Meteorologic predictors of symptoms in bipolar disorder

Date of Award




Degree Name

Doctor of Philosophy (Ph.D.)



First Committee Member

Sheri Johnson - Committee Chair


Although much progress has been made in understanding who will develop bipolar disorder, more research is required for us to be able to predict onset and course of specific episodes. Seasonality predicts episode relapse for some individuals, but methodological limitations hamper seasonality research. The present study employed a sample of 107 bipolar individuals from South Florida and Rhode Island who were participating in a longitudinal nontreatment study of bipolar disorder. For each individual, continuous-variable seasonality indices were created: Light/Depression, Light/Mania, Temperature/Depression, and Temperature/Mania. Distributions of these indices, as predicted, were normally distributed. Age, sex, personality, and latitude were examined as predictors of seasonality. Generally, hypotheses regarding predictors of seasonality were not upheld. Findings regarding latitude countered the proposed hypotheses. Results regarding whether seasonality is an absolute or relative phenomenon were inconclusive. To further validate the seasonality indices, their stability was examined. The indices were found to be unstable, though some validational evidence was provided by further post-hoc analyses. Specifically, seasonality and the seasonality-life events interaction were found to significantly contribute to the prediction of mood symptoms, indicating that life events may mask a seasonal pattern of symptoms. Findings of the current study highlight the importance of operationalizing seasonality as a continuous variable, determining which meteorologic indices account for seasonal patterns, and accounting for life events when assessing for a seasonal pattern. Directions for future research are discussed.


Psychology, Clinical

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