Published in:
Open Access 01-12-2019 | Opioids | Research article
The Severity of Dependence Scale detects medication misuse and dependence among hospitalized older patients
Published in: BMC Geriatrics | Issue 1/2019
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Background
In older patients, timely recognition and treatment of medication misuse and dependence are crucial to secure medication safety and to avoid increasing health expenditure. Nonetheless, the detection of this condition remains challenging due to the paucity of screening instruments validated for older people.
This study assesses diagnostic accuracy, reliability, validity and the factor structure of the Severity of Dependence Scale (SDS) in detecting medication misuse and dependence among hospitalized older patients, focusing on prescribed central nervous system depressants (CNSDs): opioid analgesics, benzodiazepines and z-hypnotics.
Methods
246 adults aged 65–90 were recruited consecutively from somatic departments of the Akershus University Hospital, Norway. Among these, 100 patients were identified as prolonged users of CNSDs. Diagnostic accuracy and validity of the SDS were assessed using DSM-IV criteria for substance abuse and dependence as the reference standard. We also performed an exploratory factor analysis and assessment of internal consistency using Cronbach’s alpha.
Results
The area under the ROC curve was 0.86 (95%CI = 0.79–0.93; p < 0.001). A score of 5.5 was determined as the optimal cutoff for detecting CNSD misuse and dependence among older patients. Cronbach’s alpha obtained was satisfactory (α = 0.73). There was a significant positive correlation between the SDS score and DSM-IV criteria for substance abuse and dependence (Pearson’s correlation coefficient = 0.61, p < 0.001). The uni-dimensionality of the SDS was documented.
Conclusions
The SDS is reliable, valid and capable of detecting medication misuse and dependence among hospitalized older patients, with good diagnostic performance. The scale thus holds promise for use in both clinical and research contexts.
Trial registration
ClinicalTrials.gov Identifier: NCT03162081. Registered 3 May 2017.