By Dr. Felix Kauye, Prof. Rachel Jenkins, Prof. Atif Rahman

1. Primary Health Workers’ TRAINING in Mental Health and Its Impact on diagnoses of common mental disorders and related physical illnesses in malawi By Dr. Felix Kauye, Prof. Rachel Jenkins, Prof. Atif Rahman

2. Mental Health in Primary care • Mental health problems are common in primary care • WHO PPGHC study in 15 countries found an average point prevalence of 24% • Average prevalence of depression alone was 14% • Other studies have found rates up to 40% but 50% are missed • Presentation of physical symptoms is one of the contributory factors

3. Pilot Study • Involved 388 patients • Mental health accounted for less than 2% of workload and mostly severe illnesses e.g. Psychosis • Most patients who met research tool diagnosis of common mental disorders treated for malaria and MSP • Malaria is very common and endemic in Malawi and accounts for about 35% of OPD diagnoses • In adults, we found that MSP(MUS) accounted for 18% of diagnoses during pilot study

4. Malawi Malawi is a country with • area approx - 118 000 sq km • Population est.: 13 million • Sex ratio (men/ 100 women): 98 • Proportion of population under 15 years - 47 %; over 60 % - 5 % • Literacy rate: 75.5 % for men; 48 % for women • Divided into 3 regions, Northern, Central & Southern & further divided into 28 districts & Lilongwe being Capital city. • Structure of health system is from health post, health centres, district hospital and tertiary hospitals • Very low number of mental health professionals and psychiatric nurses form backbone of mental health services • Medical assistants (paramedics) are the cadre which works in primary care

5. OBJECTIVES OF STUDY • To determine the prevalence of common mental disorders in primary health units in a designated district in the southern region of Malawi • To determine the effect of PHC trainings on the number of patients with common mental health problems (depression and anxiety) treated at primary health units in a designated district in the southern region of Malawi. • To determine the impact of PHC trainings in mental health on other clinic parameters including cases of clinically diagnosed malaria and of medically unexplained symptoms

6. Major hypotheses for Study Flow diagram illustrating hypothesis Training of PHC workers in mental health Increased detection and management of patients with mental health problems Decrease in cases of erroneously diagnosed malaria Decrease in cases of medically unexplained symptoms

7. Training of research assistants and checking of inter-later reliability Participating information and consent forms sent to PHC Workers in all 18 clusters Baseline Data collection in all 18 clusters for 1 month N= 800 Randomization of Cluster units after pair matching 18 clusters 22 PHC workers 2600 patients Intervention arm PHC Worker Trainings using Toolkit: 5 days Control arm PHC Worker Training using normal –in-service: 3 days Data Collection 9 Clusters 11 PHC workers N= approx. 1300 Data Collection 9 Clusters 11 PHC workers N= approx. 1300 Flow diagram of study

8. Summary of Intervention toolkit • Designed by Prof. Rachel Jenkins • Being used to train 3000 PHC workers in Kenya • Adapted for Malawi • Made up of five units; A. Unit 1on concepts in mental health B. Unit 2 on history taking and MSE C. Unit 3 on Common mental health disorders D. Unit 4 on neurological disorders E. Unit 5 National mental health policy

9. Randomization • Unit of randomization was the health centre • All 18 health centres with OPD facilities included • Health centres pair-matched according to average daily attendance rates • Randomization done by a statistician in Liverpool not involved in study and with no knowledge of study area • All 22 primary health workers working in the randomized health centres participated in study

10. ALL ADULTS ATTENDING CLINIC Age < 16 yrs Refuse consent Very ill Participated already Exclusion criteria SRQ COMPLETED NORMAL CONSULTATION: Clinician Diagnosis POTENTIAL CASES ACCORDING TO SRQ SCORE > 9 NON-POTENTIAL CASES, SRQ SCORE < 9 All patients 10% patients 90% cases SCID FOR DEPRESSION SCREENING NO FURTHER ACTION Non- Cases Positive for depression REGISTER AS DEFINITE CASES FOR DEPRESSION NO FURTHER ACTION Clinic Procedure

11. Data analysis • Design effect incorporated in sample size calculation • Analysis done using multilevel analysis on STATA • Individual level rather than cluster level analyses used • Two level nesting rather then three level nesting used • Multilevel regression methods rather then traditional regression methods used in analysis

12. Results I: Comparative and descriptive analysis • No significant differences at baseline in patient factors apart from number of presenting symptoms • All patients presented with physical symptoms • Average no. Of presenting symptoms was 1.8 in control arm and 2.0 in intervention, p value 0.04 • No significant differences in patient factors at follow up • Average number of presenting symptoms in both arms was 2.3 at follow up • Nearly 100% of patients presented with physical symptoms at follow up

13. Prevalence rates

14. Results of main outcomes at baseline

15. Graph of Results of Main outcomes at baseline

16. Comparison of clinician diagnosis against research tool diagnosis of depression at baseline

17. Factors associated with main outcomes at baseline • Since rates of depression and anxiety were 0% at baseline, no factors analyzed for these two main outcomes • Malaria diagnosis strongly associated with number of presenting symptoms. Odds of a malaria diagnosis increased by 89% for each increase in symptom. Nil effect of arm. Others factors, nil significant association • MSP diagnosis associated with patient age. Highest in 26-35 yrs age group (OR 2.02), and lowest in 60+ (OR 0.32), compared to those aged 25yrs or less • Number of presenting symptoms had no significant association with MSP diagnosis

18. Results of main outcomes at follow up

19. Graph illustrating results of main outcomes at follow up

20. Factors associated with a diagnosis of depression at follow up(multivariate analysis results)

21. Factors associated with a diagnosis of Malaria and MSP at follow up • Health worker sex and patient age found to be significantly associated with a diagnosis of malaria and MSP at follow up • Male health workers more likely to make a diagnosis of malaria compared to females (OR 1.40, p= 0.01), and malaria diagnosis less likely in the 61+ age group (OR 0.59, p= 0.006) compared to those aged 25 yrs or less • Male health workers less likely to make diagnosis of MSP compared to female health workers (OR 0.62, p= 0.02) and MSP diagnosis more likely in the 61+ age group ( OR 3.03, p = < 0.001) compared to those aged 25 or less • Diagnosis of MSP also significantly associated with patient occupation (OR 1.64, p= 0.08) with farmers more likely to be diagnosed than those with no occupation • Malaria diagnosis also significantly associated with number of symptoms with arm effect. Odds of malaria diagnosis increasing by 91% for each increase in symptom in control arm and 54% in intervention arm

22. Baseline versus follow-up data (control)

23. Baseline versus Follow- up (intervention)

24. Detection rates for depression

25. Discussion • Prevalence of common mental disorders in primary care in Malawi not different to other countries • Detection and management of CMDs very low • High probability that patients with CMD are erroneously misdiagnosed for clinical malaria and MSP • Special toolkit shown to be effective especially in detecting depression with moderate sensitivity and kappa co-efficient despite very high attendance rates with limited consultation times • Good detection of CMD leads to a decrease in cases erroneously misdiagnosed malaria