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 in Primary care
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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
Pilot Study
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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
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
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
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
Flow diagram of study
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
Data Collection
9 Clusters
11 PHC workers
N= approx. 1300
Control arm PHC Worker Training
using normal –in-service: 3 days
Data Collection
9 Clusters
11 PHC workers
N= approx. 1300
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
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Randomization
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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
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
Clinic Procedure
ALL ADULTS ATTENDING CLINIC
Exclusion criteria
Age < 16 yrs
Refuse consent
Very ill
Participated already
SRQ COMPLETED
NORMAL CONSULTATION: Clinician Diagnosis
POTENTIAL CASES
ACCORDING TO SRQ SCORE > 9
All patients
NON-POTENTIAL CASES,
SRQ SCORE < 9
10% patients
SCID FOR DEPRESSION SCREENING
Positive for depression
REGISTER AS DEFINITE CASES FOR
DEPRESSION
90% cases
NO FURTHER ACTION
Non- Cases
NO FURTHER ACTION
Data analysis
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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
Results I: Comparative and
descriptive analysis
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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
Prevalence rates
Total
Number
Control
%
100%
Number
%
SRQ score
below 9
596
71.2%
298
69.3%
298
73.2%
SRQ score
9 and
above
241
28.8%
109
30.7%
109
26.8%
Weighted
Prevalence
depression
407
%
837
for
100%
Number
Total
rate
430
Intervention
was
100%
19%
Results of main outcomes at
baseline
Variable
Category
Control
Number (%)
Intervention
Number (%)
Odds Ratio
(95% CI)
Malaria
diagnosis
NO
YES
326 (76%)
104 (24%)
310 (76%)
97 (24%)
1
0.95 (0.64,
1.41)
0.80
MSP diagnosis
NO
YES
379 (88%)
51 (12%)
319 (78%)
88 (22%)
1
1.85 (0.89,
3.85)
0.10
Depression
NO
YES
430 (100%)
0 (0%)
407 (100%)
0 (0%)
-
-
NO
YES
430 (100%)
0 (0%)
407 (100%)
0 (0%)
-
-
Anxiety
P-value
Graph of Results of Main outcomes
at baseline
Comparison of clinician diagnosis against research
tool diagnosis of depression at baseline
Time/Analy
sis
Outcome
Arm
Diagnosis
Number (%)
Odds Ratio
(95% CI)
Baseline
Malaria
Control
Intervention
19/61 (31%)
15/51 (29%)
1
0.76(0.20,2.
84)
0.69
Control
Intervention
4/61 (7%)
11/51 (22%)
1
5.84 (0.62,
54.9)
0.12
MSP
P-value
Factors associated with main
outcomes at baseline
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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
Results of main outcomes at follow
up
Variable
Category
Control
Number (%)
Interventio
n
Number
(%)
Unadjusted
OR (95%
CI)
[p-value]
Adjusted
OR (95%
CI)
[p-value]
Malaria
diagnosis
NO
YES
779 (60%)
521 (40%)
897 (69%)
403 (31%)
1
0.56 (0.37,
0.86)
[p=0.007]
1
0.62 (0.43,
0.89)
[p=0.01]
MSP diagnosis
NO
YES
1202 (92%)
98 (8%)
1160(89%) 1
140 (11%) 1.24 (0.71,
2.16)
[p=0.46]
1
0.62 (0.39,
1.01)
[p=0.06]
Depression
NO
YES
1294 (99%)
6 (1%)
1181(91%) 1
119 (9%)
32.1 (7.4,
144.3)
[p<0.001]
-
Anxiety
NO
1300 (100%)
1284(99%) 1
-
Graph illustrating results of main
outcomes at follow up
Factors associated with a diagnosis of depression
at follow up(multivariate analysis results)
Variable
Category
Odds Ratio (95% CI)
P-value
Health worker age
21 – 40 yr
41 – 60 yr
61 +
1
1.42 (0.82, 2.45)
0.13 (0.02, 0.90)
0.03
Female
Male
1
0.60 (0.37, 0.98)
0.04
Patient sex
Patient marital
status
Number of
symptoms
Married
1
Single/Divorced/W 1.76 (1.18, 2.61)
idow
1.76 (1.18, 2.61)
0.005
<0.001
Factors associated with a diagnosis
of Malaria and MSP at follow up
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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
Baseline versus follow-up data
(control)
Baseline versus Follow- up
(intervention)
Detection rates for depression
Control
Intervention
Diagnostic sensitivity
3.19%
60.24%
Diagnostic specificity
66.67%
82.02%
Kappa Co-efficient
0.0145
0.4632
Kappa
Strength of agreement
0.00
poor
0.01 – 0.20
slight
0.21 – 0.40
fair
0.41 – 0.60
moderate
0.61 – 0.80
substantial
0.81 – 1.00
Almost perfect
Discussion
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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
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Training primary health workers in mental health and its impact on