Evidence map›Paper›PMID 31628787›Full record

ReviewJMIR public health and surveillance2019

Using Web-Based Pin-Drop Maps to Capture Activity Spaces Among Young Adults Who Use Drugs in Rural Areas: Cross-Sectional Survey.

Hannah Luke Fenimore Cooper, Natalie D Crawford, Regine Haardörfer, Nadya Prood, Carla Jones-Harrell, Umedjon Ibragimov, April M Ballard, April M Young

Open access · goldAbstract readReview
In one paragraph

Review in JMIR public health and surveillance, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.7field-weighted citation impact, top 10% 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

7 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. 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

8 authors at 2 institutions in 1 country.

Hannah Luke Fenimore Cooper *Rollins School of Public Health, Emory University, Atlanta, GA, United States.ORCID https://orcid.org/0000-0002-0521-2438
Natalie D Crawford *Rollins School of Public Health, Emory University, Atlanta, GA, United States.ORCID https://orcid.org/0000-0001-7397-8008
Regine Haardörfer *Rollins School of Public Health, Emory University, Atlanta, GA, United States.ORCID https://orcid.org/0000-0002-5470-9352
Nadya ProodRollins School of Public Health, Emory University, Atlanta, GA, United States.ORCID https://orcid.org/0000-0002-9577-4396
Carla Jones-HarrellRollins School of Public Health, Emory University, Atlanta, GA, United States.ORCID https://orcid.org/0000-0002-2257-1942
Umedjon IbragimovRollins School of Public Health, Emory University, Atlanta, GA, United States.ORCID https://orcid.org/0000-0001-7111-2139
April M BallardRollins School of Public Health, Emory University, Atlanta, GA, United States.ORCID https://orcid.org/0000-0003-3839-5637
April M Young *College of Public Health, University of Kentucky, Lexington, KY, United States.ORCID https://orcid.org/0000-0003-3969-3249
Emory University · USUniversity of Kentucky · US

Funding

Virology and Molecular Biomarkers CoreP30AI050409 · NIAID · EMORY UNIVERSITY · PI Carlos del Rio · 2002 to 2026
$74.0M
Kentucky Communities and Researchers Engaging to Halt the Opioid Epidemic (CARE2HOPE)UH3DA044798 · NIDA · UNIVERSITY OF KENTUCKY · PI COOPER, HANNAH LF, YOUNG, APRIL MARIE · 2019 to 2022
$4.4M
Kentucky Communities & Researchers Engaging to Halt the Opioid Epidemic-CARE2HOPEUG3DA044798 · NIDA · UNIVERSITY OF KENTUCKY · PI COOPER, HANNAH LF, YOUNG, APRIL MARIE · 2017 to 2018
$1.3M
Novel methods for research on young rural opioid users at risk of HIV, HCV & ODR21DA042727 · NIDA · EMORY UNIVERSITY · PI COOPER, HANNAH LF, YOUNG, APRIL MARIE · 2016 to 2017
$437k
NIAID NIH HHS P30 AI050409NIDA NIH HHS R21 DA042727NIDA NIH HHS UG3 DA044798NIDA NIH HHS UH3 DA044798
6 · The paper itself

Abstract

backgroundEpicenters of harmful drug use are expanding to US rural areas, with rural young adults bearing a disproportionate burden. A large body of work suggests that place characteristics (eg, spatial access to health services) shape vulnerability to drug-related harms among urban residents. Research on the role of place characteristics in shaping these harms among rural residents is nascent, as are methods of gathering place-based data.

objectiveWe (1) analyzed whether young rural adults who used drugs answered self-administered Web-based mapping items about locations where they engaged in risk behaviors and (2) determined the precision of mapped locations.

methodsEligible individuals had to report recently using opioids to get high; be aged between 18 and 35 years; and live in the 5-county rural Appalachian Kentucky study area. We used targeted outreach and peer-referral methods to recruit participants. The survey asked participants to drop a pin in interactive maps to mark where they completed the survey, and where they had slept most; used drugs most; and had sex most in the past 6 months. Precision was assessed by (1) determining whether mapped locations were within 100 m of a structure and (2) calculating the Euclidean distance between the pin-drop home location and the street address where participants reported sleeping most often. Measures of central tendency and dispersion were calculated for all variables; distributions of missingness for mapping items and for the Euclidean distance variable were explored across participant characteristics.

resultsOf the 151 participants, 88.7% (134/151) completed all mapping items, and ≥92.1% (>139/151) dropped a pin at each of the 4 locations queried. Missingness did not vary across most participant characteristics, except that lower percentages of full-time workers and peer-recruited participants mapped some locations. Two-thirds of the pin-drop sex and drug use locations were less than 100 m from a structure, as were 92.1% (139/151) of pin-drop home locations. The median distance between the pin-drop and street-address home locations was 2.0 miles (25th percentile=0.8 miles; 75th percentile=5.5 miles); distances were shorter for high-school graduates, staff-recruited participants, and participants reporting no technical difficulties completing the survey.

conclusionsMissingness for mapping items was low and unlikely to introduce bias, given that it varied across few participant characteristics. Precision results were mixed. In a rural study area of 1378 square miles, most pin-drop home addresses were near a structure; it is unsurprising that fewer drug and sex locations were near structures because most participants reported engaging in these activities outside at times. The error in pin-drop home locations, however, might be too large for some purposes. We offer several recommendations to strengthen future research, including gathering metadata on the extent to which participants zoom in on each map and recruiting participants via trusted staff.

Indexed as

activity spacesgeospatial methodsrisk environmentruralsubstance use disorderWeb-based data collection

Identifiers

PMID31628787
PMCPMC6913769
OpenAlexW2921978561

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.