Background: Dependent variables in health psychology are often counts, for example, of a behaviour or number of engagements with an intervention. These counts can be very strongly skewed, and/or contain large numbers of zeros as well as extreme outliers. For example, ‘How many cigarettes do you smoke on an average day?’ The modal answer may be zero but may range from 0 to 40+. The same can be true for minutes of moderate-to-vigorous physical activity. For some people, this may be near zero, but take on extreme values for someone training for a marathon. Typical analytical strategies for this data involve explicit (or implied) transformations (smoker v. non-smoker, log transformations). However, these data types are ‘counts’ (i.e. non-negative whole numbers) or quasi-counts (time is ratio but discrete minutes of activity could be analysed as a count), and can be modelled using count distributions – including the Poisson and negative binomial distribution (and their zero-inflated and hurdle extensions, which alloweven more zeros). Methods: In this tutorial paper I demonstrate (in R, Jamovi, and SPSS) the easy application of these models to health psychology data, and their advantages over alternative ways of analysing this type of data using two datasets – one highly dispersed dependent variable (number of views on YouTube, and another with a large number of zeros (number of days on which symptoms were reported over a month). Results: The negative binomial distribution had the best fit for the overdispersed number of views on YouTube. Negative binomial, and zero-inflated negative binomial were both good fits for the symptom data with over-abundant zeros. Conclusions: In both cases, count distributions provided not just a better fit but would lead to different conclusions compared to the poorly fitting traditional regression/linear models.

This review aims to locate existing studies on health-seeking behavior of people in Indonesia, identify gaps, and highlight important findings. Articles were retrieved from Medline, Scopus, Web of Science, Academic Search Complete (via Ebsco), and ProQuest with a number of key words and various combinations. Articles from Indonesian journals were also searched for with Google Scholar. A total of 56 articles from peer-reviewed journal databases and 19 articles from Indonesian journals were reviewed. Quantitative designs were applied more frequently than qualitative, and mixed methods designs were used in some studies. The majority gathered retrospective information about people’s behaviors. Communicable diseases and maternity care were the most frequently studied conditions, in contrast to noncommunicable diseases. In terms of geographical distribution, most research was conducted on Java island, with very few in outside Java. Important findings are a model of Indonesian care-seeking pathways, an understanding of determinants of people’s care choices, and the role of sociocultural beliefs. The findings from this narrative review provide insight to what and how Indonesians make decisions to manage their illness and why. This makes an important contribution to understanding the problem of underutilization of medical services despite the government’s extensive efforts to improve accessibility.

Habitual behaviours are triggered automatically, with little conscious forethought. Theory suggests that making healthy behaviours habitual, and breaking the habits that underpin many ingrained unh...