Internalized Stigma Measurement in Substance Use Treatment Settings: A Narrative Review.

Stigma relating to substance use disorders is one of the many barriers to enrolling in substance use treatment. Stigma is also related to poorer substance use treatment outcomes, yet few studies of substance use and substance use treatment outcomes include measures of stigma. Stigma is a multi-level experience occurring as a result of discrimination within a systematic power structure promoting inequities among marginalized populations. Several domains of stigma are manifested among individuals seeking treatment for a substance use disorder, with internalized stigma being the most commonly measured. The current paper is a narrative review of measures that have been developed to measure internalized stigma related to substance use in treatment settings. Measures of stigma (n=8) in substance use treatment settings were identified using PubMed and PsycINFO databases. The review identified various strengths of existing measures, including a broad range of measures with mostly excellent internal consistency. The review also identified limitations including the general lack of consideration for multiple domains and intersecting forms of stigma, samples with limited racial and ethnic diversity, and the lack of assessments of polysubstance use. The development of measures of stigma that assess multiple domains of stigma and that are tested in a wide range of substance use treatment settings with racially and ethnically diverse participants is needed. This is of particular importance because stigma remains a crucial barrier to successful initiation and completion of substance use treatment.

Sociodemographic and Clinical Characteristics Associated With Worst Pain Intensity Among Cancer Patients.

AIMS: Patients with cancer have pain due to their cancer, the cancer treatment and other causes, and the pain intensity varies considerably between individuals. Additional research is needed to understand the factors associated with worst pain intensity. Our study aim was to determine the association between worst pain intensity and sociodemographics and cancerspecific factors among patients with cancer. DESIGN: A total of 1,280 patients with cancer recruited from multiple cancer centers over 25 years in the United States were asked to complete a questionnaire that collected respondents' demographic, chronic pain, and cancer-specific information. SETTINGS: Worst, least, and current pain intensities were captured using a modified McGill Pain Questionnaire (pain intensity measured on 0-10 scale). A generalized linear regression analysis was utilized to assess the associations between significant bivariate predictors and worst pain intensity scores.Our study sample was non-Hispanic White (64.5%), non-Hispanic Black (28.3%), and Hispanic (7.2%). On average, participants were 59.4 (standard deviation = 14.4) years old. The average worst pain intensity score was 6.6 (standard deviation = 2.50). After controlling for selected covariates, being Hispanic (ß = 0.6859), previous toothache pain (ß = 0.0960), headache pain (ß = 0.0549), and stomachache pain (ß = 0.0577) were positively associated with worse cancer pain. Notably, year of enrollment was not statistically associated with pain. CONCLUSIONS: Our study sample was non-Hispanic White (64.5%), non-Hispanic Black (28.3%), and Hispanic (7.2%). On average, participants were 59.4 (standard deviation = 14.4) years old. The average worst pain intensity score was 6.6 (standard deviation = 2.50). After controlling for selected covariates, being Hispanic (ß = 0.6859), previous toothache pain (ß = 0.0960), headache pain (ß = 0.0549), and stomachache pain (ß = 0.0577) were positively associated with worse cancer pain. Notably, year of enrollment was not statistically associated with pain. Findings identified being Hispanic and having previous severe toothache, stomachache, and headache pain as significant predictors of worst pain intensity among patients with cancer. After controlling for selected covariates, we did not note statistical differences in worst pain during a 25-year period. Therefore,studies focused on improving the management of pain among patients with cancer should target interventions for those with Hispanic heritage and those with past history of severe common pain.

Factors associated with current and severe pain among people living with HIV: results from a statewide sample.

BACKGROUND: People living with HIV (PLHIV) are more likely to suffer from pain compared to the general public. Pain often clusters with mental health symptoms and substance use. This study sought to evaluate mental health and substance use factors associated with any pain and severe pain intensities among PLHIV. METHODS: Data were derived from HIV+ adults (N = 733) recruited from community health centers across Florida who completed questionnaires regarding demographics, chronic pain, HIV clinical outcomes, mental health symptoms, and substance use information. Pain was assessed using the Brief Pain Inventory (BPI) short form. Multivariate logistic regression analysis was utilized to assess the relationship between selected covariates and pain. RESULTS: Approximately half (45.0%) of participants reported having any current pain while 16.1% reported severe pain. The odds of having any current pain were 2.49 (CI 95% 1.48, 4.18, p <  0.01) times greater among PLHIV reporting anxiety and 1.69 (CI 95% 1.11, 2.57, p = 0.01) times greater among PLHIV reporting PTSD compared to those without those factors. The odds of having severe pain were 2.03 (CI 95% 1.03, 4.01, p = 0.04) times greater among PLHIV reporting anxiety and 2.02 (CI 95% 1.26, 3.24, p <  0.01) times greater among female participants compared to PLHIV without those factors respectively. Factors including depression, alcohol consumption, and marijuana use were not statistically associated with any current pain nor with severe pain. CONCLUSION: The relationship between pain and mental health is complex. Thus, future research is needed to determine if pain treatments may reduce mental health symptoms or if treatments can be targeted to address both issues simultaneously.

The effects of self-efficacy in bifurcating the relationship of perceived benefit and cost with condom use among adolescents: A cusp catastrophe modeling analysis.

This study tested the complex relationship among the perceived benefit from and cost of condom use, self-efficacy and condom use among adolescents as a nonlinear dynamic process. Participants were 12th graders in public Bahamian high schools who reported having had sex and frequency of condom use. Results revealed that the perceived benefit and perceived cost as asymmetry variables were significantly associated with condom use (p < 0.001) after controlling for covariates. The association was bifurcated by the variable self-efficacy (p < 0.001). Furthermore, the cusp model was better than linear and logistic regression models in predicting the dynamic changes in condom use behavior, judged by the AIC and BIC, and R2 criteria. These results suggest that adolescent condom use may follow a nonlinear rather than linear dynamic process. Emphasizing bifurcation variables such as self-efficacy that promote sudden change could be essential to strengthen current evidence-based intervention programs in encouraging condom use.

Regression tree applications to studying alcohol-related problems among college students.

Machine learning algorithms hold promise for developing precision medicine approaches to addiction treatment yet have been used sparingly to identify predictors of alcohol-related problems. Recursive partitioning, a machine learning algorithm, can identify salient predictors and clinical cut points that can guide treatment. This study aimed to identify predictors and cut points of alcohol-related problems and to examine result stability in two separate, large data sets of college student drinkers (n = 5,090 and 2,808). Four regression trees were grown using the "rpart" package in R. Seventy-one predictors were classified as demographics (e.g., age), alcohol use indicators (e.g., typical quantity/frequency), or psychosocial indicators (e.g., anxiety). Predictors and cut points were extracted and used to manually recreate the tree in the other data set to test result stability. Outcome variables were alcohol-related problems as measured by the Alcohol Use Disorder Identification Test and Brief Young Adult Alcohol Consequences Questionnaire. Coping with depression, conformity motives, binge drinking frequency, typical/heaviest quantity, drunk frequency, serious harm reduction protective behavioral strategies, substance use, and psychosis symptoms best predicted alcohol-related problems across the four trees; coping with depression (cut point range: 1.83-2.17) and binge drinking frequency (cut point range: 1.5-2.5) were the most common splitting variables. Model fit indices suggest relatively stable results accounting for 17%-30% of the variance. Results suggest the nine salient predictors, particularly coping with depression motives scores around 2 and binge drinking frequency around two to three times per month, are important targets to consider when treating alcohol-related problems for college students. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A domain-oriented approach to characterizing movement-evoked pain.

Introduction: Movement-evoked pain (MEP) impacts a substantial proportion of US adults living with chronic pain. Evidence suggests that MEP is influenced by numerous biopsychosocial factors and mediated by mechanisms differing from those of spontaneous pain. However, both characteristic and mechanistic knowledge of MEP remain limited, hindering effective diagnosis and treatment. Objectives: We asked (1) can chronic pain, functional, psychosocial, and behavioral measures be grouped into descriptive domains that characterize MEP? and (2) what relationships exist between biopsychosocial factors across multiple domains of MEP? Methods: We formed 6 characteristic domains from 46 MEP-related variables in a secondary analysis of data from 178 individuals (aged 45-85 years) with knee pain. Ratings of pain during 3 functional activities (ie, Balance, Walking, Chair Stand) were used as primary MEP variables. Pearson correlations were calculated to show linear relationships between all individual domain variables. Relationships between variables were further investigated through weighted correlation network analysis. Results: We observed a unique combination of pain characteristics associated with MEP apart from general pain. Notably, minutes doing physical activity were inversely associated with multiple variables within 4 of the 6 domains. Weighted correlation network analysis largely supported our classification of MEP domains. Additional interdomain relationships were observed, with the strongest existing between MEP, Mechanical Pain, and Multiple Pain Characteristics and Symptoms. Additional relationships were observed both within and between other domains of the network. Conclusion: Our analyses bolster fundamental understanding of MEP by identifying relevant mechanistic domains and elucidating biopsychosocial and interdomain relationships.

A comprehensive examination of motivational profiles for alcohol-related behaviors among college students.

Recent research demonstrates unique relations of types of motivation for drinking responsibly based on self-determination theory and drinking motives with alcohol-related outcomes among college students. In the present study, we sought to extend prior research by using a person-centered approach to simultaneously consider types of motivation within and across these motivational constructs as well as their synergistic relations with alcohol-related outcomes. We used cross-sectional survey data from 2,808 college students at 10 universities in eight states across the United States who reported past-month alcohol use (Mage = 20.59, SD = 4.18; 72.9% female; 58.2% non-Hispanic White). A series of latent profile analyses were conducted using types of motivation for drinking responsibly and drinking motives as indicators. A five-profile solution was selected as optimal. Mean comparisons indicated that profiles defined by high endorsement of higher quality motivations for drinking responsibly (i.e., more self-determined) and low endorsement of drinking motives in combination were related to the most frequent protective behavioral strategies use, least alcohol use, and fewest negative alcohol-related consequences. Additionally, these profiles were higher on dispositional autonomy and psychological need satisfaction and lower on psychological need frustration. These findings provide initial insight into simultaneously considering motivational profiles for the interrelated behaviors of drinking responsibly and drinking that can be leveraged in college drinking interventions. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Early Birds and Night Owls: Distinguishing Profiles of Cannabis Use Habits by Use Times with Latent Class Analysis.

Background: Understanding, predicting, and reducing the harms associated with cannabis use is an important field of study. Timing (i.e., hour of day and day of week) of substance use is an established risk factor of severity of dependence. However, there has been little attention paid to morning use of cannabis and its associations with negative consequences. Objectives: The goal of the present study was to examine whether distinct classifications of cannabis use habits exist based on timing, and whether these classifications differ on cannabis use indicators, motives for using cannabis, use of protective behavioral strategies, and cannabis-related negative outcomes. Methods: Latent class analyses were conducted on four independent samples of college student cannabis users (Project MOST 1, N=2,056; Project MOST 2, N=1846; Project PSST, N=1,971; Project CABS, N=1,122). Results: Results determined that a 5-class solution best fit the data within each independent sample consisting of the classes: (1) "Daily-morning use",(2) "Daily-non-morning use", (3) "Weekend-morning use", (4) "Weekend-night use", and (5) "Weekend-evening use." Classes endorsing daily and/or morning use reported greater use, negative consequences and motives, while those endorsing weekend and/or non-morning use reported the most adaptive outcomes (i.e., reduced frequency/quantity of use, fewer consequences experienced, and fewer cannabis use disorder symptoms endorsed). Conclusions: Recreational daily use as well as morning use may be associated with greater negative consequences, and there is evidence that most college students who use cannabis do avoid these types of use. The results of the present study offer evidence that timing of cannabis use may be a pertinent factor in determining harms associated with use.

Using Decision Trees to Identify Salient Predictors of Cannabis-Related Outcomes.

Cannabis use continues to escalate among emerging adults and college attendance may be a risk factor for use. Severe cases of cannabis use can escalate to a cannabis use disorder, which is associated with worse psychosocial functioning. Predictors of cannabis use consequences and cannabis use disorder symptom severity have been identified; however, they typically employ a narrow set of predictors and rely on linear models. Machine learning is well suited for exploratory data analyses of high-dimensional data. This study applied decision tree learning to identify predictors of cannabis user status, negative cannabis-related consequences, and cannabis use disorder symptoms. Undergraduate college students (N = 7000) were recruited from nine universities in nine states across the U.S. Among the 7 trees, 24 splits created by 15 distinct predictors were identified. Consistent with prior research, one's beliefs about cannabis were strong predictors of user status. Negative reinforcement cannabis use motives were the most consistent predictors of cannabis use disorder symptoms, and past month cannabis use was the most consistent predictor of probable cannabis use disorder. Typical frequency of cannabis use was the only predictor of negative cannabis-related consequences. Our results demonstrate that decision trees are a useful methodological tool for identifying targets for future clinical research.

Individual and Community Social Determinants of Health and Recovery from Alcohol Use Disorder Three Years following Treatment.

Prior research on recovery from alcohol use disorder (AUD) has often focused on individual-level factors that promote recovery. Given systemic health inequities, it is also important to study community-level social determinants of health (SDOH) that may promote recovery from AUD. This study extended prior work examining individual profiles of recovery from AUD to assess how individual and community SDOH at the time of treatment entry were associated with recovery from AUD three years after treatment. Data were utilized from the COMBINE study (n = 664), a multisite randomized clinical trial evaluating pharmacological and behavioral treatments for AUD. Public community data sources associated with participants' study sites were used to measure community SDOH. Multilevel latent profile analyses with individual- and community-level variables as predictors of recovery profiles were estimated. Four profiles were identified based on participants' alcohol consumption and functioning. Individual SDOH variables, such as fewer years of education and lower income, and community SDOH, including lower rates of health insurance, lower income, and greater income inequality, were each associated with lower functioning profiles. The findings highlight the importance of community SDOH in AUD recovery and the value of including both individual and community SDOH variables in research on long-term recovery.

Reasons for Marijuana Use and Its Perceived Effectiveness in Therapeutic and Recreational Marijuana Users Among People Living with HIV in Florida.

Therapeutic and recreational marijuana use are common among people living with HIV (PLWH). However, the distinction between perceived "therapeutic" and "recreational" use is blurred, with little information about the specific reasons for use and perceived marijuana effectiveness in adults with chronic conditions. We aimed to compare reasons for use and reason-specific perceived marijuana effectiveness between therapeutic and recreational users among PLWH. In 2018-2019, 213 PLWH currently using marijuana (mean age 48 years, 59% male, 69% African American) completed a questionnaire assessing their specific reasons for using marijuana, including the "main reason." Participants were categorized into one of three motivation groups: therapeutic, recreational, or both equally. For each specific reason, participants rated marijuana effectiveness as 0-10, with 10 being the most effective. The mean effectiveness scores were compared across the three motivation groups via ANOVA, with p <0.05 considered statistically significant. The most frequent main reasons for marijuana use in the therapeutic (n=63, 37%), recreational (n=48, 28%), and both equally (n=59, 35%) categories were "Pain" (21%), "To get high" (32%), and "To relax" (20%), respectively. Compared to recreational users, therapeutic and both equally users provided significantly higher mean effectiveness scores for "Pain," and "To reduce anger." The "Both equally" group also provided significantly higher mean effectiveness scores for "To feel better in general," "To get high," and "To relax" compared to the other two categories. There is a significant overlap in self-reported reasons for marijuana use in primarily therapeutic or recreational users. Perceived marijuana effectiveness was lowest among recreational users.

A Mapping Literature Review of Medical Cannabis Clinical Outcomes and Quality of Evidence in Approved Conditions in the USA from 2016 to 2019.

In 2017, a National Academies of Sciences, Engineering, and Medicine (NASEM) report comprehensively evaluated the body of evidence regarding cannabis health effects through the year 2016. The objectives of this study are to identify and map the most recently (2016-2019) published literature across approved conditions for medical cannabis and to evaluate the quality of identified recent systematic reviews, published following the NASEM report. Following the literature search from 5 databases and consultation with experts, 11 conditions were identified for evidence compilation and evaluation: amyotrophic lateral sclerosis, autism, cancer, chronic noncancer pain, Crohn's disease, epilepsy, glaucoma, human immunodeficiency virus/AIDS, multiple sclerosis (MS), Parkinson's disease, and posttraumatic stress disorder. A total of 198 studies were included after screening for condition-specific relevance and after imposing the following exclusion criteria: preclinical focus, non-English language, abstracts only, editorials/commentary, case studies/series, and non-U.S. study setting. Data extracted from studies included: study design type, outcome definition, intervention definition, sample size, study setting, and reported effect size. Few completed randomized controlled trials (RCTs) were identified. Studies classified as systematic reviews were graded using the Assessing the Methodological Quality of Systematic Reviews-2 tool to evaluate the quality of evidence. Few high-quality systematic reviews were available for most conditions, with the exceptions of MS (9 of 9 graded moderate/high quality; evidence for 2/9 indicating cannabis improved outcomes; evidence for 7/9 indicating cannabis inconclusive), epilepsy (3 of 4 graded moderate/high quality; 3 indicating cannabis improved outcomes; 1 indicating cannabis inconclusive), and chronic noncancer pain (12 of 13 graded moderate/high quality; evidence for 7/13 indicating cannabis improved outcomes; evidence from 6/7 indicating cannabis inconclusive). Among RCTs, we identified few studies of substantial rigor and quality to contribute to the evidence base. However, there are some conditions for which significant evidence suggests that select dosage forms and routes of administration likely have favorable risk-benefit ratios (i.e., epilepsy and chronic noncancer pain). The body of evidence for medical cannabis requires more rigorous evaluation before consideration as a treatment option for many conditions, and evidence necessary to inform policy and treatment guidelines is currently insufficient for many conditions.

A risk score assessment tool for peripheral arterial disease in women: From the National Health and Nutrition Examination Survey.

BACKGROUND: Peripheral arterial disease (PAD) carries a significant morbidity and mortality. Women are more commonly affected with this condition and are mostly asymptomatic, and undertreated. The objective of the study was to develop and validate a simple risk score to identify women with PAD. HYPOTHESIS: Identifying those at early stage of the disease could help reduce the risk of complications. METHODS: Using data from the National Health and Nutrition Examination Survey 1999-2004, we identified women who had data on ankle brachial index. The cohort was divided into development (70%) and validation (30%) groups. Using variables that are self-reported or measured without laboratory data, we developed a multivariable logistic regression to predict PAD, which was evaluated in the validation cohort. RESULTS: A total of 150.6 million women were included. A diagnosis of PAD was reported in 13.7%. Age, body mass index, hypertension, diabetes mellitus, smoking, non-oral contraceptive pill usage, and parity were all independently associated with PAD. The C-statistics was 0.74, with good calibration. The model showed good stability in the validation cohort (C-statistics 0.73). CONCLUSION: This parsimonious risk model is a valid tool for risk prediction of PAD in women, and could be easily applied in routine clinical practice.