In Uganda, service communication was used to improve net durability. The activities – designed by a group of health workers, school teachers, district leaders, and SBCC experts - included mass media, community mobilization, and clinic posters. The evaluation showed that the intervention resulted in improved knowledge and attitudes towards care and repair, which impacted positively on net condition.

impactofbccnetsuganda

Source: Impact of a behaviour change communication programme on net durability in eastern Uganda

 

 

Results below from a facility-based cluster randomized trial in Tanzania found that a communication intervention was associated with improved prescriber adherence to rapid diagnostic test results, and reduced over-prescription of antimalarials to almost zero. Communication activities included interactive small group workshops, feedback and motivational SMS to providers, and patient leaflets and clinic posters in the facilities. Each of the activities led to incremental improvements in over-prescription of antimalarials. Provider behavior was changed through this combination of communication interventions.

The table below shows the results of the communication intervention.

Effect of Interventions on Antimalarial Prescribing, RDT Use and Antibiotic Prescribing

Outcome Arm Number of Patients Prevalence Number (%) Crude RDa (95% CI) Adjusted RD(95% CI) P-value
Patients with fever treated with rAM Control 9,231 2180 (24%) 0 0
HW 9,752 1700 (17%) 0.07 (0.004, 0.13) 0.03 (–0.04, 0.10) 0.44
HWP 7,887 1,304 (16%) 0.07 (0.01, 0.14) 0.05 (–0.002, 0.10) 0.06
Patients with no fever treated with rAM Control 4,863 82 (2%) 0 0
HW 6,062 193 (3%) –0.003 (–0.02, 0.01) 0.002 (–0.01, 0.01) 0.52
HWP 5,984 40 (1%) 0.01 (–0.01, 0.03) 0.002 (–0.01, 0.01) 0.73
RDT Uptake
Patients with fever tested with RDT Control 9,297 4960 (53%) 0 0
HW 9,825 5374 (55%) –0.04 (–0.15, 0.07) –0.04 (–0.20, 0.10) 0.57
HWP 7,963 5153 (65%) –0.12 (–0.21, –0.03) –0.02 (–0.13, 0.09) 0.72
RDT eligible (fever and no obvious alternate diagnosis) not tested Control 8,241 3697 (45%) 0 0
HW 9,064 4000 (44%) 0.04 (–0.07, 0.15) 0.06 (–0.11, 0.23) 0.44
HWP 7,292 2459 (34%) 0.12 (0.04, 0.21) 0.18 (0.05, 0.32) 0.01
RDT ineligible (no fever) tested Control 4,874 587 (12%) 0 0
HW 6,083 955 (16%) –0.01 (–0.07, 0.04) 0.01 (–0.06, 0.07) 0.86
HWP 6,000 518 (9%) 0.02 (–0.05, 0.09) 0.02 (–0.04, 0.09) 0.43
Presumptive Treatment
RDT eligible treated presumptively for malaria Control 8,241 471 (6%) 0 0
HW 9,064 374 (4%) 0.02 (–0.01, 0.05) 0.01 (–0.02, 0.04) 0.40
HWP 7,292 256 (4%) 0.02 (–0.003, 0.05) 0.02 (–0.004, 0.05) 0.09
RDT ineligible treated presumptively for malaria Control 4,874 42 (1%) 0 0
HW 6,083 47 (1%) 0.004 (–0.001, 0.01) 0.003 (–0.001, 0.01) 0.15
HWP 6,000 12 (0.2%) 0.007 (0.003, 0.01) 0.004 (–0.0001, 0.01) 0.05
Adherence to RDT negative
RDT negative receiving AM Control 4,015 762 (19%) 0 0
HW 4,539 250 (6%) 0.14 (0.08, 0.20) 0.10 (0.03, 0.17) 0.01
HWP 4,330 189 (4%) 0.15 (0.09, 0.21) 0.10 (0.04, 0.16) 0.002
RDT negative receiving AM (among those with fever) Control 3,488 723 (21%) 0 0
HW 3,793 235 (6%) 0.16 (0.08, 0.23) 0.11 (0.03, 0.19) 0.01
HWP 3,897 177 (5%) 0.21 (0.04, 0.17) 0.12 (0.05, 0.19) 0.002
RDT negative receiving AM (among those with no fever) Control 527 39 (7%) 0 0
HW 746 15 (2%) 0.05 (–0.01, 0.10) 0.03 (0.01, 0.05) 0.004
HWP 433 12 (3%) 0.04 (–0.01, 0.10) - -

Source: Cundill et al. BMC Medicine (2015) 13:118.

 

For additional malaria-related evidence on the impact of integrating SBCC and health services, see the following resources: