Evidence map›Paper›PMID 33904828›Full record

ArticleJMIR public health and surveillance2021

The Psychosocial Predictors and Day-Level Correlates of Substance Use Among Participants Recruited via an Online Crowdsourcing Platform in the United States: Daily Diary Study.

Jennifer Payaal Jain, Claudine Offer, Christopher Rowe, Caitlin Turner, Carol Dawson-Rose, Thomas Hoffmann, Glenn-Milo Santos

Open access · goldAbstract read
In one paragraph

Article in JMIR public health and surveillance, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 43% 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

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. 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

7 authors at 3 institutions in 1 country.

Jennifer Payaal JainSan Francisco Department of Public Health, San Francisco, CA, United States.ORCID 0000-0002-6339-1649
Claudine OfferSan Francisco Department of Public Health, San Francisco, CA, United States.ORCID 0000-0003-0894-2943
Christopher RoweDivision of Epidemiology, School of Public Health, University of California, Berkeley, Berkeley, CA, United States.ORCID 0000-0002-2928-425X
Caitlin TurnerDepartment of Epidemiology and Biostatistics, School of Medicine, University of California, San Francisco, San Francisco, CA, United States.ORCID 0000-0003-2894-2318
Carol Dawson-RoseSan Francisco Department of Public Health, San Francisco, CA, United States.ORCID 0000-0001-6066-1853
Thomas HoffmannDepartment of Epidemiology and Biostatistics, School of Medicine, University of California, San Francisco, San Francisco, CA, United States.ORCID 0000-0001-6893-4449
Glenn-Milo SantosSan Francisco Department of Public Health, San Francisco, CA, United States.ORCID 0000-0003-1009-5317
San Francisco Department of Public Health · USUniversity of California, San Francisco · USUniversity of California, Berkeley · US

Funding

Substance Use Disorders Treatment/Services Research Training ProgramT32DA007250 · NIDA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Derek D Satre, Janice Y Tsoh · 1991 to 2026
$7.4M
Substance Use and HIV Prevention Research in Minority Communities Training ProgramR25DA028567 · NIDA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Julia Lechuga, Torsten Brian Neilands · 2009 to 2026
$5.4M
UCSF Data Science Training to Advance Behavioral and Social Science Expertise for Health Research (DaTABASE) ProgramT32MD015070 · NIMHD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI William Brown III, Yulin Hswen · 2020 to 2026
$1.7M
NIDA NIH HHS R25 DA028567NIDA NIH HHS T32 DA007250NIMHD NIH HHS T32 MD015070
6 · The paper itself

Abstract

backgroundAlcohol consumption and stimulant use are major public health problems and contribute to morbidity and mortality in the United States. To inform interventions for substance use, there is a need to identify the day-level correlates of substance use by collecting repeated measures data in one's natural environment. There is also a need to use crowdsourcing platforms like Amazon Mechanical Turk (MTurk) to efficiently engage larger populations of people who use alcohol and stimulants in research.

objectiveWe aimed to (1) utilize daily diaries to examine the temporal relationship between day-level cravings for alcohol and stimulant/substance use (ie, heavy drinking or any drug use) in a given day over 14 days and (2) assess whether depression, negative affect, and self-esteem measured at baseline predict substance use in a given day over 14 days among people who use alcohol and/or stimulants in the United States.

methodsIndividuals aged ≥18 years in the United States, who reported alcohol or stimulant (ie, cocaine, crack cocaine, and methamphetamine) use in the past year, were recruited using MTurk between March 26 and April 13, 2018. Eligible participants completed a baseline survey and 14 daily surveys online. The baseline survey assessed sociodemographics and psychosocial (ie, depression, affect, self-esteem, and stress) factors. Daily surveys assessed substance use and cravings for alcohol and stimulants. Four multivariable random-intercept logistic regression models were built to examine psychosocial constructs separately along with other significant predictors from bivariate analyses while controlling for age and education.

resultsAmong a total of 272 participants, 220 were White, 201 were male, and 134 were men who have sex with men (MSM). The mean age was 36.1 years (SD 10.5). At baseline, 173 participants engaged in any current or past hazardous alcohol consumption, 31 reported using cocaine, 19 reported using methamphetamine, 8 reported using crack cocaine, and 104 reported any noninjection or injection drug use in the past 6 months. Factors independently associated with substance use were depression (adjusted odds ratio [aOR] 1.11, 95% CI 1.02-1.21; P=.01), negative affect (aOR 1.08, 95% CI 1.01-1.16; P=.01), lower levels of self-esteem (aOR 0.90, 95% CI 0.82-0.98; P=.02), and cravings for alcohol (aOR 1.02, 95% CI 1.01-1.03; P<.001) and stimulants (aOR 1.03, 95% CI 1.01-1.04; P=.01). MSM had higher odds of engaging in substance use in all models (model 1: aOR 4.90, 95% CI 1.28-18.70; P=.02; model 2: aOR 5.47, 95% CI 1.43-20.87; P=.01; model 3: aOR 5.99, 95% CI 1.55-23.13; P=.009; and model 4: aOR 4.94, 95% CI 1.29-18.84; P=.01).

conclusionsInterventions for substance use should utilize evidenced-based approaches to reduce depression, negative affect, and cravings; increase self-esteem; and engage MSM. Interventions may also consider leveraging technology-based approaches to reduce substance use among populations who use crowdsourcing platforms.

Indexed as

AdultCrowdsourcingFemaleHomosexuality, MaleHumansInternetMalePsychologyRisk FactorsSubstance-Related DisordersTime FactorsUnited Statesaffectalcohol useAmazon Mechanical Turkcravingdepressionmen who have sex with menself-esteemstimulant use

Identifiers

PMID33904828
PMCPMC8114164
OpenAlexW3123483514

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.