Evidence map›Paper›PMID 27876595›Full record

ArticleResearch in social & administrative pharmacy : RSAP2017

Behavioral, mental, and physical health characteristics and opioid medication misuse among community pharmacy patients: A latent class analysis.

Gerald Cochran, Valerie Hruschak, Jennifer L Bacci, Kenneth C Hohmeier, Ralph Tarter

Open access · greenAbstract read
In one paragraph

Article in Research in social & administrative pharmacy : RSAP, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.5field-weighted citation impact, top 14% of its field
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

10 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Brief intervention medication therapy management: Establishment of an opioid misuse intervention model delivered in a community pharmacy.American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists · 2021
    Article
  6. Article
  7. Article
  8. Observational
  9. Big Data's Role in Precision Public Health.Frontiers in public health · 2018
    Review
  10. Article
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

5 authors at 3 institutions in 1 country.

Gerald CochranUniversity of Pittsburgh, School of Social Work, 4200 Forbes Ave. #2006, Pittsburgh, PA 15260, USA; University of Pittsburgh, School of Medicine, Department of Psychiatry, 3811 O'Hara St, Pittsburgh, PA 15213, USA. Electronic address: gcochran@pitt.edu.
Valerie HruschakUniversity of Pittsburgh, School of Social Work, 4200 Forbes Ave. #2006, Pittsburgh, PA 15260, USA.
Jennifer L BacciUniversity of Washington, School of Pharmacy, Box 357631, H364 Health Sciences Building, Seattle, WA 98195-7631, USA.
Kenneth C HohmeierUniversity of Tennessee, College of Pharmacy, Department of Clinical Pharmacy, 193 Polk Ave. Suite 2D, Nashville, TN 37210, USA.
Ralph TarterUniversity of Pittsburgh, School of Pharmacy, 3501 Terrace St, Pittsburgh, PA 15261, USA.
University of Pittsburgh · USUniversity of Tennessee at Knoxville · USUniversity of Washington · US

Funding

Longitudinal Modeling of SUD EtiologyK05DA031248 · NIDA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI TARTER, RALPH E · 2012 to 2016
$679k
NIDA NIH HHS K05 DA031248
6 · The paper itself

Abstract

backgroundCommunity pharmacists are well-positioned to address the US opioid medication crisis, which has created a need to detect misuse risk in order to provide optimal patient care.

objectivesThis study sought to identify community pharmacy patient subgroups at risk for opioid medication misuse.

methodsThis study was a cross-sectional survey that examined behavioral, mental, and physical health characteristics among patients filling opioid pain medications. A convenience sample of adult patients filling opioid pain medications who were not receiving cancer treatment were screened in 2 urban and 2 rural community pharmacies in southwestern Pennsylvania. Patient subgroups were identified using latent class analysis. Latent class regression analysis was used to examine the association between subgroup membership and misuse.

resultsA total of 333 patients completed the survey (response rate 71.4%). Latent class analysis results showed that a 3-class solution best fit the data, which were labeled: mental health (8.4%, n = 28), poor health (79.6%, n = 265), and hazardous alcohol use (12%, n = 40). Individuals within the mental health subgroup had an increased risk for opioid medication misuse (Odds Ratio = 6.23, 95% CI = 5.13-7.33).

conclusionThese findings demonstrate heterogeneity of this population receiving prescribed opioids and the potential to identify subgroups with high misuse risk. These findings also support routine screening of patients filling opioid medications and suggest the need for evidence-based patient-centered intervention development.

Indexed as

Health StatusMental HealthAdultAlcoholismAnalgesics, OpioidFemaleHumansMaleMiddle AgedOdds RatioOpioid-Related DisordersPennsylvaniaPharmaciesPrescription Drug MisuseRural PopulationUrban PopulationAnalgesics, OpioidCommunity pharmacyLatent class analysisOpioid medication misuseScreening

Identifiers

PMID27876595
PMCPMC5815164
OpenAlexW2550754477

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.