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Table 1 Logistic regression analyses of TB treatment assistance preferences and TB stigmatizing ideas, HIV/AIDS stigmatizing ideas and the view that TB patients should be queued with other chronically ill patients.

From: The relationship between (stigmatizing) views and lay public preferences regarding tuberculosis treatment in the Eastern Cape, South Africa

 

Assigning a DOTS volunteer to support them while on treatment

Providing porridge so TB patients do not take their medicine on an empty stomach

Assigning special queues or a special room at clinics

Giving TB patients a temporary disability grant so they can be financially independent while on treatment

Contacting people at work or school to inform them that the patient is not infectious because he/she is on treatment

 

Adjusted OR

Adjusted OR

Adjusted OR

Adjusted OR

Adjusted OR

TB stigma

1.230 (1.084-1.449)

1.075 (0.933-1.225)

1.169 (1.000-1.354)

0.708 (0.600-0.826)

0.852 (0.671-1.009)

HIV/AIDS Stigma

1.122 (0.992-1.316)

0.975 (0.828-1.104)

0.960 (0.838-1.120)

0.982 (0.831-1.109)

0.937 (0.786-1.132)

TB patients queued with chronically ill

0.756 (0.583-0.974)

1.442 (1.094-1.879)

0.873 (0.660-1.177)

1.667 (1.283-2.083)

0.710 (0.517-0.971)

Constant

0.950

1.161

0.364

0.508

0.415

Model χ2

x 2 = 22.443

x 2 = 8.062

x2 = 5.295

x 2 = 42.181

x 2 = 8.475

-2 log likelihood

1381,757

1308.976

1126.231

1361.622

984.000

Nagelkerke R2

0.029

0.011

0.008

0.054

0.013

  1. Notes: Figures in bold are statistically significant at p < 0.05.
  2. Not stigmatizing ideas = 0; stigmatizing ideas = 1.
  3. It does not help to put TB patients in a queue with other chronically ill patients = 0; it does help to put TB patients in a queue with other chronically ill patients = 1.
  4. The tables stating the logistic regression models also adjust for gender and education.