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. 2022 Nov 18;6(11):e40996. doi: 10.2196/40996

Table 5.

Post-self-sampling scores (ranging between 1 [strongly disagree] and 10 [strongly agree]) and their changes across visits in binary logistic generalized estimating equation (GEE) models.

Model and visit number Participants, n Median (IQR) High scorea, n (%) GEE model results




Exp(B) P value
Model A: It's convenient

1 60 8 (5-9) 31 (52) 1  —b

2 105 8 (4-10) 57 (54) 1.03 .91

3 97 8 (5-9) 52 (54) 0.93 .81

4 75 8 (6-10) 45 (60) 1.11 .75

5 51 8 (5-9) 31 (61) 1.45 .28

Intercept 1.19 .48
Model B: I am confident to self-sample correctly

1 62 7 (4-9) 23 (37) 1

2 106 8 (5-9) 55 (52) 1.33 .34

3 97 7 (5-9) 46 (47) 1.05 .87

4 76 8 (5-10) 42 (55) 1.46 .24

5 50 8 (5-9) 26 (52) 1.71 .11

Intercept 0.77 .30
Model C: I am confident that self-sampled specimens can accurately reflect my HIV or STI status

1 61 7 (5-9) 30 (49) 1

2 108 8 (5-9) 61 (58) 0.81 .61

3 96 7 (5-9) 47 (49) 0.67 .29

4 76 8 (5-10) 42 (55) 0.78 .51

5 49 8 (6-9) 29 (58) 0.70 .47

Intercept 1.52 .22
Model D: I feel discomfort during self-sampling

1 57 3 (2-5) 33 (58) 1

2 101 3 (2-6) 69 (68) 1.95 .10

3 93 3 (2-6) 57 (61) 1.42 .38

4 75 3 (2-5) 39 (52) 1.11 .81

5 49 4 (2-7) 32 (65) 0.93 .82

Intercept 1.08 .82

aThe high score was coded 1 as a binary dependent variable in the GEE models: scores ≥8 for models A, B, and C and ≥3 for model D.

bNot applicable.