BACKGROUND
Substance use is a major public health problem and contributes substantially to the burden of disease among adults throughout the United States (US). To inform interventions, there is a need to identify the antecedents of substance use by collecting data in real-time using ecological momentary assessment (EMA). Also, crowdsourcing platforms like Amazon Mechanical Turk (MTurk) which leverage the internet to conduct research used in conjunction with EMA, may improve the scientific rigor of addiction science.
OBJECTIVE
We aimed to: 1) utilize EMA data and examine the temporal relationship between day-level cravings for alcohol and stimulants (e.g., cocaine, crack cocaine, and methamphetamine) and substance use (i.e., heavy drinking or any drug use) in a given day; and 2) assess whether depression, negative affect, and self-esteem measured at baseline predicted substance use in a given day, among participants recruited using MTurk.
METHODS
Adults in the US who reported alcohol or stimulant use (i.e., crack cocaine, cocaine, or methamphetamine) in the past year, were recruited using MTurk in 2018. Participants completed a baseline survey assessing socio-demographics, and psychosocial factors, and daily diaries assessing substance use, and cravings for alcohol and stimulants, online. Four multivariable random-intercept logistic regression models were built to examine psychosocial constructs separately along with other significant predictors from bivariate analyses, controlling for age and education.
RESULTS
Among a total of 272 participants, the average age was 36.1 (standard deviation [SD]=10.5), most (80.8%) were white and male (73.9%), and 65.3% were men who reported having sex with other men (MSM). At baseline, 63.8% engaged in any current or past hazardous alcohol consumption, 15.3% reported using cocaine, 10.1% reported using methamphetamine, 4.4% reported using crack cocaine, and 38.2% reported any non-injection or injection drug use in the past six months. On a scale from 0-100, median day-level cravings for alcohol, methamphetamine, cocaine and crack cocaine were; 5 (interquartile range [IQR]=0-26), 54 (IQR=20-88), 39 (IQR=1-71), and 52 (IQR=51-87), respectively. In multivariable analyses, factors independently associated with substance use in a given day were: higher baseline levels of depression (adjusted odds ratio [aOR]=1.11, 95% CI=1.02-1.21, P=0.01), and negative affect (aOR=1.08, 95% CI=1.01-1.16, P=0.01), lower levels of self-esteem (aOR=0.90, 95% CI=0.82-0.98, P=0.02), and greater day-level cravings for alcohol (aOR=1.02, 95% CI=1.01-1.03, P<0.001), and stimulants (aOR=1.03, 95% CI=1.01-1.04, P=0.01). Lastly, MSM had a higher odds of engaging in substance use in a given day in all final models: (aOR=4.90, 95% CI=1.28-18.70, p=0.02); (aOR=5.47, 95% CI=1.43-20.87, p=0.01); (aOR=5.99, 95% CI=1.55-23.13, p=0.009); and (aOR=4.94, 95% CI=1.29-18.84, p=0.01).
CONCLUSIONS
Substance use interventions should utilize evidenced-based approaches to reduce depression, negative affect, and cravings, increase self-esteem, and engage MSM. Interventions may also consider leveraging mobile health platforms to more effectively reduce substance use among populations who use crowdsourcing platforms.