Evidence map›Paper›PMID 40372396›Full record

ArticlePsychiatry2025

Daily Impact of Medical Cannabis on Anxiety and Sleep Quality in Older Adults.

Madison Maynard, Robert D Dvorak, Daniel Paulson, Emily K Burr, Quinn Allen, Nichole R Lighthall, Apollonia E Lysandrou

Abstract read
In one paragraph

Article in Psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Quinn Allen
Nichole R LighthallORCID 0000-0002-8131-8373
Apollonia E LysandrouORCID 0000-0002-7798-5042

Funding

Applying Harm Reduction to Binge Eating Disorder: An Investigation of Protective Behavioral Strategies Against Uncontrolled EatingF31MH135713 · NIMH · UNIVERSITY OF CENTRAL FLORIDA · PI Emily K Burr · 2024 to 2026
$96k
NIMH NIH HHS F31 MH135713
6 · The paper itself

Abstract

objectiveOlder 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. However, current evidence leaves questions of efficacy unanswered among these groups. Goals of the present study were to examine the hypothesis that medical cannabis (MC) use will, at the daily level, predict lower pain, depression, anxiety, and improved sleep.

methodA final sample of 106 MC users were recruited nationwide (ages 55-74, 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. MC use, operationalized as subjective intoxication (Epoch 1), averaged across the day was used to predict subsequent pain, anxiety, and depression levels (Epoch 2), which were then used to predict sleep that night (Epoch 3), then subsequent pain, anxiety, and depression the following day (Epoch 4) prior to initiation of MC use.

conclusionsThese findings provide evidence of momentary improvements in pain, anxiety, depression, and indirect benefits for sleep quality. In combination with other findings, the results advance our understanding of the efficacy and limitations of MC among older adults. Findings are limited by MC measurement and sample homogeneity (primarily White, non-Hispanic female). Future research should seek to further measurement of use and corresponding effects and examine expectancy effects in aging clinical populations.

Indexed as

AnxietyChronic PainDepressionMedical MarijuanaSleep QualityAgedFemaleHumansMaleMiddle AgedMedical Marijuana

Identifiers

PMID40372396
PMCPMC12353920

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.