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Table 3 Adjusted risk ratios of substance use treatment enrollment outcomes vs. successfully enrolling: RAPiDS (n = 200)

From: Access to substance use treatment among young adults who use prescription opioids non-medically

 

Never attempted to enroll (n = 91)

Unsuccessfully attempted to enroll (n = 39)

Adjusted risk ratio

95% Confidence Interval (CI)

p - value

Adjusted risk ratio

95% Confidence Interval (CI)

p - value

Ethnicity

 Hispanic or Latino descent

0.30

(0.10, 0.95)

0.040

0.12

(0.01, 1.07)

0.058

 Non-Hispanic

1.00

(Ref)

 

1.00

(Ref)

 

Race

 White

1.00

(Ref)

 

1.00

(Ref)

 

 Non-white

3.16

(1.28, 7.83)

0.013

1.39

(0.44, 4.43)

0.578

Monthly income

  < $501

1.00

(Ref)

 

1.00

(Ref)

 

 $501 - $1500

3.93

(1.53, 10.12)

0.005

5.36

(1.79, 16.03)

0.003

  > $1500

2.16

(0.90, 5.80)

0.128

2.32

(0.74, 7.31)

0.151

Ever overdosed by accident

 Yes

0.50

(0.19, 1.34)

0.169

2.71

(1.06, 6.91)

0.037

 No

1.00

(Ref)

 

1.00

(Ref)

 

Drug-related discrimination by medical community

 Yes

0.25

(0.10, 0.62)

0.003

1.33

(0.55, 3.27)

0.527

 No

1.00

(Ref)

 

1.00

(Ref)

 

Ever incarcerated in jail or prison

 Yes

0.31

(0.14, 0.66)

0.003

0.99

(0.40, 2.41)

0.977

 No

1.00

(Ref)

 

1.00

(Ref)

 
  1. Notes Model adjusted for recruitment source
  2. The log likelihood of the model before stepwise removal is −151.39
  3. The log likelihood of the model after stepwise removal is −157.95
  4. The Nagelkerke R-squared of the model before stepwise removal is 0.478
  5. The Nagelkerke R-squared of the model after stepwise removal is 0.432
  6. The mean variance inflation factor for the model before stepwise removal is 1.33
  7. The mean variance inflation factor for the model after stepwise removal is 1.15
  8. The final model uses multinomial logistic regression and has 16 degrees of freedom