Development of the Enthusiastic Substance Use Attitudes Scale: Preliminary Evidence of a Novel Maintenance Factor

Abstract

Background: Expectancies, motives, and attitudes toward substances are cognitive factors that partially account for substance use; however, existing measures tend to have monotonous phrasing, diverging from the enthusiastic attitude toward the perceived benefits of substance use exhibited by those who use substances regularly in informal settings. Objective: I aimed to characterize a new cognitive maintenance factor that precedes substance use by creating a brief, multidimensional measure to capture this tone nuance, which I called the Enthusiastic Substance Use Attitudes Scale (ESUAS). Method: Undergraduate students (n = 198) between ages 18 and 62 (M = 19.15, SD = 3.65; 66.2% women; 71.71% White) completed the study for course credit. Results: I used exploratory and confirmatory factor analyses to reduce a 90-item item pool based on a comprehensive qualitative thematic analysis of social media, traditional media, and the scientific literature to an 18-item hierarchical bifactor model. This model contained nine specific factors, which are (1) sociability, (2) enjoyment, (3) physical health, (4) mental health, (5) relaxation, (6) personal growth, (7) performance enhancement, (8) boredom, and (9) life processing; two general factors, which are (1) substance-induced emotion regulation and (2) substance-based assistance; and a higher-order single factor above the nine specific factors – resulting in twelve highly internally consistent, empirically supported scales. Further, the ESUAS demonstrated excellent structural, convergent, divergent, incremental, and diagnostic validity. The degree of enthusiasm towards substance use positively related to substance use disorder symptomology, polysubstance use, neuroticism, and difficulty with regulating emotions while negatively relating to one’s psychological quality of life and agreeableness. Conclusion: The ESUAS may be an effective tool for professionals to characterize these enthusiastic attitudes further and measure a more ecologically valid view of the perceived benefits of substance use among those who use substances, thereby developing a more compassionate, non-stigmatizing understanding within the general public, advancing medicinal uses of illicit substances, and improving conceptualizations and treatments.

Keywords:

• perceived benefits
• substance use
• substance use disorder
• enthusiastic attitude
• maintenance factor 

Consent for publication

I approved the submission and publication of the current manuscript.

Ethical approval

The Human Subjects Committee at Southern Illinois University approved this study. All participants read and agreed to an informed consent before participating.

Disclosure statement

I have no conflicts of interest or competing interests

Availability of data, code, and material

All data, syntax, and materials are freely available on the Open Science Framework website: https://doi.org/10.17605/OSF.IO/WKT9Y

Notes

1 The link provided here offer open access to the study materials. For specific questions about the materials or analyses, please contact the author at [email protected].

2 There was a tenth theme that I defined at this stage titled “coping,” which comprised individuals using substances to manage stressful life situations and unpleasant emotions, but I integrated this theme into the other themes due to high similarities and weak boundaries.

3 I still examined the results for poor loadings across items, but I did not encounter any.

4 I tested a three-level higher order model that was empirically underidentified and did not converge, so I removed it from the analyses.

5 Researchers may consider interpretations of the higher-order scores in the context of the nine single-domain scores, as models without the nine subfactors did not fit the data well.

6 Note that post-hoc power analyses for confirmatory factor analyses differ from correlational-based hypothesis testing. The excellent model fit greatly deflates power. A low observed power means that the data-model misspecification is so minor that one would need a very large sample to detect it. In this study, I would need a sample of over 900 participants to detect this misfit, which is an unnecessarily large sample size given the standards for assessing model fit and resources to conduct a study of that size. Data-model misfits this small are likely insignificant and negligible, so increasing the sample size to detect a misfit this small will likely result in a Type II error.

7 With the current sample size of 198, an a priori power analysis determined that these correlations must be greater than, r = .199, to reach 80% power, which is a small effect size for human-subjects medical research (Mukaka, 2012) and using empirically derived interpretations (Lovakov & Agadullina, 2021). The average power of the correlations, k = 32, that fall below this cut-off is 60%, with 53.1% for the weakest correlation, r = .14, Thus, although my chances of making a Type II error are higher among the very weak correlations, many of the most notable correlations (e.g., total score and DUDIT) having power well over 99.99%. Thus, I have a sufficient sample size for reasonably small correlations and to stabilize my estimates (Schönbrodt & Perugini, 2013).

8 It is not possible to determine causation, given that the data are cross-sectional. Thus, interpretations beyond a simple relationship are speculative and can go in either direction and other, unmeasured variables can affect this relationship.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article. An NIH training grant supported the author while working on this manuscript (NIDA T32DA007292 PI: Maher).