Research Article

Engagement in HIV Medical Care and Technology Use among Stimulant-Using and Nonstimulant-Using Men who have Sex with Men

Table 3

Estimated effect of recent (past 30 days) stimulant use on engagement in HIV care in past year.

Ref. no missed appointmentsModel 1aModel 2bModel 3c
RRRd (95% CIe),
value
RRR (95% CI),
value
RRR (95% CI),
value

Missed appointment(s)
 Stimulant use1.84 (0.87, 3.87),
1.99 (0.91, 4.37),
1.73 (0.72, 4.16),
 Agef0.98 (0.94, 1.01),
0.97 (0.94, 1.01),
 Nonwhite race/ethnicity1.56 (0.82, 2.96),
1.68 (0.85, 3.32),
 Education
  High school or lessRef.Ref.
  Technical school/some college0.45 (0.19, 1.08),
0.51 (0.20, 1.28),
  College degree0.20 (0.08, 0.52),
0.21 (0.08, 0.58),
 Depression1.04 (0.48, 2.27),
 Life chaos1.17 (1.09, 1.26),

Not in HIV medical care
 Stimulant use2.84 (1.07, 7.58),
3.16 (1.13, 8.84),
3.44 (1.17, 10.15),
 Age0.97 (0.92, 1.01),
0.97 (0.92, 1.01),
 Nonwhite race/ethnicity2.33 (0.95, 5.70),
2.58 (1.04, 6.40),
 Education
  High school or lessRef.Ref.
  Technical/some college0.64 (0.17, 2.31),
0.73 (0.20, 2.73),
  College degree0.22 (0.05, 0.94),
0.22 (0.05, 0.98),
 Depressiong0.54 (0.19, 1.52),
 Life chaosh1.11 (0.99, 1.23),

Notes: aunadjusted model; bModel 1 plus demographic variables significantly associated with treatment engagement in the bivariate analyses; cModel 2 plus psychosocial variables significantly associated with treatment engagement in the bivariate analyses, 5 missing cases; drelative risk ratio; econfidence interval; fvariable not included in model; gusing the 10-item CES-D scale [30]; husing the life chaos scale [32].