Diverse Attitudes and Experiences With Technology Use During the COVID-19 Pandemic Among Asian American and Pacific Islander Adults (the COMPASS Study): Survey Study
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic forced the world to quarantine to slow the rate of transmission, causing communities to transition into virtual spaces. Asian American and Pacific Islander communities faced the additional challenge of discrimination that stemmed from racist and xenophobic rhetoric in the media. Limited data exist on technology use among Asian American and Pacific Islander adults during the height of the COVID-19 shelter-in-place period and its effect on their physical and mental health. OBJECTIVE: This study aims to examine Asian American and Pacific Islander adults' attitudes, perspectives, and experiences regarding their use of technology during the COVID-19 pandemic. METHODS: We collaborated with community partners and used social media to distribute the COVID-19 Effects on the Mental and Physical Health of Asian Americans and Pacific Islanders Survey Study, a nationwide multilingual survey available in English, Chinese, Korean, Samoan, and Vietnamese. The survey was administered from October 2020 to February 2021, and participants rated their level of agreement (1=not at all to 5=extremely) on 6 items assessing their attitudes toward technology use. Thematic analysis was conducted on responses to the open-ended question "Is there anything else you want to tell us about your use of technology during COVID-19?" The qualitative responses were reviewed, analyzed, coded, and organized into corresponding themes. RESULTS: The mean age of respondents was 45.9 (SD 16.3; range 18-98) years, with 5398 participants completing the quantitative survey and 1115 (20.66%) providing unique responses to the open-ended question. In the quantitative survey, 68% (3671/5398) of the respondents reported being comfortable using technology; the majority indicated that it helped them keep up with the news (4318/5398, 79.99%), maintain social connections (4102/5398, 75.99%), and provide care for others (2537/5398, 46.99%). However, responses were mixed regarding the usefulness of technology for health: 39.99% (2159/5398) agreed that it was helpful for mental health but disagreed regarding physical health. Four main themes emerged from the qualitative analysis: (1) technology was critical for functioning across many aspects of life and maintaining physical, mental, and emotional well-being; (2) technology was often the only means of interpersonal social connections; (3) overuse led to negative physical and mental health outcomes; and (4) technology use was associated with multiple challenges and barriers. CONCLUSIONS: Our findings revealed diverse perspectives and experiences related to technology use by Asian American and Pacific Islander adults during the height of the COVID-19 pandemic. Dependence on technology may have exacerbated social inequities, particularly for those with lack of access to devices and Wi-Fi and limited English proficiency, affecting their ability to work, apply for jobs, and communicate virtually. Further qualitative research would be beneficial in amplifying the perspectives of Asian American and Pacific Islander adults to uncover concerns and address health disparities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".