e.g. mhealth
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COVID-19–Related Racism and Mental Health Among Asian Americans: Integrative Review
All 29 studies, with a wide range of sample sizes (from N=64 to N=7813), utilized cross-sectional survey designs conducted during the COVID-19 pandemic starting in March 2020, assessing possible associations between individual-level racism and mental health outcomes (Table 2 and Figure 1). All 29 articles received a score above 7 using the JBI Critical Appraisal tool.
Asian Pac Isl Nurs J 2025;9:e63769
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The survey was created and hosted on Qualtrics (Qualtrics International Inc), a web-based software to assist with survey management. The web-based survey consisted of 30 closed questions, 2 open questions, 2 attention checks, 2 screener validation questions (age and country of residence), and 1 CAPTCHA challenge (Multimedia Appendix 1). The survey was developed by the research team with input from a patient and public involvement panel and pilot-tested with individuals external to the research team (n=5).
J Med Internet Res 2025;27:e59591
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A self-administered web-based survey was completed by a select sample of respondents from the EOI. The demographic profile of EOI responses was screened as they were received, with approximately 15 individuals from each geographic location being invited to participate.
J Med Internet Res 2025;27:e63822
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Participation in the survey was completely voluntary, and no incentives or compensation were offered to participants. To participate in the survey, individuals had to have a good command of English, Spanish, French, or Chinese and be either video game players or involved in esports. No further specific eligibility criteria for access were specified, and participants could freely choose to participate.
JMIR Form Res 2025;9:e60476
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In August 2022, a cross-sectional survey was conducted with a nationwide US sample of young adults recruited and enrolled through Prolific, a survey platform that hosts a diverse panel of adults aged ≥18 years. The survey was conducted as part of Trans Health GUIDE, a National Institutes of Health (NIH)-funded project (U01 MH136558) aimed at designing and implementing strategies to address mental health disparities among TGD young adults.
Interact J Med Res 2025;14:e66630
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Determinants of Telehealth Adoption Among Older Adults: Cross-Sectional Survey Study
To ensure the questionnaire’s reliability, a pilot survey was carried out involving 10 older adults. This pretest, which involved contacting 10 older adults before conducting the web-based survey, was conducted to validate the instrument. On the basis of the feedback received, minor adjustments were made to the questionnaire to improve its effectiveness.
This study focused on the factors influencing the intention to adopt telehealth among adults aged ≥60 years in Malaysia.
JMIR Aging 2025;8:e60936
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An empirical analysis based on data from the United States Health Information Trends Survey revealed that OHIS has a positive, relatively large, and statistically significant effect on individual health care demand [21].
J Med Internet Res 2025;27:e66683
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A working group from phact MI developed a cross-sectional survey to assess the time and tediousness of various aspects of SRD creation. phact MI, a nonprofit consortium of medical information leaders from the pharmaceutical industry, conducted the survey using the survey tool Alchemer. The initial contact for the web-based open survey link was emailed to one contact at each of the 33 member companies in March 2023 (see Multimedia Appendix 1 for email wording).
JMIR AI 2025;4:e55277
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This survey set out to engage respondents with and without a history of SH in order to gain insights into their views and knowledge of how different kinds of data are anonymized and used for research and to determine whether there are any differences of opinions between those 2 groups. We also aimed to explore differences between those who had contacted health services for SH and those who had not.
This study was a web-based cross-sectional survey.
JMIR Ment Health 2025;12:e60649
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Teitcher et al [12] recommends checking for inconsistent survey responses, using a CAPTCHA, collecting paradata to examine how individuals are responding to survey questions, tracking personal information (eg, email, home address, or telephone number), checking for encrypted IP addresses or multiple survey entries from the same IP address, enabling cookies to prevent multiple survey completion attempts, and including an interview to determine whether an individual has already participated or is being dishonest
JMIR Form Res 2025;9:e59955
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