Older adults represent the fastest growing demographic of cannabis users, and they endorse cannabis use for a variety of reasons including modulation of chronic pain, mental health symptoms, and sleep concerns. Despite escalating patterns of use, current evidence leaves questions of efficacy unanswered among these groups of users. Goals of the present study were to examine the role of medicinal cannabis within subjects at the daily level on the interrelated symptoms of depression, anxiety, sleep, and pain. A final sample of 106 medical cannabis users were recruited nationwide, ranging from 55 to 74 years of age (66.67% female, 82.86% white). A fully within-subject multilevel structural equation model was conducted with use patterns and symptomology broken into four temporal epochs. Subjective intoxication (Epoch 1) averaged across the day was used to predict subsequent anxiety, depression, and pain levels (Epoch 2), which then were used to predict sleep that night (Epoch 3), then subsequent anxiety, depression, and pain levels the following day (Epoch 4) prior to initiation of cannabis use. Results indicated that subjective intoxication negatively predicted post-use anxiety, depression, and pain. There was also a significant indirect effect from subjective intoxication to sleep quality through post- use anxiety. These findings provide evidence of momentary improvement in symptomology, but do not speak to long term changes. Findings are limited by measures used and potential expectancy effects but may help practitioners and patients determine windows for therapeutic use and identify potential development of problematic use as reinforced by momentary improvements in symptomology. Despite its limitations, the results of this study contribute to a growing body of research evaluating the efficacy of medicinal cannabis use for older adults.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2023-1230 |
| Date | 01 January 2024 |
| Creators | Maynard, Madison H |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Thesis and Dissertation 2023-2024 |
| Rights | In copyright |
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