Date of Award

2024

Document Type

Dissertation

Degree Name

Doctor of Psychology (PsyD)

Department

Graduate Department of Clinical Psychology

First Advisor

Rodger Bufford, PhD

Second Advisor

Winston Seegobin, PsyD

Third Advisor

Ken Logan, PsyD

Abstract

Objectives: Growing political polarization and instability in the United States has increasingly influenced reactions to important topics such as health disparities and class inequality. Political biases and divisions influence the health and wellbeing of individuals and institutions. This study was designed to examine the effects of political bias in the social sciences on mental health treatment seeking and outcomes. The experimental design observed potential differences in therapeutic relationship/alliance and treatment seeking based on the perception of political bias in a therapy context. Methods: Four groups of participants were formed based on self-identified political ideology and were asked to read a politically biased vignette and answer questions regarding therapeutic relationships and outcomes. This study tested the hypothesis that perceived political bias in a therapy context acts as a barrier to treatment and negatively impacts the therapeutic alliance/relationship. The primary researcher predicted that an interaction effect between perceived bias and participant self-identified political ideology would statistically predict scores on the outcome measures. Results: Initial regression models for the full sample of participants did not indicate differences between groups based on political ideology or bias. As such, this study did not find statistically significant results for the primary hypotheses predicting differences in outcomes measures of essential therapeutic factors based on self-identified political ideology or perceived political bias. After a participant correction controlling for rapid responders, a supplemental analysis revealed differences between groups based on politically bias therapy context. Additionally, the population density of the setting a person grew up in accounted for a statistically significant amount of the variance in outcomes, with a small effect size. Conclusions: Discussion contains methodological limitations and directions for future research related to implicit bias within the academic social sciences. Key limitations for this study included the omission of validity check questions, flaws in how the data service defined a “quality completed response,” the sample was not drawn from the clinical mental health setting, and the analogue nature of the study may not observe the same psychological effects as lived experience. Future directions could include correcting the limitations described and sampling for regional effects, especially in specific populations thought to be experiencing this phenomenon, like some military and first responders.

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