Open AccessThe Psychosocial Predictors and Day-Level Correlates of Substance Use Among Participants Recruited via an Online Crowdsourcing Platform in the United States: Daily Diary Study
Author(s) -
Jennifer Jain,
Claudine Offer,
Christopher Rowe,
Caitlin Turner,
Carol Dawson-Rose,
Thomas J. Hoffmann,
Glenn-Milo Santos
Publication year - 2021
Publication title -
jmir public health and surveillance
Language(s) - English
Resource type - Journals
ISSN - 2369-2960
DOI - 10.2196/23872
Subject(s) - psychosocial , stimulant , psychological intervention , affect (linguistics) , medicine , logistic regression , psychiatry , clinical psychology , psychology , gerontology , communication
Background Alcohol 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. Objective We 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. Methods Individuals 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. Results Among 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). Conclusions Interventions 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.