Association Between Workplace Absenteeism and Alcohol Use Disorder From the National Survey on Drug Use and Health, 2015-2019

Group based metacognitive therapy for alcohol use disorder: a pilot study

Introduction

Alcohol use disorder (AUD) is a severe clinical disorder, which has been associated with 5.3% of death worldwide. Although several treatments have been developed to improve AUD symptomatology, treatment effects were moderate, with a certain amount of patients displaying symptom deterioration after treatment termination. Moreover, outpatient treatment placements become increasingly scarce, thus necessitating more efficient treatment options. Therefore, the aim of the present study was to investigate the efficacy, feasibility, and acceptability of a newly invented, short, group based metacognitive therapy (MCT) for patients diagnosed with AUD.

Method

Seven patients were treated with eight sessions of group based MCT using a single case series design with an A-B replication across patients. Patients were assessed one month and one week before treatment, as well as one week and three months after treatment termination.

Results

Patients improved significantly and with large effect sizes regarding dysfunctional metacognitive beliefs, desire thinking/craving and depressive symptoms up to three months after treatment termination. AUD symptomatology as well as positive and negative metacognitive beliefs improved at post-treatment, but improvements could not be maintained at follow-up. All included patients completed the treatment and were highly satisfied.

Conclusion

The presented findings show preliminary evidence for the efficacy, feasibility, and acceptability of the implemented group based MCT treatment. Large scale randomized controlled trials (RCTs) are needed to confirm the effectiveness of the developed program for patients diagnosed with AUD.

Unmet need for alcohol use disorder treatment in reproductive-age females, with emphasis on pregnant and parenting populations in the United States: Findings from NSDUH 2015-2021

The negative effects of alcohol use can transmit intergenerational harm if alcohol use disorder (AUD) occurs during pregnancy and/or while parenting a child. Prenatal alcohol exposure is the leading preventable cause of congenital anomalies in the USA, and heavy drinking in women has been on the rise, further accelerated by the COVID-19 pandemic. This study describes the most recent patterns in the past year AUD prevalence and treatment among reproductive-aged women, with a specific focus on pregnant and parenting women, and barriers to treatment among those affected. We analyzed data on reproductive-age women from the National Survey on Drug Use and Health (2015-2021). We used generalized linear models to estimate prevalence ratios (PR) for past 12-month AUD and its treatment based on DSM-V criteria. We considered sociodemographic characteristics, including age, race/ethnicity, income, health insurance type, and arrest history. Pregnant and parenting women displayed lower risk for AUD (PR = 0.48, 95% CI:0.41-0.57; PR = 0.5 95% CI:0.48-0.54, respectively) relative to non-pregnant/non-parenting women. Excess risk for AUD was associated with education (some college vs. college graduates, PR = 1.07, 95% CI:1.01-1.13) and history of arrests (PR = 2.93, 95% CI:2.67-3.21). There were no clear differences in AUD treatment use based on parenting or pregnancy status. Among those with AUD, the prevalence of treatment was higher among individuals aged 35-49 years compared to those 18-25 years (PR = 1.6, 95% CI: 1.19-2.14) and in those enrolled in Medicaid vs. private insurance (PR = 2.62, 95%CI:1.97-3.47). Financial barriers and treatment not being a priority were the most frequently reported barriers to treatment. To promote well-being among parents and their children, healthcare providers should prioritize reproductive-age women at higher AUD risk. Decreasing the stigma attached to AUD and intensifying efforts to educate women about the dangers of AUD may improve treatment use among pregnant and parenting women.

On-call absences and academic recognition: A retrospective cohort analysis

BACKGROUND

Resident call schedules require careful planning and are vulnerable to unanticipated absences from unpredictable factors. We tested whether unplanned absences from resident call schedules were associated with the likelihood of subsequent academic recognition.

METHODS

We examined unplanned absences from call shifts for internal medicine residents at the University of Toronto from 2014 to 2022 (8 years). We identified institutional awards granted at the end of the academic year as an indicator of academic recognition. We defined the resident-year as the unit-of-analysis that started in July and ended in June of the subsequent year. Secondary analyses examined the association between unplanned absences and the likelihood of academic recognition in later years.

RESULTS

We identified 1668 resident-years of training in internal medicine. In total, 579 (35%) had an unplanned absence, and the remaining 1089 (65%) had no unplanned absence. Baseline characteristics were similar between the two groups of residents. In total, 301 awards were received for academic recognition. The likelihood of receiving an award at the end of the year was 31% lower for residents who had any unplanned absence compared with those who had no absence (adjusted odds ratio = 0.69, 95% confidence interval 0.51-0.93, p = 0.015). The likelihood of receiving an award was further decreased for residents with multiple unplanned absences compared with those with none (odds ratio 0.54, 95% confidence interval 0.33-0.83, p = 0.008). An absence during the first year of residency was not significantly associated with the likelihood of academic recognition in later years of training (odds ratio 0.62, 95% confidence interval 0.36-1.04, p = 0.081).

CONCLUSIONS

The results of this analysis suggest unplanned absences from scheduled call shifts may be associated with a decreased likelihood of academic recognition for internal medicine residents. This association could reflect countless confounders or the prevailing culture of medicine.

Prediction of Future Medical Costs by Modifiable Measures of Health

Introduction

Strategies to mitigate rising health-care costs are a priority for patients, employers, and health insurers. Yet gaps currently exist in whether health risk assessment can forecast medical claims costs. This study examined the ability of a health quotient (HQ) based on modifiable risk factors, age, sex, and chronic conditions to predict future medical claims spending.

Methods

The study included 18,695 employees and adult dependents who participated in health assessments and were enrolled in an employer-sponsored health plan. Linear mixed effect models stratified by chronic conditions and adjusted for age and sex were utilized to evaluate the relationship between the health quotient (score of 0-100) and future medical claims spending.

Results

Lower baseline health quotient was associated with higher medical claims cost over 2 years of follow up. For participants with chronic condition(s), costs were $3628 higher for those with a low health quotient (<73; N = 2673) compared to those with high health quotient (>85; N = 1045), after adjustment for age and sex (P value = 0.004). Each one-unit increase in health quotient was associated with a decrease of $154 (95% CI: 87.4, 220.3) in average yearly medical claims costs during follow up.

Discussion

This study used a large employee population with 2 years of follow-up data, which provides insights that are applicable to other large employers. Results of this analysis contribute to our ability to predict health-care costs using modifiable aspects of health, objective laboratory testing and chronic condition status.

Health check-ups as interventions for work disability management: supervisors and occupational healthcare follow the recommendations to a great extent

OBJECTIVES

Work disability management is a problem globally. This study was designed to find out whether the initiation, process and outcome of health check-ups (HCUs) follow the national legislation and whether supervisors and occupational healthcare (OHC) units act according to the legislation-based recommendations.

METHODS

Data of 1092 employees with reduced work ability were collected during 2013-2018 in 15 OHC units across Finland. Nine reasons for HCUs, eight process activities and three recommendations were analysed. Cross-tabulation and multinomial logistic regression analysis were used in the analyses.

RESULTS

Employees themselves initiated an HCU for early support more often (OR with 95% CI 2.37; 1.04 to 5.40) compared with supervisors. Personnel in OHC units initiated an HCU in musculoskeletal disorders more often (OR 1.58; 95% CI 1.05 to 2.37) and in mental disorders less often (OR 0.52; 95% CI 0.35 to 0.76) compared with supervisors. These findings were reflected in the recommendations after the HCU, where rehabilitation was recommended for employees with musculoskeletal disorders more often than for employees with mental disorders (ORs 5.48; 95% CI 1.91 to 15.67 and 1.59; 95% CI 0.74 to 3.43, respectively).

CONCLUSION

Supervisors and OHC units followed the recommendations for management of work disability to a great extent. Employees were active in looking for help early when they had problems with work ability. This positive finding should be promoted even more. OHC units did not initiate HCUs or recommend rehabilitation in mental disorders as actively as they did in musculoskeletal disorders. Support of employees with mental disorders should be improved and studied more. Registration of the study The study protocol was approved and registered on 22 September 2017 by the Doctoral Program of Health Sciences, Faculty of Medicine, University of Eastern Finland, registration no. 189067.

Common Laboratory Parameters Are Useful for Screening for Alcohol Use Disorder: Designing a Predictive Model Using Machine Learning

The diagnosis of alcohol use disorder (AUD) remains a difficult challenge, and some patients may not be adequately diagnosed. This study aims to identify an optimum combination of laboratory markers to detect alcohol consumption, using data science. An analytical observational study was conducted with 337 subjects (253 men and 83 women, with a mean age of 44 years (10.61 Standard Deviation (SD)). The first group included 204 participants being treated in the Addictive Behaviors Unit (ABU) from Albacete (Spain). They met the diagnostic criteria for AUD specified in the Diagnostic and Statistical Manual of mental disorders fifth edition (DSM-5). The second group included 133 blood donors (people with no risk of AUD), recruited by cross-section. All participants were also divided in two groups according to the WHO classification for risk of alcohol consumption in Spain, that is, males drinking more than 28 standard drink units (SDUs) or women drinking more than 17 SDUs. Medical history and laboratory markers were selected from our hospital's database. A correlation between alterations in laboratory markers and the amount of alcohol consumed was established. We then created three predicted models (with logistic regression, classification tree, and Bayesian network) to detect risk of alcohol consumption by using laboratory markers as predictive features. For the execution of the selection of variables and the creation and validation of predictive models, two tools were used: the scikit-learn library for Python, and the Weka application. The logistic regression model provided a maximum AUD prediction accuracy of 85.07%. Secondly, the classification tree provided a lower accuracy of 79.4%, but easier interpretation. Finally, the Naive Bayes network had an accuracy of 87.46%. The combination of several common biochemical markers and the use of data science can enhance detection of AUD, helping to prevent future medical complications derived from AUD.