Evidence map›Paper›PMID 39611051›Full record

ArticleInternet interventions2024

Predictors of participant compliance with ecological momentary assessment among individuals with chronic pain who are using cannabis and opioids.

Jungin Joo, Janardan Devkota, Bryant M Stone, Kelly E Dunn, Vadim Zipunnikov, Ryan Vandrey, Patrick H Finan, Johannes Thrul

Abstract read
In one paragraph

Article in Internet interventions, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Observational
  4. Observational
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

8 authors.

Jungin JooDepartment of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea.
Janardan DevkotaDepartment of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Bryant M StoneDepartment of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Kelly E DunnDepartment of Psychiatry & Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Vadim ZipunnikovDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
Ryan VandreyDepartment of Psychiatry & Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Patrick H FinanDepartment of Psychiatry & Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Johannes ThrulDepartment of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.

Funding

NIDA Epidemiology Training Program: Johns Hopkins UniversityT32DA007292 · NIDA · JOHNS HOPKINS UNIVERSITY · PI RENEE M. JOHNSON, Brion S Maher · 1993 to 2026
$17.7M
Development of a Longitudinal Observational Research Registry for the Study of Medicinal Cannabis Use and HealthUM1DA059000 · NIDA · JOHNS HOPKINS UNIVERSITY · PI Johannes Thrul, RYAN G VANDREY · 2023 to 2026
$8.1M
Real Time Monitoring of Prescription Opioid and Cannabis Co-Use in Patients with Chronic PainR21DA048175 · NIDA · JOHNS HOPKINS UNIVERSITY · PI THRUL, JOHANNES · 2020 to 2021
$450k
NIDA NIH HHS R21 DA048175NIDA NIH HHS T32 DA007292NIDA NIH HHS UM1 DA059000
6 · The paper itself

Abstract

Background: Cannabis may be an alternative or adjunct to opioid therapy for chronic pain. However, there are limited data on patterns of opioid medication and medical cannabis use. The current study investigated the feasibility of using Ecological Momentary Assessment (EMA) to assess patterns of prescription opioids and medical cannabis among individuals experiencing chronic pain. Method: The study included 133 participants recruited online. Participants were 42.6 (SD = 13.9) years old on average and the majority were men (57.9 %) and Non-Hispanic White (63.2 %). Participants completed a baseline assessment, followed by 30 days of EMA data collection with four randomly prompted past-hour surveys and one daily diary per day, and a follow-up survey that assessed perceived EMA burden. Simple and multivariable linear regression models were estimated to investigate participant predictors of the proportion of EMA surveys completed (past-hour surveys and daily diaries in separate models). Results: Compliance rates for EMA prompts were 89.7 % for daily diaries and 63.3 % for past-hour surveys. In multivariable regression, participants holding a graduate degree completed a lower proportion of daily diaries ( Conclusions: Study results confirm the feasibility of using EMA methods to assess patterns of prescription opioids and medical cannabis among individuals experiencing chronic pain.

Indexed as

CannabisChronic painComplianceEcological momentary assessmentOpioidPatterns

Identifiers

PMID39611051
PMCPMC11602567

What OpenQuestion holds

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Registered trials

None linked

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.