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. Author manuscript; available in PMC: 2014 Jan 1.
Published in final edited form as: AIDS Behav. 2013 Jan;17(1):260–265. doi: 10.1007/s10461-011-0132-7

Brief report: No association found between traditional healers use and delayed antiretroviral initiation in rural Uganda

Russell H Horwitz 1,2, Alexander C Tsai 3, Samuel Maling 4, Francis Bajunirwe 5,6, Jessica E Haberer 7,8, Nneka Emenyonu 9,10, Conrad Muzoora 9, Peter W Hunt 10,11, Jeff N Martin 12, David R Bangsberg 2,7,8,9,13
PMCID: PMC3718889  NIHMSID: NIHMS432108  PMID: 22246516

Abstract

Traditional healer and/or spiritual counselor (TH/SC) use has been associated with delays in HIV testing. We examined HIV-infected individuals in southwestern Uganda to test the hypothesis that TH/SC use was also associated with lower CD4-counts at antiretroviral therapy (ART) initiation. Nearly 500 individuals initiating ART through an HIV/AIDS clinic at the Mbarara University of Science and Technology (MUST) were recruited to participate. Patients were predominantly female, ranged in age from 18 to 75, and had a median CD4 count of 130. TH/SC use was not associated with lower CD4 cell count, but age and quality-of-life physical health summary score were associated with CD4 cell count at initiation while asset index was negatively associated with CD4 count at ART initiation. These findings suggest that TH/SC use does not delay initiation of ART.

Keywords: HIV/AIDS, traditional healer, spiritual counselor, late presentation, Uganda

INTRODUCTION

Late presentation for antiretroviral therapy (ART) contributes to disease progression, mortality, and HIV transmission,(1) and has posed a particular threat to the population in sub-Saharan Africa.(2, 3) Traditional healers and/or spiritual counselors (TH/SC) are often the first point of contact for the health care needs of the sub-Saharan African underserved community;(4) they hold a familiar belief system, have ancestral roots in the community, and maintain an in-depth understanding of the culture.(5) Estimates indicate up to 70% of the population in sub-Saharan Africa receive care from TH/SC,(6, 7) who have been implicated in patient health care-seeking delays.(810) Prior research examined factors associated with delays in HIV testing,(1115) and TH/SC use was found to be associated with late HIV diagnosis.(1618) Coordination and collaboration with these highly respected and trusted members of the community could potentially facilitate HIV testing and treatment of individuals from these hard-to-reach communities.

While most studies indicate that high-risk behavior (or a higher perceived risk) is protective against late HIV testing,(1) predictors of late initiation of ART may be more complicated.(19, 20) Little is known about whether TH/SC use is associated with the timely initiation of ART. We examined TH/SC use among patients initiating ART in rural southwestern Uganda and hypothesized TH/SC exposure would be associated with delayed ART initiation, measured by lower CD4 at ART initiation.

METHODS

Study Population

Patients beginning ART at the Mbarara University of Science and Technology (MUST) Immune Suppression Syndrome (ISS) Clinic in southwestern Uganda were invited to participate in this study. The ISS Clinic has over 18,000 registered HIV-infected patients, of whom approximately 7,000 individuals receive ART.(21) For this analysis we used baseline data, measured prior to ART initiation, from a cohort of almost 500 patients participating in the Uganda AIDS Rural Treatment Outcomes (UARTO) study, a prospective study of ART-naive patients initiating no-cost ART. Data were analyzed from June, 2005 until August, 2009.

Measures

Traditional healer/herbalist (TH) and/or spiritual counselor (SC) use at the time of ART initiation was determined by the question, “In the past 3 months, did you visit or were you visited by:” “Spiritual Counselor,” “Traditional Healer or Herbalist?” Demographic characteristics collected included age, sex, marital status, educational background, household asset wealth, alcohol consumption, and distance from clinic in self-reported travel time. The Medical Outcomes Study HIV Health Survey (MOS-HIV)(2224) is a 35-item instrument used to measure health-related quality of life (HRQoL). Composite Mental Health Summary (MHS) and Physical Health Summary (PHS) scores were calculated from the MOS-HIV scale scores that measured physical functioning, role functioning, social functioning, cognitive functioning, mental health, health distress, energy/fatigue, pain, quality of life, and general health perception.(25) The MOS-HIV has been used previously in research with people living with HIV/AIDS in Uganda and has been shown to be a reliable and valid instrument.(2628) Depression severity was measured using a modified Hopkins Symptoms Checklist for Depression (HSCL-D).(2933) Household wealth was measured using an asset index derived from a principal components analysis of three groups of asset indicators: consumer goods owned by participant, characteristics of participant living quarters, and participant landownership.(34) The asset index at ART initiation was converted into an ordinal variable of increasing quintiles, and a dichotomous variable was created based on univariable regression analysis results that distinguished the top two from the bottom three quintiles. All information was collected by trained interviewers using structured questionnaire translated and back translated in the local language of Runyankole.

Statistical Analyses

The primary analysis examined the association between CD-4 count and TH/SC use at ART initiation using ordinary least squared (OLS) regression and controlling for potential confounders. Variables found to be associated at p < 0.25 with the outcome (CD-4 count) on univariable regression were retained for the multivariable model.(35)

Ethical Considerations

The study was approved by the Partners Human Research Committee at Massachusetts General Hospital; the Institutional Ethical Review Committee, Mbarara University; and the Uganda National Council of Science and Technology.

RESULTS

Participants included 457 HIV-infected individuals interviewed at ART initiation, of whom 317 (69%) were female, one quarter had a secondary-level education or higher, and close to half (44%) were married. Ages ranged from 18 to 75 years with a median age of 34 years, interquartile range (IQR) = 29–39. Over 40% of the population took an hour or more to travel from their home to the clinic. Participants at ART initiation had a median CD4 count of 130, IQR = 70 – 195. (Table I)

Table I.

Participant Demographics (N = 457)

Characteristics Median (IQR) or n (%)
Sex
  Male 140 (30.6%)
Age 34 (29–39)
Education
  No Education 79 (17.3%)
  Primary 265 (58.0%)
  Secondary and above 113 (24.7%)
Marital Status
  Never Married 34 (7.4%)
  Married 197 (43.1%)
  Divorced 117 (25.6%)
  Widowed 106 (23.2%)
CD4 Count 130 (70–195)
AUDIT-C
  Problem-Drinking 110 (24.1%)
Asset Index
  0–20% Quintile 90 (19.7%)
  20–40% Quintile 93 (20.4%)
  40–60% Quintile 88 (19.3%)
  60– 80% Quintile 93 (20.4%)
  80–100% Quintile 88 (19.3%)
MOS HIV
  Physical Health Summary 53.1 (43.4–58.2)
  Mental Health Summary 50.4 (45.0–57.2)
Depression Score (DSHSCL score) 1.73 (1.31–2.00)
Distance to clinic (in minutes) 40 (30–60)
TH/SC exposure 78 (17.1%)

At baseline, 30 participants (7%) had visited a traditional healer or herbalist (TH) and 51 participants (11%) had visited a spiritual counselor (SC) during the three months prior to ART initiation; a total of 78 participants (17%) visited a traditional healer/herbalist and/or a spiritual counselor (TH/SC) during the three months prior to ART initiation, and only three participants (0.6%) reported visiting both.

Univariable linear regression found no association between CD4 cell count and TH/SC use during the three months prior to ART initiation. Both age (p = 0.037) and MOS-HIV physical health summary (PHS) score (p = 0.007) were directly associated with CD4-count at ART initiation. (Table II) Having a secondary or above level of education and having an asset index in the highest two quintiles were inversely proportional to CD4-count; while these relationships were not statistically significant (p < 0.25), they were included in the multivariable regression model.

Table II.

Adjusted and unadjusted linear regression coefficients (Standard Error) on CD4-count

TH Exposure
Variable Unadjusted Coefficient (SE) Adjusted Standardized Beta
Age 1.21 (0.58)* 0.107*
Sex (ref: Female)
  Male −9.41 (10.48)
Educational level (ref: no education)
  Primary −10.46 (13.25)
  Secondary and above −18.11 (15.16) −0.011
Marital status (ref: never married)
  Married 18.23 (19.19)
  Widowed 17.12 (20.37)
  Divorced 10.55 (20.13)
AUDIT-C (ref: Men < 4, Women < 3)
  Men > 3, Women > 2 −9.54 (11.32)
Asset Index (ref: 0 – 20% Quintile)§
  20–40% −7.79 (15.18)
  40–60% 2.17 (15.39)
  60–80% −23.47 (15.18)
  80–100% −23.28 (15.39) −0.099*
Travel time to clinic (in minutes) 0.08 (0.11)
TH/SC (ref: No visit in past three months)
  Visit with TH/SC in past three months 14.08 (12.84) 0.066
MOS-HIV
  Mental Health 0.38 (0.51)
  Physical Health 1.14 (0.42)** 0.155***
Depression −8.76 (8.83)
N 431
R2 0.045

Multivariable linear regression at ART initiation

Factors associated with the outcome at p < 0.25 and included as covariates in multivariable regression analysis

§

Dichotomous variable was created for multivariable linear regression dividing first three and highest two quintiles

*

p < 0.05;

**

p < 0.01;

***

p < 0.005

Multivariable regression did not show a significant relationship between CD-4 count and TH/SC use after adjusting for covariates. CD-4 count did show a significant direct relationship with PHS (p = 0.001) and with age (p = 0.024), as well as a significant inversely proportional relationship with having an asset index in the top two quintiles (0.047).

DISCUSSION

We found that visiting a TH/SC during the three-month period prior to ART initiation was not associated with CD4 count at ART initiation, suggesting that TH/SC exposure is not associated with late presentation for ART initiation. A recent review article on delays in tuberculosis (TB) care in sub-Saharan Africa by Finnie and colleagues found that consulting traditional healers was the only factor which consistently led to delays in both diagnosis and care seeking. (36) Studies in sub-Saharan African have also documented delays in seeking treatment for malaria,(37) breast cancer,(38) and first-episode psychosis,(39) which were also attributed to traditional healers. Much like HIV infection, initial symptoms may not be readily identified, and health-seeking behaviors for these illnesses may be quite similar. An HIV diagnosis, however, may heighten concerns and lead to more prompt treatment, a response that may differ for other ailments.

Older age was also associated with earlier ART initiation in univariable and multivariable linear regression, while being in the top two quintiles of a composite asset index score was inversely proportional to CD4 count. In contrast to Girardi and colleagues, who found that older age correlated with late HIV diagnosis but did not correlate with late presentation for treatment,(19) our study found older age to be protective against late ART presentation. Higher asset index correlated with late presentation, and this delay may reflect participants in high social economic strata concerned about local stigma and delaying to seek treatment in distant regions. Lower PHS, a marker of lower physical functional status was associated with lower CD4, consistent with more advanced HIV disease.

There are several limitations to our analysis. We examined TH/SC use during the three-month period prior to ART initiation without temporal or quantitative assessment. More distant TH/SC use was not assessed and no distinction between participants who met with a TH/SC frequently versus those who had visited only once during this period could be made. Future studies will need to obtain more detailed information regarding TH/SC exposure, including visit frequency and duration, motivations for seeking care, and treatments received. Rates of TH/SC exposure were low, which limits our ability to detect an association, and which may reflect a selection bias where individuals who visit TH/SC do not survive or do not choose to be treated at biomedical institutions. Finally, our parameter estimates have an associational, not causal, interpretation. Further longitudinal studies are needed to explain this relationship.

CONCLUSION

In summary, our study indicated that visiting a TH/SC prior to ART initiation is not associated with delayed ART initiation while higher asset index did have a paradoxical association with delayed ART initiation. These findings suggest that exposure to TH/SC are not a barrier to ART use. Future studies and interventions are needed to see how TH/SC may be leveraged to improve early presentation for treatment and care.

Acknowledgments

We would like to acknowledge Dr. Paul Bolton of Boston University for generously providing the locally validated version of the Hopkins Symptom Check list. This study received funding by the National Institutes of Health (RO1MH54907; K24MH87227; P30AI027763; UL1RR024131).

References

  • 1.Girardi E, Sabin CA, Monforte AD. Late diagnosis of HIV infection: epidemiological features, consequences and strategies to encourage earlier testing. J Acquir Immune Defic Syndr. 2007 Sep;46(Suppl 1):S3–8. doi: 10.1097/01.qai.0000286597.57066.2b. [DOI] [PubMed] [Google Scholar]
  • 2.Brinkhof MW, Boulle A, Weigel R, Messou E, Mathers C, Orrell C, et al. Mortality of HIV-infected patients starting antiretroviral therapy in sub-Saharan Africa: comparison with HIV-unrelated mortality. PLoS Med. 2009 Apr 28;6(4):e1000066. doi: 10.1371/journal.pmed.1000066. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.May M, Boulle A, Phiri S, Messou E, Myer L, Wood R, et al. Prognosis of patients with HIV-1 infection starting antiretroviral therapy in sub-Saharan Africa: a collaborative analysis of scale-up programmes. Lancet. 2010 Aug 7;376(9739):449–57. doi: 10.1016/S0140-6736(10)60666-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Puckree T, Mkhize M, Mgobhozi Z, Lin J. African traditional healers: what health care professionals need to know. Int J Rehabil Res. 2002 Dec;25(4):247–51. doi: 10.1097/00004356-200212000-00001. [DOI] [PubMed] [Google Scholar]
  • 5.Homsy J, King R, Balaba D, Kabatesi D. Traditional health practitioners are key to scaling up comprehensive care for HIV/AIDS in sub-Saharan Africa. AIDS. 2004 Aug 20;18(12):172, 3–5. doi: 10.1097/01.aids.0000131380.30479.16. [DOI] [PubMed] [Google Scholar]
  • 6.Mills E, Singh S, Wilson K, Peters E, Onia R, Kanfer I. The challenges of involving traditional healers in HIV/AIDS care. Int J STD AIDS. 2006 Jun;17(6):360–3. doi: 10.1258/095646206777323382. [DOI] [PubMed] [Google Scholar]
  • 7.Traditional medicine – growing needs and potential: WHO Policy Perspectives on Medicines. Geneva, Switzerland: World Health Organization; 2002. May 2, [Google Scholar]
  • 8.Malik IA, Gopalan S. Use of CAM results in delay in seeking medical advice for breast cancer. Eur J Epidemiol. 2003;18(8):817–22. doi: 10.1023/a:1025343720564. [DOI] [PubMed] [Google Scholar]
  • 9.Yimer S, Bjune G, Alene G. Diagnostic and treatment delay among pulmonary tuberculosis patients in Ethiopia: a cross sectional study. BMC Infect Dis. 2005;5:112. doi: 10.1186/1471-2334-5-112. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Storla DG, Yimer S, Bjune GA. A systematic review of delay in the diagnosis and treatment of tuberculosis. BMC Public Health. 2008;8:15. doi: 10.1186/1471-2458-8-15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Kigozi IM, Dobkin LM, Martin JN, Geng EH, Muyindike W, Emenyonu NI, et al. Late-disease stage at presentation to an HIV clinic in the era of free antiretroviral therapy in Sub-Saharan Africa. J Acquir Immune Defic Syndr. 2009 Oct 1;52(2):280–9. doi: 10.1097/QAI.0b013e3181ab6eab. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Begovac J, Gedike K, Lukas D, Lepej SZ. Late presentation to care for HIV infection in Croatia and the effect of interventions during the Croatian Global Fund Project. AIDS Behav. 2008 Jul;12(4 Suppl):S48–53. doi: 10.1007/s10461-008-9398-9. [DOI] [PubMed] [Google Scholar]
  • 13.de Olalla PG, Mazardo C, Sambeat MA, Ocana I, Knobel H, Humet V, et al. Epidemiological characteristics and predictors of late presentation of HIV infection in Barcelona (Spain) during the period 2001–2009. AIDS Res Ther. 2011;8(1):22. doi: 10.1186/1742-6405-8-22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Bonjour MA, Montagne M, Zambrano M, Molina G, Lippuner C, Wadskier FG, et al. Determinants of late disease-stage presentation at diagnosis of HIV infection in Venezuela: a case-case comparison. AIDS Res Ther. 2008;5:6. doi: 10.1186/1742-6405-5-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Lo YC, Wu PY, Hsieh CY, Chen MY, Sheng WH, Hsieh SM, et al. Late diagnosis of human immunodeficiency virus infection in the era of highly active antiretroviral therapy: role of socio-behavioral factors and medical encounters. J Formos Med Assoc. 2011 May;110(5):306–15. doi: 10.1016/S0929-6646(11)60046-6. [DOI] [PubMed] [Google Scholar]
  • 16.Okome-Nkoumou M, Okome-Miame F, Kendjo E, Obiang GP, Kouna P, Essola-Biba O, et al. Delay between first HIV-related symptoms and diagnosis of HIV infection in patients attending the internal medicine department of the Fondation Jeanne Ebori (FJE), Libreville, Gabon. HIV Clin Trials. 2005 Jan-Feb;6(1):38–42. doi: 10.1310/ULR3-VN8N-KKB5-05UV. [DOI] [PubMed] [Google Scholar]
  • 17.Wanyenze RK, Kamya MR, Fatch R, Mayanja-Kizza H, Baveewo S, Sawires S, et al. Missed opportunities for HIV testing and late-stage diagnosis among HIV-infected patients in Uganda. PLoS One. 2011;6(7):e21794. doi: 10.1371/journal.pone.0021794. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Louis C, Ivers LC, Smith Fawzi MC, Freedberg KA, Castro A. Late presentation for HIV care in central Haiti: factors limiting access to care. AIDS Care. 2007 Apr;19(4):487–91. doi: 10.1080/09540120701203246. [DOI] [PubMed] [Google Scholar]
  • 19.Girardi E, Aloisi MS, Arici C, Pezzotti P, Serraino D, Balzano R, et al. Delayed presentation and late testing for HIV: demographic and behavioral risk factors in a multicenter study in Italy. J Acquir Immune Defic Syndr. 2004 Aug 1;36(4):951–9. doi: 10.1097/00126334-200408010-00009. [DOI] [PubMed] [Google Scholar]
  • 20.Samet JH, Freedberg KA, Stein MD, Lewis R, Savetsky J, Sullivan L, et al. Trillion virion delay: time from testing positive for HIV to presentation for primary care. Arch Intern Med. 1998 Apr 13;158(7):734–40. doi: 10.1001/archinte.158.7.734. [DOI] [PubMed] [Google Scholar]
  • 21.Geng EH, Bwana MB, Kabakyenga J, Muyindike W, Emenyonu NI, Musinguzi N, et al. Diminishing availability of publicly funded slots for antiretroviral initiation among HIV-infected ART-eligible patients in Uganda. PLoS One. 2010;5(11):e14098. doi: 10.1371/journal.pone.0014098. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Wu AW, Revicki DA, Jacobson D, Malitz FE. Evidence for reliability, validity and usefulness of the Medical Outcomes Study HIV Health Survey (MOS-HIV) Qual Life Res. 1997 Aug;6(6):481–93. doi: 10.1023/a:1018451930750. [DOI] [PubMed] [Google Scholar]
  • 23.Wu AW, Rubin HR, Mathews WC, Ware JE, Jr, Brysk LT, Hardy WD, et al. A health status questionnaire using 30 items from the Medical Outcomes Study. Preliminary validation in persons with early HIV infection. Med Care. 1991 Aug;29(8):786–98. doi: 10.1097/00005650-199108000-00011. [DOI] [PubMed] [Google Scholar]
  • 24.Ware JE, Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care. 1992 Jun;30(6):473–83. [PubMed] [Google Scholar]
  • 25.Revicki DA, Sorensen S, Wu AW. Reliability and validity of physical and mental health summary scores from the Medical Outcomes Study HIV Health Survey. Med Care. 1998 Feb;36(2):126–37. doi: 10.1097/00005650-199802000-00003. [DOI] [PubMed] [Google Scholar]
  • 26.Mast TC, Kigozi G, Wabwire-Mangen F, Black R, Sewankambo N, Serwadda D, et al. Measuring quality of life among HIV-infected women using a culturally adapted questionnaire in Rakai district, Uganda. AIDS Care. 2004 Jan;16(1):81–94. doi: 10.1080/09540120310001633994. [DOI] [PubMed] [Google Scholar]
  • 27.Stangl AL, Wamai N, Mermin J, Awor AC, Bunnell RE. Trends and predictors of quality of life among HIV-infected adults taking highly active antiretroviral therapy in rural Uganda. AIDS Care. 2007 May;19(5):626–36. doi: 10.1080/09540120701203915. [DOI] [PubMed] [Google Scholar]
  • 28.Bajunirwe F, Tisch DJ, King CH, Arts EJ, Debanne SM, Sethi AK. Quality of life and social support among patients receiving antiretroviral therapy in Western Uganda. AIDS Care. 2009 Mar;21(3):271–9. doi: 10.1080/09540120802241863. [DOI] [PubMed] [Google Scholar]
  • 29.Mollica RF, Wyshak G, de Marneffe D, Khuon F, Lavelle J. Indochinese versions of the Hopkins Symptom Checklist-25: a screening instrument for the psychiatric care of refugees. Am J Psychiatry. 1987 Apr;144(4):497–500. doi: 10.1176/ajp.144.4.497. [DOI] [PubMed] [Google Scholar]
  • 30.McKelvey RS, Mao AR, Webb JA. Premigratory expectations and mental health symptomatology in a group of Vietnamese Amerasian youth. J Am Acad Child Adolesc Psychiatry. 1993 Mar;32(2):414–8. doi: 10.1097/00004583-199303000-00024. [DOI] [PubMed] [Google Scholar]
  • 31.McKelvey RS, Webb JA, Mao AR. Premigratory risk factors in Vietnamese Amerasians. Am J Psychiatry. 1993 Mar;150(3):470–3. doi: 10.1176/ajp.150.3.470. [DOI] [PubMed] [Google Scholar]
  • 32.Mouanoutoua VL, Brown LG. Hopkins Symptom Checklist-25, Hmong version: a screening instrument for psychological distress. J Pers Assess. 1995 Apr;64(2):376–83. doi: 10.1207/s15327752jpa6402_16. [DOI] [PubMed] [Google Scholar]
  • 33.Kaaya SF, Fawzi MC, Mbwambo JK, Lee B, Msamanga GI, Fawzi W. Validity of the Hopkins Symptom Checklist-25 amongst HIV-positive pregnant women in Tanzania. Acta Psychiatr Scand. 2002 Jul;106(1):9–19. doi: 10.1034/j.1600-0447.2002.01205.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Fillmore KM. Research as a handmaiden of policy: an appraisal of estimates of alcoholism and its cost in the workplace. J Public Health Policy. 1984;5(1):40–64. [PubMed] [Google Scholar]
  • 35.Hosmer DW, Lemeshow S. Applied Logistic Regression. 2. New York City, NY: John Wiley & Sons, Inc; 2000. [Google Scholar]
  • 36.Finnie RK, Khoza LB, van den Borne B, Mabunda T, Abotchie P, Mullen PD. Factors associated with patient and health care system delay in diagnosis and treatment for TB in sub-Saharan African countries with high burdens of TB and HIV. Trop Med Int Health. 2011 Apr;16(4):394–411. doi: 10.1111/j.1365-3156.2010.02718.x. [DOI] [PubMed] [Google Scholar]
  • 37.Warsame M, Kimbute O, Machinda Z, Ruddy P, Melkisedick M, Peto T, et al. Recognition, perceptions and treatment practices for severe malaria in rural Tanzania: implications for accessing rectal artesunate as a pre-referral. PLoS One. 2007;2(1):e149. doi: 10.1371/journal.pone.0000149. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Dye TD, Bogale S, Hobden C, Tilahun Y, Hechter V, Deressa T, et al. Complex care systems in developing countries: breast cancer patient navigation in Ethiopia. Cancer. 2010 Feb 1;116(3):577–85. doi: 10.1002/cncr.24776. [DOI] [PubMed] [Google Scholar]
  • 39.Burns JK, Jhazbhay K, Emsley RA. Causal attributions, pathway to care and clinical features of first-episode psychosis: a South African perspective. Int J Soc Psychiatry. 2011 Sep;57(5):538–45. doi: 10.1177/0020764010390199. [DOI] [PubMed] [Google Scholar]

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