Table 1.
Survey Respondent Characteristics
| Variable | Overall | All Tool Users | Non-health Only Tools | Crossover | Health Only Tools | Test Statistica | p Valuea |
|---|---|---|---|---|---|---|---|
| Number of respondents | 1,137 | 820b | 263 | 458 | 98 | ||
| Mean age (SD; range) | 46.4 (15; 18–>89) | 46.7 (15; 18–84) | 51.8 (14; 18–83) | 45.5 (15; 18–84) | 39.4(12; 20–73) | 27.2 | 3.87e−12 |
| Gender | |||||||
| Women (%) | 67.4 | 67.1 | 69.8 | 68.7 | 53.3 | 8.99 | 0.0111 |
| Race (%) | |||||||
| Asian | 1.8 | 1.6 | 0.9 | 1.9 | 2.2 | N/A | 0.0650 |
| Black or African American | 1.7 | 1.6 | 0.9 | 2.1 | 1.1 | ||
| Hawaiian or Pacific Islander | 0.1 | 0.1 | 0.0 | 0.2 | 0.0 | ||
| White | 81.6 | 80.6 | 76.2 | 81.7 | 86.7 | ||
| Other | 3.7 | 4.0 | 6.8 | 2.8 | 2.2 | ||
| Prefer no answer | 2.2 | 2.4 | 4.7 | 1.4 | 1.1 | ||
| Multiplec | 8.9 | 9.8 | 10.6 | 10.0 | 6.7 | ||
| Hispanic/Latino (%) | 6.7 | 6.6 | 8.1 | 6.0 | 5.6 | N/A | 0.677 |
| Lives in US (%) | 75.9 | 74.9 | 74.5 | 74.2 | 78.9 | 1.45 | 0.485 |
| Max education (%) | |||||||
| Less than high school | 1.0 | 1.1 | 2.1 | 0.5 | 1.1 | 12.3 |
0.139 |
| High school graduate or GED | 26.1 | 26.8 | 27.0 | 28.1 | 20.0 | ||
| College degree | 41.0 | 41.3 | 39.9 | 42.2 | 41.1 | ||
| Master’s degree | 23.1 | 22.8 | 21.5 | 23.2 | 24.4 | ||
| Doctorate/terminal degree |
8.9 |
8.1 |
9.4 |
6.0 |
13.3 |
||
| Occupation (%) | |||||||
| Business, financial, management, sales | 14.2 | 14.2 | 15.0 | 15.1 | 7.8 | 31.0 | 0.0556 |
| Computer, engineering, math | 16.9 | 17.1 | 16.7 | 15.5 | 25.6 | ||
| Life, physical, and social science | 9.2 | 8.2 | 6.8 | 7.2 | 15.6 | ||
| Legal | 2.5 | 2.6 | 0.9 | 3.5 | 3.3 | ||
| Education, training, library | 14.3 | 13.6 | 13.2 | 15.3 | 6.7 | ||
| Arts, design, entertainment, sports, media | 4.7 | 4.6 | 3.4 | 5.1 | 5.6 | ||
| Healthcare practitioner | 8.9 | 8.9 | 10.3 | 7.7 | 11.1 | ||
| Office, administrative support | 7.7 | 7.5 | 6.4 | 8.8 | 4.4 | ||
| Construction, maintenance, natural resources | 1.9 | 1.9 | 2.6 | 1.6 | 1.1 | ||
| Production and transportation | 1.5 | 1.7 | 2.1 | 1.6 | 1.1 | ||
| Other | 18.2 | 19.7 | 22.6 | 18.6 | 17.8 | ||
| Works in genetic research/medicine (%) | 5.1 | 3.8 | 3.0 | 2.3 | 13.3 | 24.8 | 4.11e−06 |
| Participant in genetic research (%) | 14.9 | 16.2 | 11.5 | 19.0 | 15.6 | 7.68 | 0.0215 |
Survey respondent characteristics, overall and grouped by type(s) of tools used. For categorical variables, values are given as within-group percentage, excluding NA/missing values from the denominator. Statistical tests of difference are reported for comparison between groups of tool users: users of non-health only tools, crossover users (used both health and non-health tools), and users of health-only tools. SD indicates standard deviation.
Comparing three groups of tool users: non-health only tool users, crossover tool users, and health-only tool users. For categorical values where all cell counts >5, the test statistic and p value are from a chi-square test. For categorical values with low cell counts (i.e., race and Hispanic/Latino), the p value is from a Fisher exact test, and the test statistic is N/A. ANOVA was used to compare continuous variables; the test statistic given is the F value.
Of the 820 respondents who used at least one tool, one respondent reported using only “various R packages” and could therefore not be assigned a tool user group (non-health only; crossover; health only).
Respondents who checked more than one box for self-identified race are counted under “Multiple.” Note all American Indian/Alaska Native respondents checked more than one box and are therefore all counted under “Multiple” here.