide Multicenter Database
    Park, Min Sue
    Jo, Hyeontae
    Lee, Haeun
    Jung, Se Young
    Hwang, Hyung Ju
    INFECTIOUS DISEASES AND THERAPY, 2022, 11 (02) : 787 - 805