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In Kenya, gaps exist in health service provision to slum residents, especially service availability and access to quality care. There is also little information on the health status of people living in slums other than in Nairobi. The purpose of this paper is to generate evidence for use in designing interventions to improve health services in four mid-sized slums in Embu, Nyeri and Thika, Kenya.

A cross-sectional survey of clients receiving services in health facilities was conducted in the targeted slums. Data were collected through face-to-face interviews. Factor scores were generated using the Rasch model; simple and multivariate logistic regression analyses were done using the R statistical software.

Overall, 81 per cent of the 203 participants reported being satisfied with health services. Most clients (89 per cent) reported that health facility staff greeted them warmly; 82 per cent said their consultation was private. The facility type, waiting time and client experience with service providers determined their satisfaction (p < 0.05).

Healthcare managers can improve client satisfaction levels by understanding the client flow in their facilities and addressing causes of client dissatisfaction, such as long waiting times, while at the same time promoting facilitating factors.

The authors use latent variable modelling to compute client satisfaction scores, which were dichotomised into two categories and fitted into a logistic regression model to identify factors that influence client satisfaction. Health facility clients in the four slums are satisfied with services and have confidence the providers will serve them in a friendly and professional manner that promotes respect and quality care. The paper recommend healthcare managers in similar settings carry out client flow analysis and institute remedial measures to address long waiting times. Qualitative studies are recommended to determine the reasons behind the high satisfaction levels reported in this study.

Price promotions are a common tool used by retailers to increase sales. This study aims to investigate the effect of consumer's numerical skills and other demographic characteristics on their ability to determine the best deal when conducting a grocery shop (referred to as deal competency).

A consumer survey (n = 308) was conducted online, collecting information about respondent's demographics and grocery shopping behaviours, numerical literacy using the subjective numeracy scale (SNS), and deal competency (a novel measure). Multiple regression analysis and Pearson's correlations were conducted using SPSSv26.

Overall, the mean SNS score for the total sample was 31.47 (SD = 8.27), and the mean sample deal competency score was 13.5 (SD = 2.3). Spearman's correlation analysis identified a moderate significant positive relationship between numerical skills and deal competency, r_s(303) = 0.360, p < 0.001. Regression analysis found significant positive relationships between numerical skills and being male, and with mathematical achievement; and between deal competency and age, mathematical achievement and educational achievement. Regarding buying behaviour, correlation analyses identified only one significant relationship between numerical skills (SNS score) and deal competency and variables relating to buying behaviour, namely a negative relationship between deal competency and amount spent on promotional food items in top up grocery shops.

This study contributes to the gap in literature regarding consumer ability to work out the best deal on promotions, presents a novel scale for describing consumer deal competency, and considers the comparative usefulness of using objective and subjective scales in similar studies.