Kleine-Kracht, Donald (2019-11). Predicting Treatment Response and No-Show Appointments for Low-Income and Rural Populations at a Community Mental Health Clinic. Doctoral Dissertation.
Thesis
Mental health disparities for marginalized populations are a critical issue requiring immediate national research attention. This study, which utilized archived data from a community mental health clinic in Bryan, Texas, explored how a client's level of income and rurality predicts their treatment-related outcomes. This study utilized two adult samples: a total sample (n = 330) and an outpatient clinical subsample (n = 240). A client's level of rurality was identified by the distances they travelled to the clinic and the population density of their home address, while a client's level of income was determined through their session fee derived from their income level on a sliding fee scale. Logistic regressions were used to predict a client's positive treatment response and negative binomial regressions were used to predict No-Show appointments. This study was not able to significantly statistically predict treatment response, but was able to predict No-Show appointments. Population Density, Distance Travelled, and Session Fee were statistically significant in predicting No-Show appointments. Marginal analyses were also used to explore differences in the levels of rurality and income in the statistically significant model. Results suggest that clients living in lower populated areas, travel shorter distances, and pay lower session fees were associated with more No-Show appointments than clients in higher populated areas, drove further distances, and paid more per session. This study further provides recommendations for future research and policy-makers who aim to alleviate treatment access barriers for low-income and rural client populations.
