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


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


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

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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

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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

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

Flow diagram of study
Data Collection
9 Clusters
11 PHC workers
N= approx. 1300
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
Intervention arm PHC Worker
Trainings using Toolkit : 5 days
Randomization of Cluster units after pair matching
18 clusters
22 PHC workers
2600 patients
Control arm PHC Worker Training using normal –in-service : 3 days
Data Collection
9 Clusters
11 PHC workers
N= approx. 1300


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

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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
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Randomization done by a statistician in Liverpool not involved in study and with no knowledge of study area
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All 22 primary health workers working in the randomized health centres participated in study

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


Design effect incorporated in sample size calculation
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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


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

Total
SRQ score below 9
SRQ score
9 and above
Total
Number
837
596
241
%
100% 430
71.2% 298
Control
Number %
Intervention
Number
100% 407
69.3% 298
%
100%
73.2%
28.8% 109 30.7% 109 26.8%
Weighted Prevalence rate for depression was 19%

Variable Category
Malaria diagnosis
MSP diagnosis
NO
YES
NO
YES
Control
Number (%)
326 (76%)
104 (24%)
379 (88%)
51 (12%)
Intervention
Number (%)
310 (76%)
97 (24%)
319 (78%)
88 (22%)
Odds Ratio
(95% CI)
1
0.95 (0.64,
1.41)
-
1
1.85 (0.89,
3.85)
-
P-value
0.80
0.10
Depression
Anxiety
NO
YES
NO
YES
430 (100%)
0 (0%)
430 (100%)
0 (0%)
407 (100%)
0 (0%)
407 (100%)
0 (0%)
-

Comparison of clinician diagnosis against research tool diagnosis of depression at baseline
Time/Analy sis
Baseline
Outcome
Malaria
MSP
Arm
Control
Intervention
Diagnosis
Number (%)
19/61 (31%)
15/51 (29%)
Control
Intervention
4/61 (7%)
11/51 (22%)
Odds Ratio
(95% CI)
1
0.76(0.20,2.
84)
1
5.84 (0.62,
54.9)
P-value
0.69
0.12

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
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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

Variable Category
Malaria diagnosis
MSP diagnosis
Depression
Anxiety
NO
YES
NO
YES
NO
YES
NO
YES
Control
Number (%)
779 (60%)
521 (40%)
1202 (92%)
98 (8%)
1294 (99%)
6 (1%)
1300 (100%)
0 (0%)
Interventio n
Number
(%)
897 (69%)
403 (31%)
1160(89%)
140 (11%)
1181(91%)
119 (9%)
1284(99%)
16 (1.2%)
Unadjusted
OR (95%
CI)
[p-value]
1
0.56 (0.37,
0.86)
[p=0.007]
1
1.24 (0.71,
2.16)
[p=0.46]
1
32.1 (7.4,
144.3)
[p<0.001]
1
[p<0.001]
-
Adjusted
OR (95%
CI)
[p-value]
1
0.62 (0.43,
0.89)
[p=0.01]
-
1
0.62 (0.39,
1.01)
[p=0.06]

Factors associated with a diagnosis of depression at follow up(multivariate analysis results)
P-value Variable Category
Health worker age 21 – 40 yr
41 – 60 yr
61 +
Patient sex Female
Male
Patient marital status
Married
Single/Divorced/W idow
Number of symptoms
Odds Ratio (95% CI)
1
1.42 (0.82, 2.45)
0.13 (0.02, 0.90)
1
0.60 (0.37, 0.98)
1
1.76 (1.18, 2.61)
1.76 (1.18, 2.61)
0.03
0.04
0.005
<0.001

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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

Diagnostic sensitivity
Diagnostic specificity
Kappa Co-efficient
Kappa
0.00
0.01 – 0.20
0.21 – 0.40
0.41 – 0.60
0.61 – 0.80
0.81 – 1.00
Control
3.19%
66.67%
0.0145
Strength of agreement poor slight fair moderate substantial
Almost perfect
Intervention
60.24%
82.02%
0.4632


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
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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