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 | |||||
|
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5 | 49 | 8 (6-9) | 29 (58) | 0.70 | .47 | |||||
|
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Intercept | — | — | — | 1.52 | .22 | |||||
| Model D: I feel discomfort during self-sampling | |||||||||||
|
|
1 | 57 | 3 (2-5) | 33 (58) | 1 | — | |||||
|
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2 | 101 | 3 (2-6) | 69 (68) | 1.95 | .10 | |||||
|
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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.