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Symptom severity upon admission and frequency of hospital readmission as predictors of medication adherence and length of stay for involuntary adults in an inpatient psychiatric facility

<p> Severely mentally ill adults are a historically underserved population that tends to be highly resistant to taking psychiatric medications. Although medications generally help to decrease the severity of symptoms and lower risk of relapse/hospital readmission, they also negatively impact sense of self and identity, and lead to unwanted side effects. Non adherence frequently leads to involuntary hospitalizations, where a medication adherence intervention is needed. In order to make a case for a medication adherence intervention, regression analyses were conducted on an inpatient psychiatric sample of 178 adults diagnosed with severe mental illnesses in order to determine predictive relationships between symptom severity upon admission, frequency of hospital readmission, medication adherence/non-adherence, and length of hospital stay (LOS). Results yielded insignificant findings, which is informative and even compelling due to medications being considered the gold standard in inpatient psychiatric care. Results were limited by medication adherence being measured dichotomously, and confounds related to ethnicity, family involvement, and substance abuse. Post-hoc analyses yielded significant relationships between pretest symptom severity and length of stay, as well as significance between medication non-adherence and elevations on the symptoms: Conceptual Disorganization, Grandiosity, Suspiciousness, and Motor Retardation, which indirectly support concerns about severely mentally ill adults not taking medications due to concerns related to autonomy and distrust of providers. Implications and future research and practice are also discussed.</p>

Identiferoai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:3714400
Date03 September 2015
CreatorsDanzer, Graham
PublisherAlliant International University
Source SetsProQuest.com
LanguageEnglish
Detected LanguageEnglish
Typethesis

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