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Optimizing data visualization for reproductive,maternal,newborn,child health,and nutrition(RMNCH&N)policymaking:data visualization preferences and interpretation capacity among decision-makers in Tanzania
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作者 Tricia Aung Debora Niyeha +4 位作者 Shagihilu Shagihilu Rose Mpembeni Joyceline Kaganda ashley sheffel Rebecca Heidkamp 《Global Health Research and Policy》 2019年第1期360-373,共14页
Background:Reproductive,maternal,newborn,child health,and nutrition(RMNCH&N)data is an indispensable tool for program and policy decisions in low-and middle-income countries.However,being equipped with evidence do... Background:Reproductive,maternal,newborn,child health,and nutrition(RMNCH&N)data is an indispensable tool for program and policy decisions in low-and middle-income countries.However,being equipped with evidence doesn’t necessarily translate to program and policy changes.This study aimed to characterize data visualization interpretation capacity and preferences among RMNCH&N Tanzanian program implementers and policymakers(“decision-makers”)to design more effective approaches towards promoting evidence-based RMNCH&N decisions in Tanzania.Methods:We conducted 25 semi-structured interviews in Kiswahili with junior,mid-level,and senior RMNCH&N decision-makers working in Tanzanian government institutions.We used snowball sampling to recruit participants with different rank and roles in RMNCH&N decision-making.Using semi-structured interviews,we probed participants on their statistical skills and data use,and asked participants to identify key messages and rank prepared RMNCH&N visualizations.We used a grounded theory approach to organize themes and identify findings.Results:The findings suggest that data literacy and statistical skills among RMNCH&N decision-makers in Tanzania varies.Most participants demonstrated awareness of many critical factors that should influence a visualization choice—audience,key message,simplicity—but assessments of data interpretation and preferences suggest that there may be weak knowledge of basic statistics.A majority of decision-makers have not had any statistical training since attending university.There appeared to be some discomfort with interpreting and using visualizations that are not bar charts,pie charts,and maps.Conclusions:Decision-makers must be able to understand and interpret RMNCH&N data they receive to be empowered to act.Addressing inadequate data literacy and presentation skills among decision-makers is vital to bridging gaps between evidence and policymaking.It would be beneficial to host basic data literacy and visualization training for RMNCH&N decision-makers at all levels in Tanzania,and to expand skills on developing key messages from visualizations. 展开更多
关键词 Reproductive Maternal Newborn Child health Nutrition Data visualization Policy Tanzania
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