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Abstract Background Health workers lack the competence to address maternal depression in the routine health education in Nigeria. Hence, awareness among maternal-child health clients is low. We assessed the effect of training and supervision on knowledge, skills, and self-efficacy of primary healthcare workers in delivering health talks and the clients’ knowledge on maternal depression. Methods A quasi-experimental study design was adopted. Five Local Government Area (LGAs) in the Ibadan metropolis were grouped according to geographical proximity and randomly assigned to experimental (Group A = two LGAs) and control (Group B = three LGAs) with 12 primary health centres in each group. All primary health care workers recruited in group A received a one-day training on maternal depression. Good Knowledge Gain (GKG), Good Skill Gain (GSG) and Self-Efficacy (SEG) were assessed in both groups. 1-week post-training, the knowledge of all the PHCs’ attendees in the two groups was assessed. Two weeks post- training, a half of experimental group’s PHCs received supportive supervision and a clinic-based health education delivery skill assessment was conducted. The knowledge of clients and their health seeking were also assessed. Fisher’s exact test, independent t test and Poisson regression were used to analyze differences in percentages and mean/ factors associated with GKG, GSG and SE, using SPSS 25. Results Training improved gains in the experimental versus controls as follows: GKG (84.3% vs. 15.7%), GSG (90.7% vs 9.3%) and SEG (100% vs 0%). Training contributed to the good gain in knowledge (RR = 6.03; 95%CI =2.44–16.46; p

BACKGROUND: This study aimed to develop a risk-scoring model for hypertension among Africans. METHODS: In this study, 4413 stroke-free controls were used to develop the risk-scoring model for hypertension. Logistic regression models were applied to 13 risk factors. We randomly split the dataset into training and testing data at a ratio of 80:20. Constant and standardized weights were assigned to factors significantly associated with hypertension in the regression model to develop a probability risk score on a scale of 0 to 1 using a logistic regression model. The model accuracy was assessed to estimate the cutoff score for discriminating hypertensives. RESULTS: Mean age was 59.9±13.3 years, 56.0% were hypertensives, and 8 factors, including diabetes, age =65 years, higher waist circumference, (BMI) =30 kg/m², lack of formal education, living in urban residence, family history of cardiovascular diseases, and dyslipidemia use were associated with hypertension. Cohen κ was maximal at =0.28, and a total probability risk score of =0.60 was adopted for both statistical weighting for risk quantification of hypertension in both datasets. The probability risk score presented a good performance--receiver operating characteristic: 64% (95% CI, 61.0-68.0), a sensitivity of 55.1%, specificity of 71.5%, positive predicted value of 70.9%, and negative predicted value of 55.8%, in the test dataset. Similarly, decision tree had a predictive accuracy of 67.7% (95% CI, 66.1-69.3) for the training set and 64.6% (95% CI, 61.0-68.0) for the testing dataset. CONCLUSIONS: The novel risk-scoring model discriminated hypertensives with good accuracy and will be helpful in the early identification of community-based Africans vulnerable to hypertension for its primary prevention. [ABSTRACT FROM AUTHOR]