Perceptions of research risk and undue influence: Implications for ethics of research conducted with cocaine users

Cannabis Use Disorder Treatment Preferences: A Pilot Survey in Current Users of Cannabis

OBJECTIVES

Highly effective treatments for cannabis use disorder (CUD) are lacking, and patient preferences have not been considered during treatment development. We therefore conducted an exploratory crowdsourced survey of individuals reporting current cannabis use and a willingness to cut down or quit their cannabis use, to determine their interest in various treatment aspects.

METHODS

Subjects (n = 63) were queried about their willingness to take medications as a function of type, route, and regimen and to participate in adherence monitoring. Subjects were also asked about their willingness to engage in behavioral/psychosocial interventions as a function of type, setting, and duration. Measures theorized to be associated with treatment preferences were also collected, including cannabis use variables, readiness to change, reduction or cessation goal, perceived cessation barriers, and medication use beliefs and behaviors.

RESULTS

Survey responses indicated that efforts to develop CUD medications should focus on nonsynthetic compounds administered orally or by mouth spray no more than once per day to maximize patient acceptance. Remote adherence monitoring and one-on-one outpatient behavioral treatment approaches, especially contingency management, are also anticipated to enhance participation. Most subjects indicated a preference to reduce their cannabis use rather than quit.

CONCLUSIONS

These data provide guidance for the development of CUD interventions based on the preferences of individuals interested in treatment for their cannabis use. Additional research is needed to confirm these results in a larger sample and determine if matching CUD patients with their preferred treatments improves success rates.

Benzodiazepine Use and Dependence in Relation to Chronic Pain Intensity and Pain Catastrophizing

Benzodiazepines (BZDs), a class of sedative-hypnotic medications, generated concern as their popularity grew, with particular alarm regarding elevated rates of BZD use among chronic pain populations. Consistent with negative reinforcement/motivational models of substance use, desire for pain alleviation may motivate BZD use. Yet, little is known about relations between pain and addiction-relevant BZD use processes. This cross-sectional survey study aimed to: a) test associations between pain intensity and clinically relevant BZD use patterns, and b) examine the role of pain catastrophizing in hypothesized pain-BZD relations. Participants included 306 adults with chronic musculoskeletal pain and a current BZD prescription who completed an online survey study (Mage = 38.7, 38.9% female). Results indicated that pain intensity was positively associated with past-month BZD use frequency, BZD dependence severity, and likelihood of endorsing BZD misuse behaviors (ps < .05). Pain catastrophizing was positively associated with BZD dependence/likelihood of BZD misuse, covarying for pain intensity (P < .05). These findings build upon an emerging literature by highlighting positive covariation of pain intensity and pain catastrophizing with addiction-relevant BZD use behaviors. Results underscore the need to further investigate high-risk BZD use among individuals with chronic pain, with and without concurrent opioid use, to inform prevention/intervention efforts. PERSPECTIVE: This article presents findings on cross-sectional associations of pain intensity and pain catastrophizing with clinically relevant benzodiazepine (BZD) use outcomes, including dependence and misuse, among individuals with chronic pain. Findings help elucidate the higher burden of BZD misuse/dependence in chronic pain populations and suggest that pain relief may be a common, yet under recognized, self-reported motivation for taking BZDs.

Analysis of correlations between gut microbiota, stool short chain fatty acids, calprotectin and cardiometabolic risk factors in postmenopausal women with obesity: a cross-sectional study

BACKGROUND

Microbiota and its metabolites are known to regulate host metabolism. In cross-sectional study conducted in postmenopausal women we aimed to assess whether the microbiota, its metabolites and gut barrier integrity marker are correlated with cardiometabolic risk factors and if microbiota is different between obese and non-obese subjects.

METHODS

We analysed the faecal microbiota of 56 obese, postmenopausal women by means of 16S rRNA analysis. Stool short chain fatty acids, calprotectin and anthropometric, physiological and biochemical parameters were correlates to microbiome analyses.

RESULTS

Alpha-diversity was inversely correlated with lipopolysaccharide (Rho = - 0.43, FDR P (Q) = 0.004). Bray-Curtis distance based RDA revealed that visceral fat and waist circumference had a significant impact on metabolic potential (P = 0.003). Plasma glucose was positively correlated with the Coriobacteriaceae (Rho = 0.48, Q = 0.004) and its higher taxonomic ranks, up to phylum (Actinobacteria, Rho = 0.46, Q = 0.004). At the metabolic level, the strongest correlation was observed for the visceral fat (Q < 0.15), especially with the DENOVOPURINE2-PWY, PWY-841 and PWY0-162 pathways. Bacterial abundance was correlated with SCFAs, thus some microbiota-glucose relationships may be mediated by propionate, as indicated by the significant average causal mediation effect (ACME): Lachnospiraceae (ACME 1.25, 95%CI (0.10, 2.97), Firmicutes (ACME 1.28, 95%CI (0.23, 3.83)) and Tenericutes (ACME - 0.39, 95%CI (- 0.87, - 0.03)). There were significant differences in the distribution of phyla between this study and Qiita database (P < 0.0001).

CONCLUSIONS

Microbiota composition and metabolic potential are associated with some CMRF and fecal SCFAs concentration in obese postmenopausal women. There is no unequivocal relationship between fecal SCFAs and the marker of intestinal barrier integrity and CMRF. Further studies with appropriately matched control groups are warranted to look for causality between SCFAs and CMRF.

Differential impacts of economic and demographic variables on substance use patterns during the COVID-19 pandemic

Background: The COVID-19 pandemic and subsequent economic crisis has provided a unique opportunity to investigate the effects of economic shifts on substance use. Existing literature on this relationship is limited and conflicting, warranting further exploration.Objective: This study aimed to identify relationships between socioeconomic status (SES), demographic variables, and substance use patterns before and after government-mandated business closures due to COVID-19.Methods: Participants were recruited based on self-reported substance use through Amazon's Mechanical Turk (MTurk). Qualifying participants (N = 315, 43% female, mean age = 35.35) reported their substance use and SES for two-week periods before and after pandemic-related business closures. Regression models analyzed relationships between substance use and study variables.Results: Regression models found that, during COVID-19 closures, greater financial strain predicted decreased benzodiazepine (β = -1.12) and tobacco (β = 1.59) use. Additionally, certain predictor variables (e.g., participants' age [β = 1.22], race [β = -4.43], psychiatric disorders including ADHD [β = -2.73] and anxiety [β = 1.53], and concomitant substance use [β = 3.38]) predicted changes in substance use patterns; however, the directionality of these associations varied across substances.Conclusion: Specific substance use patterns were significantly and differentially impacted by economic strain, psychiatric diagnoses, and concomitant substance use. These results can help direct harm reduction efforts toward populations at greatest risk of harmful substance use following the pandemic.

A Brief Introduction to Human Behavioral Pharmacology: Methods, Design Considerations and Ethics

Human behavioral pharmacology methods have been used to rigorously evaluate the effects of a range of centrally acting drugs in humans under controlled conditions for decades. Methods like drug self-administration and drug discrimination have been adapted from nonhuman laboratory animal models. Because humans have the capacity to communicate verbally, self-report methods are also commonly used to understand drug effects. This perspective article provides an overview of these traditional human behavioral pharmacology methods and introduces some novel methodologies that have more recently been adapted for use in the field. Design (e.g., using placebo controls, testing multiple doses) and ethical (e.g., avoiding enrollment of individuals seeking treatment, determining capacity to consent) considerations that must be addressed when conducting these types of studies are also described.

The Association Between Fecal Short-Chain Fatty Acids, Gut Microbiota, and Visceral Fat in Monozygotic Twin Pairs

PURPOSE

To examine the association of short-chain fatty acids (SCFAs), gut microbiota and obesity in individual twins and to control for genetic and shared environmental effects by studying monozygotic intrapair differences.

PATIENTS AND METHODS

The study recruited 20 pairs of monozygotic twins. Body composition measurements were performed by using the multi-frequency bioelectrical impedance technique. SCFAs were extracted from feces and quantified by gas chromatography-mass spectrometer. Gut microbiota was evaluated by 16S rRNA gene sequencing.

RESULTS

Fecal SCFAs were negatively correlated with adiposity parameters including body mass index, visceral adipose tissue and waist circumference (all P < 0.05). Metastat analysis showed that the top 5 relatively abundant bacterial taxa of viscerally obese and non-obese groups were Bacteroides, Collinsella, Eubacterium rectale group, Lachnoclostridium, and Tyzzerella. Participants with visceral obesity had lower abundance of Bacteroides and Collinsella compared to non-obese patients (P < 0.05). Among them, the abundance of Collinsella was positively correlated with acetic acid concentrations (r = 0.63, P = 0.011). There were no significant intrapair differences in each SCFA concentrations between the twins in our study (P > 0.05).

CONCLUSION

Low fecal concentrations of SCFAs were associated with visceral obesity, and the gut microbiota might be involved in the underlying mechanism.

Assessing open science and citizen science in addictions and substance use research: A scoping review

BACKGROUND

The EU promotes 'Open Science' as a public good. Complementary to its implementation is Citizen Science, which redefines the relationship between the scientific community, civic society and the individual. Open Science and Citizen Science poses challenges for the substance use and addictions research community but may provide positive opportunities for future European addiction research. This paper explores both current barriers and potential facilitators for the implementation of Open Science and Citizen Science in substance use and addictions research.

METHODOLOGY

A scoping review was used to examine barriers and facilitators identified in the substance use and addiction research literature for the adoption of Open Science and Citizen Science.

RESULTS

'Technical' facilitators included the pre-registration of study protocols; publication of open-source datasets; open peer review and online tools. 'Motivational' facilitators included enhanced reputation; embracing co-creation; engaged citizenship and gamification. 'Economic' facilitators included the use of free tools and balanced remuneration of crowdworkers. 'Political' facilitators included better informed debates through the 'triple helix' approach and trust-generating transparency. 'Legal' facilitators included epidemiologically informed law enforcement; better policy surveillance and the validation of other datasets. 'Ethical' facilitators included the 'democratisation of science' and opportunities to explore new concepts of ethics in addiction research.

CONCLUSION

Open Science and Citizen Science in substance use and addictions research may provide a range of benefits in relation to the democratisation of science; transparency; efficiency and the reliability/validity of data. However, its implementation raises a range of research integrity and ethical issues that need be considered. These include issues related to participant recruitment; privacy; confidentiality; security; cost and industry involvement. Progressive journal policies to support Open Science practices; a shift in researcher norms; the use of free tools and the greater availability of methodological and ethical standards are likely to increase adoption in the field.

Researcher perspectives on including people who use drugs in clinical research

Background: People who use drugs are commonly excluded from clinical research despite being disproportionately impacted by numerous health conditions. Recent work indicates that community-recruited individuals report low support of research inclusion for persons reporting substance use.Objective: This study conducted a mixed-method assessment of researchers' attitudes on including persons reporting substance use in clinical research.Methods: Respondents (N = 168; 58% female; 58% psychologists) recruited via scientific society listservs and Twitter completed a survey containing two hypothetical research vignettes. Quantitative items evaluated respondents' endorsement of research participation by healthy adults, people who use drugs, and vulnerable populations. Qualitative items included open-ended questions asking reasons why people who use drugs should and should not participate in research.Results: Respondents reported significantly lower support for research participation by people who use drugs compared to healthy adults (p <.001). Open-ended responses concerning the inclusion of people who use drugs included themes relevant to the Belmont Principles (e.g., capacity to consent) and data quality (e.g., "bad data," poor compliance).Conclusion: Although lower support for research participation by people who use drugs was observed compared to healthy adults, the magnitude of this difference was smaller than reported for prior community-recruited respondents. These findings emphasize salient factors that may serve as both protections for and barriers to inclusion of people who use drugs in research. Initiatives including adoption of person-first language, addressing stereotyping of people who use drugs, and emphasizing the benefits of including these populations in clinical research should be explored to reduce bias while retaining needed protections.

Leveraging crowdsourcing methods to collect qualitative data in addiction science: Narratives of non-medical prescription opioid, heroin, and fentanyl use

BACKGROUND

Online crowdsourcing methods have proved useful for studies of diverse designs in the behavioral and addiction sciences. The remote and online setting of crowdsourcing research may provide easier access to unique participant populations and improved comfort for these participants in sharing sensitive health or behavioral information. To date, few studies have evaluated the use of qualitative research methods on crowdsourcing platforms and even fewer have evaluated the quality of data gathered. The purpose of the present analysis was to document the feasibility and validity of using crowdsourcing techniques for collecting qualitative data among people who use drugs.

METHODS

Participants (N = 60) with a history of non-medical prescription opioid use with transition to heroin or fentanyl use were recruited using Amazon Mechanical Turk (mTurk). A battery of qualitative questions was included indexing beliefs and behaviors surrounding opioid use, transition pathways to heroin and/or fentanyl use, and drug-related contacts with structural institutions (e.g., health care, criminal justice).

RESULTS

Qualitative data recruitment was feasible as evidenced by the rapid sampling of a relatively large number of participants from diverse geographic regions. Computerized text analysis indicated high ratings of authenticity for the provided narratives. These authenticity percentiles were higher than the average of general normative writing samples as well as than those collected in experimental settings.

CONCLUSIONS

These findings support the feasibility and quality of qualitative data collected in online settings, broadly, and crowdsourced settings, specifically. Future work among people who use drugs may leverage crowdsourcing methods and the access to hard-to-sample populations to complement existing studies in the human laboratory and clinic as well as those using other digital technology methods.

Evaluating non-medical prescription opioid demand using commodity purchase tasks: test-retest reliability and incremental validity

RATIONALE

Non-medical prescription opioid use and opioid use disorder (OUD) present a significant public health concern. Identifying behavioral mechanisms underlying OUD will assist in developing improved prevention and intervention approaches. Behavioral economic demand has been extensively evaluated as a measure of reinforcer valuation for alcohol and cigarettes, whereas prescription opioids have received comparatively little attention.

OBJECTIVES

Utilize a purchase task procedure to measure the incremental validity and test-retest reliability of opioid demand.

METHODS

Individuals reporting past year non-medical prescription opioid use were recruited using the crowdsourcing platform Amazon Mechanical Turk (mTurk). Participants completed an opioid purchase task as well as measures of cannabis demand, delay discounting, and self-reported pain. A 1-month follow-up was used to evaluate test-retest reliability.

RESULTS

More intense and inelastic opioid demand was associated with OUD and more intense cannabis demand was associated with cannabis use disorder. Multivariable models indicated that higher opioid intensity and steeper opioid delay discounting rates each significantly and uniquely predicted OUD. Increased opioid demand intensity, but not elasticity, was associated with higher self-reported pain, and no relationship was observed with perceived pain relief from opioids. Opioid demand showed acceptable-to-good test-retest reliability (e.g., intensity rxx = .75; elasticity rxx = .63). Temporal reliability was lower for cannabis demand (e.g., intensity rxx = .53; elasticity rxx = .58) and discounting rates (rxx = .42-.61).

CONCLUSIONS

Opioid demand was incrementally valid and test-retest reliable as measured by purchase tasks. These findings support behavioral economic demand as a clinically useful measure of drug valuation that is sensitive to individual difference variables.

Tobacco and cannabis co-use: Drug substitution, quit interest, and cessation preferences

The co-use of tobacco and cannabis is a common practice worldwide and carries with it substantial public health burden. Few interventions exist that target both substances and little is known about quit interest, treatment preferences, and drug substitution during past cessation attempts, which is critical to guide the development of treatment strategies. The goal of this study was to provide descriptive information regarding quit interest, treatment preferences, and perceived drug substitution among adult (age 18 +) cannabis-tobacco co-users. Participants (N = 282) from two independent survey samples (recruited from Amazon Mechanical Turk) from across the United States were combined. Among all participants, 57% were female, 79% were White, and average age was 33.31 (SD = 9.54) years old. Approximately 80% had tried to quit smoking cigarettes at least once, while 40% had tried to quit using cannabis at least once. Of those who tried to quit, 50% self-reported a perceived increase in their cannabis use during tobacco cessation and 62% self-reported a perceived increase in their tobacco use during cannabis cessation. Average quit interest (10-point scale) for cannabis was 2.39 (SD = 2.35) and for tobacco was 7.07 (SD = 2.90). Results of this study suggest that tobacco use should be addressed among cannabis-tobacco co-users, but interventions should consider lack of interest in cannabis cessation. Reduction-based strategies for cannabis use appear to be more acceptable to this nontreatment-seeking, co-using population. Drug substitution during quit attempts for one substance should be further explored as an important treatment consideration. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Waking Up from Dreamland: Opioid Addiction Precipitance and Support for Redistributive Drug Treatment

Motivated by the historical components of the ongoing U.S. opioid epidemic, this study examines how public support for redistributive drug treatment changes with awareness that someone's opioid addiction started with a legally acquired prescription. Using different versions of a vignette, we vary in a randomized design whether someone's addiction to painkillers started with a legally acquired prescription or with the decision to take pills from a friend. After reading the vignette, participants expressed their level of support for a policy that uses income redistribution to fund a program that provides the person in the vignette with drug treatment. We find that participants are less likely to support redistributive drug treatment when a prescription precipitates the addiction. The results imply that emphasizing the medical establishment's role in the opioid epidemic may actually make people less likely to favor using redistributive drug treatment to provide support.

Feasibility, Acceptability, and Initial Efficacy of Delivering Alcohol Use Cognitive Interventions via Crowdsourcing

BACKGROUND

Inhibitory control training and working memory training are 2 cognitive interventions that have been considered for alcohol use disorder (AUD). Existing studies have typically relied on small samples that preclude the evaluation of small effects. Crowdsourcing is a sampling method that can address these limitations by effectively and efficiently recruiting large samples with varying health histories. This study tested the feasibility and acceptability of delivering cognitive training interventions via crowdsourcing.

METHODS

Participants with AUD were recruited from the crowdsourcing website Amazon Mechanical Turk (mTurk) (ClinicalTrials.gov; NCT03438539). Following completion of a baseline survey, participants were randomized to an inhibitory control, working memory, or control training condition. Participants were asked to complete training tasks daily over a 2-week period. Follow-up assessments evaluating acceptability measures and alcohol and soda consumption were completed immediately following and 2 weeks after training.

RESULTS

Response rates were satisfactory over the 2-week intervention period (65% of training tasks completed), and performance on training tasks was consistent with expected effects. A majority of participants indicated that they were satisfied with the study procedures (94.6%), would participate again (97.4%), and would consider incorporating the training task in their daily life (81.1%). Modest reductions in alcohol consumption were observed (e.g., 0.5 drinking day/wk), primarily in the inhibitory control group, and these effects were selective to alcohol use and did not extend to soda consumption.

CONCLUSIONS

These findings demonstrate the feasibility and acceptability of utilizing crowdsourcing methods for interventions development. Such a demonstration helps establish the crowdsourcing setting for future large sample studies testing novel interventions for AUD and other substance use disorders.

Tobacco and cannabis co-use and interrelatedness among adults

Cannabis and tobacco co-use is prevalent, but consensus regarding the reasons for co-use among adults and the degree of interrelatedness between these substances is lacking. Reasons for co-use have been explored with younger users, but little data exists for more experienced users with entrenched patterns of co-use. The goal of this study was to examine characteristics and patterns of cannabis-tobacco co-use among adults in the Southeastern United States (US), where there is a legal landscape of generally restrictive cannabis legislation coupled with more permissive tobacco control compared to other US regions. Participants (N = 432) were regular cannabis users recruited through Amazon Mechanical Turk. Measures included demographics, patterns of cannabis and tobacco use, and reasons for co-use. Within this sample, 42% were current users of tobacco (n = 182). Cannabis-tobacco co-users were older and had more years of cannabis use than cannabis-only users. Among the co-using sub-sample, there was little consistency in the reasons for co-use, suggesting individual differences in the use of both substances. High levels of cannabis-tobacco interrelatedness (i.e., temporally concurrent use) were associated with smoking more cigarettes (tobacco) per day and greater nicotine dependence scores when compared to users with low levels of interrelatedness. Though these results are limited by a small sample size and generalizability issues, there were individual differences in cannabis-tobacco relatedness, which may be of importance when considering treatment strategies for cannabis, tobacco, or both. With additional research, personalized strategies adapted to cannabis-tobacco relatedness profiles among co-users may be warranted as a treatment strategy.

Medical Cannabis Use among Adults in the Southeastern United States

OBJECTIVES

To assess the self-reported reasons for medical cannabis use within the southeastern United States and compare recreational and medical cannabis users.

METHODS

This study was a cross-sectional survey administered in 2017 through Amazon's Mechanical Turk and enrolled 432 adult, regular cannabis users. Measures included demographics, cannabis use characteristics, and medical reasons for cannabis use.

RESULTS

Under half (47%) of respondents endorsed using cannabis for both medical and recreational reasons and 12% reported medical use only. The most commonly cited reasons for medical cannabis use were psychiatric and 60 unique medical conditions were listed. Recreational and medical users were similar on several measures of current use, but did vary in their use history, methods of use, and product knowledge.

CONCLUSIONS

Despite state laws and conclusive scientific evidence to support medical cannabis use for certain conditions, cannabis is still used frequently for a range of medical issues.

POLICY IMPLICATIONS

These data may assist healthcare providers in better understanding medical cannabis use in states with tightened restrictions and tailoring information to medical cannabis users about their specific conditions and prioritizing therapeutic options.

The impact of financial strain on medication non-adherence: Influence of psychiatric medication use

Non-adherence to prescribed medications is a systemic public health concern. Financial strain, the extent to which an individual is unable to afford necessary items, may represent an important factor related to adherence. This study evaluated the association between financial strain and medication adherence as a function of medication type. Participants reporting a daily prescription for psychiatric or other chronic health conditions (N = 231) were sampled from the crowdsourcing website Amazon Mechanical Turk (mTurk). All participants completed measures of financial strain and other individual-difference factors related to adherence. Medication adherence was evaluated using a subjective scale (i.e., ARMS) and past month non-adherence rates. General financial strain showed a modest relationship with subjective scales of adherence, but not past month non-adherence rates. Medication-specific financial strain was associated with greater non-adherence, even after controlling for relevant demographic, socio-economic, and personality factors. Medication-specific financial strain also disproportionately affected individuals taking psychiatric medications relative to those not taking psychiatric medications. These findings emphasize the role that financial strain plays in medication adherence, and in particular, in psychiatric conditions. Future studies could design interventions targeting financial strain to improve clinical adherence, broadly, and psychiatric medication adherence, specifically.

Association of exercise with smoking-related symptomatology, smoking behavior and impulsivity in men and women

INTRODUCTION

Despite extensive efforts to develop effective smoking cessation interventions, 70-85% of American cigarette smokers who quit relapse within one year. Exercise has shown promise as an intervention; however, many results have been equivocal. This study explored how exercise is associated with smoking-related symptomatology, smoking behavior and impulsivity in male and female smokers.

METHODS

Participants were recruited throughout the United States using the on-line crowdsourcing platform, Amazon's Mechanical Turk. They completed a survey with self-report measures assessing exercise, smoking-related symptomatology, smoking behavior and impulsivity. Differences between men and women were tested using t- and chi-square tests. Regression analyses tested for associations between exercise and smoking-related symptomatology, smoking behavior and impulsivity.

RESULTS

Participants (N = 604) were, on average, 32 (SD = 6.2) years old, mostly Caucasian, with at least some college education and approximately half were women. Women exercised slightly less than men and had more negative affect, craving, physical symptoms and withdrawal. Women smoked more cigarettes per day, had greater nicotine dependency and more years of smoking. Positive affect was positively associated with exercise for both men and women; however, this association was significantly stronger in women. Negative affect and withdrawal were inversely associated with exercise for women only. Impulsivity was inversely associated with exercise for both men and women.

CONCLUSION

Exercise was significantly associated with several smoking-related symptomatology, smoking behavior and impulsivity variables for both men and women, suggesting that exercise may be a useful intervention for smoking cessation. Future prospective research should determine how exercise directly impacts smoking cessation.

Mapping of Crowdsourcing in Health: Systematic Review

Background

Crowdsourcing involves obtaining ideas, needed services, or content by soliciting Web-based contributions from a crowd. The 4 types of crowdsourced tasks (problem solving, data processing, surveillance or monitoring, and surveying) can be applied in the 3 categories of health (promotion, research, and care).

Objective

This study aimed to map the different applications of crowdsourcing in health to assess the fields of health that are using crowdsourcing and the crowdsourced tasks used. We also describe the logistics of crowdsourcing and the characteristics of crowd workers.

Methods

MEDLINE, EMBASE, and ClinicalTrials.gov were searched for available reports from inception to March 30, 2016, with no restriction on language or publication status.

Results

We identified 202 relevant studies that used crowdsourcing, including 9 randomized controlled trials, of which only one had posted results at ClinicalTrials.gov. Crowdsourcing was used in health promotion (91/202, 45.0%), research (73/202, 36.1%), and care (38/202, 18.8%). The 4 most frequent areas of application were public health (67/202, 33.2%), psychiatry (32/202, 15.8%), surgery (22/202, 10.9%), and oncology (14/202, 6.9%). Half of the reports (99/202, 49.0%) referred to data processing, 34.6% (70/202) referred to surveying, 10.4% (21/202) referred to surveillance or monitoring, and 5.9% (12/202) referred to problem-solving. Labor market platforms (eg, Amazon Mechanical Turk) were used in most studies (190/202, 94%). The crowd workers’ characteristics were poorly reported, and crowdsourcing logistics were missing from two-thirds of the reports. When reported, the median size of the crowd was 424 (first and third quartiles: 167-802); crowd workers’ median age was 34 years (32-36). Crowd workers were mainly recruited nationally, particularly in the United States. For many studies (58.9%, 119/202), previous experience in crowdsourcing was required, and passing a qualification test or training was seldom needed (11.9% of studies; 24/202). For half of the studies, monetary incentives were mentioned, with mainly less than US $1 to perform the task. The time needed to perform the task was mostly less than 10 min (58.9% of studies; 119/202). Data quality validation was used in 54/202 studies (26.7%), mainly by attention check questions or by replicating the task with several crowd workers.

Conclusions

The use of crowdsourcing, which allows access to a large pool of participants as well as saving time in data collection, lowering costs, and speeding up innovations, is increasing in health promotion, research, and care. However, the description of crowdsourcing logistics and crowd workers’ characteristics is frequently missing in study reports and needs to be precisely reported to better interpret the study findings and replicate them.

Opioid use and stigma: The role of gender, language and precipitating events

The stigma of drug addiction is associated with negative perceptions and can be a barrier to treatment. With the rise in opioid overdose deaths, understanding stigmatizing attitudes towards individuals who use opioids is a crucial matter. There is a lack of opioid use research on stigma and, therefore, we aimed to discern stigmatizing attitudes towards people with opioid addiction. A randomized, between-subjects case vignette study (n = 2605) was conducted with a nation-wide online survey. Participants rated a hypothetical individual addicted to opioids on different dimensions of stigma after seeing one version of a vignette that varied by three conditions: 1) a male versus a female, 2) an individual labeled as being a "drug addict" versus having an "opioid use disorder" and 3) an individual whose use started by taking prescription opioids from a friend versus receiving a prescription from a doctor. Our results indicated that there were higher stigmatizing attitudes overall towards a male, an individual labeled as a "drug addict" and an individual who took prescription opioids from a friend. Interaction effects also showed that a female labeled with an "opioid use disorder" and male labeled as a "drug addict" were rated with higher stigma. The findings from our study are the first to show that information about gender, precipitating events and language matter when assessing stigma and opioid use and may affect the delivery of patient care.

To take or not to take: the association between perceived addiction risk, expected analgesic response and likelihood of trying novel pain relievers in self-identified chronic pain patients

BACKGROUND AND AIMS

Probability discounting refers to the effect of outcome uncertainty on decision making. Using probability discounting, we examined the degree to which self-identified chronic pain patients (CPP) were likely to try a novel analgesic medication given increasing addiction risk. We postulated that propensity for opioid misuse, trait impulsivity and previous opioid experience would be associated positively with likelihood of risky medication use.

DESIGN

This cross-sectional on-line study determined state/trait associations with addiction-related medication decisions in CPP.

SETTING

US-based CPP participated via Amazon Mechanical Turk; data were collected and analyzed in Baltimore, Maryland.

PARTICIPANTS

A total of 263 CPP (70.6% female) participated in the study from 12-13 December 2014.

MEASUREMENTS

CPP responded to the Benefit versus Addiction Risk Questionnaire (BARQ) assessing likelihood of taking a hypothetical once-daily oral analgesic medication as a function of two factors: risk of addiction (0-50%) and duration of expected complete pain relief (3, 30 or 365 days). The primary outcome was the BARQ, quantified as area under the curve (AUC). Grouping of CPP at high or low risk for opioid misuse was based on the Screener and Opioid Assessment for Patients with Pain-Revised (SOAPP-R). Predictors included previous experience with opioids, as well as various measures of chronic pain and mental health.

FINDINGS

Across hypothetical addiction risk assessed in the BARQ, the likelihood of taking a novel analgesic medication was elevated significantly in patients with high (≥18; n = 137) versus low (<18; n = 126) SOAPP-R scores [P < 0.001; 3-day: Cohen's d = 0.66, 95% confidence interval (CI) = 0.63, 0.69; 30-day: d = 0.74, 95% CI = 0.71, 0.78; 365-day: d = 0.75, 95% CI = 0.72, 0.79].

CONCLUSIONS

In the United States, self-identified chronic pain patients (CPP) at higher risk for opioid misuse were more likely to report willingness to try a novel analgesic despite increasing addiction risk than CPP with low risk of opioid misuse.

Randomized Controlled Trial of an Educational Intervention Using an Online Risk Calculator for Knee Osteoarthritis: Effect on Risk Perception

OBJECTIVE

Young adults, in general, are not aware of their risk of knee osteoarthritis (OA). Understanding risk and risk factors is critical to knee OA prevention. We tested the efficacy of a personalized risk calculator on accuracy of knee OA risk perception and willingness to change behaviors associated with knee OA risk factors.

METHODS

We conducted a randomized controlled trial of 375 subjects recruited using Amazon Mechanical Turk. Subjects were randomized to either use a personalized risk calculator based on demographic and risk-factor information (intervention), or to view general OA risk information (control). At baseline and after the intervention, subjects estimated their 10-year and lifetime risk of knee OA and responded to contemplation ladders measuring willingness to change diet, exercise, or weight-control behaviors.

RESULTS

Subjects in both arms had an estimated 3.6% 10-year and 25.3% lifetime chance of developing symptomatic knee OA. Both arms greatly overestimated knee OA risk at baseline, estimating a 10-year risk of 26.1% and a lifetime risk of 47.8%. After the intervention, risk calculator subjects' perceived 10-year risk decreased by 12.9 percentage points to 12.5% and perceived lifetime risk decreased by 19.5 percentage points to 28.1%. Control subjects' perceived risks remained unchanged. Risk calculator subjects were more likely to move to an action stage on the exercise contemplation ladder (relative risk 2.1). There was no difference between the groups for diet or weight-control ladders.

CONCLUSION

The risk calculator is a useful intervention for knee OA education and may motivate some exercise-related behavioral change.

Predictors of Adult E-Cigarette Users Vaporizing Cannabis Using E-Cigarettes and Vape-Pens

BACKGROUND

Given limited extant research, we assessed the use of portable, battery-powered cannabis vaporizers by adult e-cigarette users.

METHODS

522 adult vapers completed an online survey. Demographics; lifetime and past-month cannabis vaporization via e-cigarettes/vape-pens; preferences for hash oil, D-9-tetrahydrocannabinol (THC) wax, or dried buds; and cannabis vaporization beliefs and motives were examined. Demographics, age of e-cigarette onset, e-cigarette use frequency, state-level legal status of cannabis, cannabis vaping beliefs/motives, and impulsivity were examined as predictors of lifetime cannabis vaporization, past-month cannabis vaporization, and cannabis vaping frequency.

RESULTS

E-cigarette users reported lifetime (17.8%) and past-month (11.5%) cannabis vaporization. Vapers preferred hash oil (LT/PM 45.5/47.5%), THC wax (15.2/32.2%), and dried buds (39.4/35.6%). Motivations to vape cannabis included: it tastes better (39.3/37.9%), is healthier (42.9/39.7%), is easier to conceal/hide (35.7/46.6%), does not smell as strong (42.9/39.7%), is more convenient (42.9/27.6%), and produces a stronger/better high (58.1/40.7%) than smoking cannabis. Lifetime and past-month cannabis vaporization, respectively, were associated with initiating e-cigarette use at an earlier age (odds ratio (OR) = 0.09/0.88), being impulsive (OR = 2.25/3.23), having poor self-control (OR = 2.23/1.85), and vaporizing cannabis because it is easier to conceal/hide (OR = 2.45/2.48) or is more convenient than smoking cannabis (OR = 5.02/2.83). Frequency of vaping cannabis was associated with heavier e-cigarette use (η_p² = 0.10) and impulsivity (η_p² = 0.09).

CONCLUSIONS

Adult e-cigarette users are vaporizing cannabis using e-cigarettes/vape-pens. Efforts to curb cannabis vaporization may benefit from targeting impulsivity in users and regulating device features that facilitate or promote convenient, inconspicuous cannabis use.

Comparing exponential and exponentiated models of drug demand in cocaine users

Drug purchase tasks provide rapid and efficient measurement of drug demand. Zero values (i.e., prices with zero consumption) present a quantitative challenge when using exponential demand models that exponentiated models may resolve. We aimed to replicate and advance the utility of using an exponentiated model by demonstrating construct validity (i.e., association with real-world drug use) and generalizability across drug commodities. Participants (N = 40 cocaine-using adults) completed Cocaine, Alcohol, and Cigarette Purchase Tasks evaluating hypothetical consumption across changes in price. Exponentiated and exponential models were fit to these data using different treatments of zero consumption values, including retaining zeros or replacing them with 0.1, 0.01, or 0.001. Excellent model fits were observed with the exponentiated model. Means and precision fluctuated with different replacement values when using the exponential model but were consistent for the exponentiated model. The exponentiated model provided the strongest correlation between derived demand intensity (Q0) and self-reported free consumption in all instances (Cocaine r = .88; Alcohol r = .97; Cigarette r = .91). Cocaine demand elasticity was positively correlated with alcohol and cigarette elasticity. Exponentiated parameters were associated with real-world drug use (e.g., weekly cocaine use) whereas these correlations were less consistent for exponential parameters. Our findings show that selection of zero replacement values affects demand parameters and their association with drug-use outcomes when using the exponential model but not the exponentiated model. This work supports the adoption of the exponentiated demand model by replicating improved fit and consistency and demonstrating construct validity and generalizability. (PsycINFO Database Record

Differential sensitivity to learning from positive and negative outcomes in cocaine users

BACKGROUND

Altered sensitivity to positive and negative outcomes may be linked to the maladaptive choices characteristic of substance use disorders. Few studies have determined the distinct roles that positive and negative outcomes play in stimulus-response learning in cocaine users. The purpose of the present study was to investigate sensitivity to learning from positive and negative outcomes on a probabilistic learning task in cocaine users employing human laboratory and crowdsourcing techniques.

METHODS

Individuals who reported cocaine use were recruited for a laboratory study (Experiment 1) or an online study on Amazon.com's Mechanical Turk (mTurk) (Experiment 2). All participants completed a feedback-based probabilistic learning task in which images were classified into categories (A versus B). Positive and negative outcomes were provided in a probabilistic manner on separate trials. Proportion of optimal responses and response times were recorded.

RESULTS

Active cocaine users were less sensitive to learning from positive relative to negative outcomes. These effects were consistent across image type and session in the laboratory sample. Similarly, reduced sensitivity to learning from positive outcomes was observed in cocaine users on mTurk. Control participants did not show suboptimal performance following positive or negative outcomes.

CONCLUSIONS

This study extends the limited research on feedback-based learning in drug users by demonstrating reduced sensitivity to positive outcomes in cocaine users recruited in the human laboratory and online. Future studies on the clinical significance and mechanisms underlying this bias are needed to understand its relevance as a target for intervention development.