Table 4.

Factor loadings.

Itema	EFAb 1-factor solution	EFA 2-factor solution		CFAc factor 1 from 2-factor solutiond
	Factor 1	Factor 1	Factor 2	Factor 1 (willingness for digital tracking)
Installing an app on your phone that asks you questions about your own symptoms and provides recommendations about COVID-19	0.893 (0.009)e	1.025 (0.032)e	–0.131 (0.041)	1.000 (0)e
Installing an app on your phone that tracks your location and sends push notifications if you might have been exposed to COVID-19	0.859 (0.010)e	0.869 (0.011)e	0.011 (0.005)	0.956 (0.011)e
Using a website to log your symptoms and location and get recommendations about COVID-19	0.852 (0.010)e	0.827 (0.029)e	0.065 (0.035)	0.962 (0.009)e
Testing you for COVID-19 infection using a Q-tip to swab your cheek or nose	0.861 (0.012)e	0.098 (0.108)	0.831 (0.110)e	N/Af
Testing you for immunity or resistance to COVID-19 by drawing a small amount of blood	0.849 (0.012)e	–0.007 (0.005)	0.919 (0.032)e	N/A

^aFor each item, the question was, “There are some options for testing and tracking people who may have COVID-19 in order to help slow the spread of this virus. If these options were available to you, how likely would you be to participate in them?” Response options were as follows: “1. Extremely likely,” “2. Very likely,” “3. Moderately likely,” “4. Not too likely,” “5. Not likely at all,” and “88. Already done this.” As the focus of this study was on willingness, or likelihood, response option 88 was not included in psychometric analyses. Only 8 (0.37%) participants responded with option 88. Possible scores for each item ranged from 1 to 5 and were reverse-coded so that higher scores indicated greater willingness. Unstandardized factor loadings are presented.

^bEFA: exploratory factor analysis.

^cCFA: confirmatory factor analysis.

^dFactor 1 was fully saturated, as it was a latent variable with 3 indicators. Because it was fully saturated, it had perfect model fit. Factor 2 only had 2 items. As such, factor 2 was underidentified and could not be fit to the data as a separate measurement model.

^eFactor loadings load strongly onto the underlying factor.

^fN/A: not applicable.