A Review of Hot Deck Imputation for Survey Non-response

Race- and sex-specific differences in the risk of incident hearing loss and associated factors

This study reports the incidence of hearing loss and associated factors, and differences across sex and race groups. Participants were from a longitudinal community-based cohort study. Hearing loss was defined as a pure-tone average of thresholds at frequencies 0.5, 1.0, 2.0, and 4.0 kHz > 25 dB HL in the worse ear. We used Cox proportional hazards regression models to determine demographic and health-related factors associated with incident hearing loss, in the entire sample and across sex (male/female) and race (White/Black) groups, separately. This study included 754 participants without hearing loss at baseline (mean age 56.7 [SD 16.2] years; 67.6% female; 24.2% racial Minority [22.9% Black]), contributing 3,771 person years (PY). The incidence rate of hearing loss was 44.8 (95% CI 38.5, 52.1) per 1000 PY, and incidence increased with age. In age-adjusted models, older age (unadjusted), male sex, noise exposure, and > 5 to 15 smoking pack years were associated with incident hearing loss; associations with noise exposure and smoking pack years did not remain in age-sex adjusted models. Some factors associated with incident hearing loss varied across sex and race groups. Interventions to prevent or manage hearing loss, which is a common public health concern, may vary across demographic groups.

The Spector Job Satisfaction Survey: Associations of Satisfaction with Leaving EMS

OBJECTIVES

Detailed job satisfaction evaluations are often used to build strategies for employee retention. Despite recognizing that emergency medical services (EMS) dissatisfaction drives turnover, validated tools rigorously evaluating satisfaction have not been employed. We aim to assess the association between EMS clinician satisfaction and their likelihood of leaving the profession using the validated Spector Job Satisfaction Survey (JSS).

METHODS

We conducted a cross-sectional survey of nationally certified EMS clinicians in the United States recertifying between October 2022 and April 2023. Our primary outcome was the self-reported likelihood of leaving EMS within 12 months (likely or not likely to leave). The primary exposure was job satisfaction, assessed using the 36-item JSS, scored from 36 to 216, and analyzed in two models: total satisfaction (dissatisfied [scores 36-108], ambivalent [108-144], satisfied [144-216]), and satisfaction subscales (e.g., pay, promotion, supervision). We applied Least Absolute Shrinkage and Selection Operator (LASSO) regression to identify key predictors of intent to leave EMS, adjusting for demographic and agency characteristics. Post-LASSO Bayesian logistic regression estimated odds ratios (OR) and 95% credible intervals (CrI).

RESULTS

Among 33,414 EMS clinicians (response rate: 26.3%), the median age was 36 years (IQR: 29,46), 74.2% were male, and 83.0% were White, non-Hispanic. Most respondents worked full-time (77.6%), primarily as EMTs (48.5%), in urban settings (89.9%). Mean satisfaction scores were higher among those not likely to leave EMS (146.7 [standard deviation: 29.0]) than those likely to leave (121.2 [28.4]). Odds of leaving decreased for more satisfied clinicians: ambivalent clinicians [0.35 (0.32-0.38)]; satisfied clinicians [0.11 (0.10-0.13)]; referent dissatisfied. Additionally, specific satisfaction subscales were associated with lower odds of leaving for those satisfied compared to those dissatisfied, including nature of work [0.32 (0.28-0.37)], pay [0.46 (0.40-0.52)], promotion opportunities [0.53 (0.47-0.61)], supervision [0.65 (0.57-0.73)] and contingent rewards [0.77 (0.67-0.88)].

CONCLUSIONS

The EMS clinicians with higher satisfaction with their nature of work, pay, and promotion opportunities were less likely to report intent to leave. These findings highlight key factors that may inform workforce retention efforts.

Misclassification of second primary and recurrent breast cancer in the surveillance epidemiology and end results registry

The Surveillance Epidemiology and End Results (SEER) registry incorporates laterality, histology, latency, and topography to identify second primary breast cancers. Contralateral tumors are classified as second primaries, but ipsilaterals are subject to additional inclusion criteria that increase specificity but may induce biases. It is important to understand how classification methods affect accuracy of second tumor classification. We collected estrogen, progesterone, and human epidermal growth factor receptor 2 (ER, PR, Her2) status for 11,838 contralateral and 5,371 ipsilateral metachronous secondary tumors and estimated concordance odds ratios (cORs) to evaluate receptor dependence (the tendency for tumors to share receptor status) by laterality. If only second primaries are included, receptor dependence should be similar for contralateral and ipsilateral tumors. Thus, we compared ratios of cORs as a measure of inaccuracy. Cases who met ipsilateral second primary criteria were younger and had less aggressive primary tumor characteristics compared to contralateral tumors. Time to secondary tumors was (by definition) longer for ipsilaterals than contralaterals, especially among ER + primaries. Overall and in multiple strata, ipsilateral tumors showed higher receptor dependence than contralateral tumors (ratios of cORs > 1), suggesting some SEER-included ipsilaterals are recurrences. SEER multiple primary criteria increase specificity, but remain inaccurate and may lack sensitivity. The dearth of early occurring ipsilateral tumors (by definition), coupled with high observed receptor dependence among ipsilaterals, suggests important inaccuracies. Datasets that allow comparison of pathologist- and SEER-classification to true multi-marker genomic dependence are needed to understand inaccuracies induced by SEER definitions.

Genomic Selection for Pea Grain Yield and Protein Content in Italian Environments for Target and Non-Target Genetic Bases

Enhanced pea cultivation, which can increase the sustainability of European agriculture, requires better-performing cultivars. This study investigated the genomic selection (GS) ability to predict grain yield, protein content, and protein yield on the same or a different genetic base (target/non-target GB) relative to that employed for model training. GS models were developed on 276 lines from three Recombinant Inbred Line (RIL) populations evaluated in three Italian autumn-sown environments using 5537 SNPs from genotyping by sequencing. Validation in two cropping years concerned 108 independent lines from five RIL populations, of which two belonged to the GS training set, and three shared one parent each with training populations. A genome-wide association study performed on the GS training set using 18,674 SNPs highlighted the polygenic control of protein content and grain yield, with several environment-dependent QTLs for yield. Intermediate/high predictive ability within or across populations emerged for all traits in the target GB (0.359-0.675), with some variation depending on the population. Predictive ability in the non-target GB was modest/intermediate for protein content, and null/poor for the other traits. No inverse correlation emerged between grain yield and protein content. GS proved useful for all traits in the target GB and for protein content in a non-target GB.

Developing a National Longitudinal Tobacco Cohort of Youth and Young Adults: The Tobacco Epidemic Evaluation Network (TEEN+) Study

INTRODUCTION

Timely and relevant data are critical to monitoring the rapidly changing youth vaping epidemic and for understanding the prevalence, patterns of use, knowledge, and perceptions of tobacco products. While e-cigarettes have been the most used tobacco product among youth for nearly a decade, new nicotine delivery products continue to be introduced to the US market. Flavored tobacco products, including flavored e-cigarettes, menthol cigarettes, and flavored cigars, drive disparities in use by young people.

AIMS AND METHODS

To examine tobacco use among youth and young adults, the Monitoring E-Cigarette Use among Youth project established a longitudinal cohort of youth and young adults (13-24)-the Tobacco Epidemic Evaluation Network (TEEN+) study. TEEN+ focuses on e-cigarette and other tobacco products use and also includes questions about other substance use (eg, marijuana, alcohol), physical health, mental health, and social determinants of health (eg, discrimination, poverty, sexual and gender identity). Geocoding of responses allows for the evaluation of local tobacco control policies. The cohort includes an oversample of California residents to generate reliable and representative state-level estimates. This manuscript provides an overview of methods and baseline demographics from Wave 1.

RESULTS

The initial Wave 1 TEEN+ cohort included 10 255 in the national sample and 2761 in the California sample.

CONCLUSIONS

TEEN+ study data complement nationally-representative cross-sectional studies and allow for rapid evaluation of local and state policies. This manuscript describes the study's probability-based sample recruitment. Furthermore, we identify this initiative as a resource for evaluating the impact of flavored tobacco restriction policies and informing policy implementation efforts.

IMPLICATIONS

This manuscript provides an overview of the methodology and baseline characteristics for a new longitudinal cohort of youth and young adults, the Tobacco Epidemic Evaluation Network (TEEN+) study. The TEEN+ study data can be used to evaluate the impact of flavored tobacco product restriction policies and informing policy implementation efforts.

Prospective Association of Sedentary Behavior With Psychological Distress Among Adolescents

PURPOSE

To analyze the associations of different types and contexts of sedentary behavior during mid-adolescence (14 years) with later psychological distress (at 17 years).

METHODS

The data include 3,675 adolescents from the Millennium Cohort Study. During mid-adolescence, participants completed a time-use diary reporting time in different sedentary activities, which were also categorized into broader contexts (i.e., Leisure-based screen-time, leisure-based nonscreen time, and educational sedentary behavior). Participants reported psychological distress at the 17-year wave, through the Kessler scale. Gender, parent's education, family net income, parent's psychological distress, body mass index, physical activity, total sedentary time (time-use diary), depressive symptoms, and bullying victimization, all assessed during mid-adolescence, were used as covariates. Interaction terms were included to assess the effect-modification of gender.

RESULTS

Increasing 1 hour of playing video games, reading for leisure and total leisure-based screen-time was prospectively associated with a 3% (risk ratio: 1.03; 1.01-1.04), 5% (1.05; 1.01-1.08) and 2% (1.02; 1.01-1.03) higher psychological distress respectively. Only the groups with more than 180 min/day of leisure-based screen time were associated with higher psychological distress (180-300 min/day: 1.08; 95% confidence interval: 1.00-1.17. 300+ min/d: 1.13; 95% confidence interval: 1.03-1.23). Similarly, only higher levels of reading for leisure and playing video games were associated with higher psychological distress. Moderate (60-119 min) durations of homework (0.92; 0.86-0.99) and higher durations attending class (0.94; 0.89-0.99) were associated with lower psychological distress. There were only minor gender interactions.

DISCUSSION

Among adolescents, the association between sedentary behavior and psychological distress is domain-dependent. Future interventions should focus on reducing leisure-time screen-based behaviors to less than 3 h/day.

Challenge of missing data in observational studies: investigating cross-sectional imputation methods for assessing disease activity in axial spondyloarthritis

OBJECTIVES

We aimed to compare various methods for imputing disease activity in longitudinally collected observational data of patients with axial spondyloarthritis (axSpA).

METHODS

We conducted a simulation study on data from 8583 axSpA patients from ten European registries. Disease activity was assessed by the Axial Spondyloarthritis Disease Activity Score (ASDAS) and the corresponding low disease activity (LDA; ASDAS<2.1) state at baseline, 6 and 12 months. We focused on cross-sectional methods which impute missing values of an individual at a particular time point based on the available information from other individuals at that time point. We applied nine single and five multiple imputation methods, covering mean, regression and hot deck methods. The performance of each imputation method was evaluated via relative bias and coverage of 95% confidence intervals for the mean ASDAS and the derived proportion of patients in LDA.

RESULTS

Hot deck imputation methods outperformed mean and regression methods, particularly when assessing LDA. Multiple imputation procedures provided better coverage than the corresponding single imputation ones. However, none of the evaluated methods produced unbiased estimates with adequate coverage across all time points, with performance for missing baseline data being worse than for missing follow-up data. Predictive mean and weighted predictive mean hot deck imputation procedures consistently provided results with low bias.

CONCLUSIONS

This study contributes to the available methods for imputing disease activity in observational research. Hot deck imputation using predictive mean matching exhibited the highest robustness and is thus our suggested approach.

Cumulative Incidence of Mortality Associated with Cardiovascular-Kidney-Metabolic (CKM) Syndrome

Key Points

Background

It is imperative to critically evaluate the prognostic implications of cardiovascular–kidney–metabolic (CKM) syndrome staging to inform clinical practice. The primary aims of this study were to define the risk of mortality associated with each CKM syndrome stage and to determine the corresponding restricted mean survival time over a 15-year period.

Methods

This was a longitudinal study of 50,678 community-dwelling US adults aged 20 years and older with baseline data for CKM stage determination participating in the 1999–2018 National Health and Nutrition Examination Survey. CKM stages were defined according to the American Heart Association presidential advisory. Fifteen-year adjusted cumulative incidences of cardiovascular mortality were calculated for each stage from confounder-adjusted survival curves using the G-formula.

Results

Over a median 9.5-year follow-up, 2564 participants experienced cardiovascular death. The 15-year adjusted cumulative incidences of cardiovascular mortality were stage 0, 5.5% (95% confidence interval [CI], 1.8 to 9.3); stage 1, 5.7% (95% CI, 3.2 to 8.2); stage 2, 7.9% (95% CI, 6.8 to 9.1); stage 3, 8.7% (95% CI, 6.7 to 10.8); and stage 4, 15.2% (95% CI, 13.6 to 16.8). The absolute risk difference between CKM stage 4 and stage 0 at 15 years was 9.6% (95% CI, 5.6 to 13.6). The survival difference between CKM stage 0 and stage 4 at 15 years was 8.1 (95% CI, 8.0 to 8.2) months.

Conclusions

Our findings reveal a graded risk of cardiovascular mortality associated with higher CKM syndrome stage.

D-MGDCN-CLSTM: A Traffic Prediction Model Based on Multi-Graph Gated Convolution and Convolutional Long-Short-Term Memory

Real-time and accurate traffic forecasting aids in traffic planning and design and helps to alleviate congestion. Addressing the negative impacts of partial data loss in traffic forecasting, and the challenge of simultaneously capturing short-term fluctuations and long-term trends, this paper presents a traffic forecasting model, D-MGDCN-CLSTM, based on Multi-Graph Gated Dilated Convolution and Conv-LSTM. The model uses the DTWN algorithm to fill in missing data. To better capture the dual characteristics of short-term fluctuations and long-term trends in traffic, the model employs the DWT for multi-scale decomposition to obtain approximation and detail coefficients. The Conv-LSTM processes the approximation coefficients to capture the long-term characteristics of the time series, while the multiple layers of the MGDCN process the detail coefficients to capture short-term fluctuations. The outputs of the two branches are then merged to produce the forecast results. The model is tested against 10 algorithms using the PeMSD7(M) and PeMSD7(L) datasets, improving MAE, RMSE, and ACC by an average of 1.38% and 13.89%, 1% and 1.24%, and 5.92% and 1%, respectively. Ablation experiments, parameter impact analysis, and visual analysis all demonstrate the superiority of our decompositional approach in handling the dual characteristics of traffic data.

Predictors of self-reported hypertension among women of reproductive age in North Dakota

BACKGROUND

Understanding the risk factors of hypertension among women of reproductive age (18-44 years) is important for guiding health programs aimed at reducing the burden of hypertensive disorders in this population. Therefore, the objective of this study was to investigate predictors of self-reported hypertension among women of reproductive age in North Dakota.

METHODS

Behavioral Risk Factor Surveillance System data for the years 2017, 2019, and 2021 were obtained from North Dakota Department of Health and Human Services. A conceptual model was used to identify potential predictors of hypertension including sociodemographic characteristics, behavioral factors, chronic health conditions, and healthcare access. A multivariable binary logistic regression model was then used to identify significant predictors of hypertension. The predictive ability of the final model was assessed using a Receiver Operating Characteristic (ROC) curve and area under the curve (AUC).

RESULTS

The odds of hypertension were significantly higher among women of reproductive age who reported frequent mental distress (odds ratio [OR] = 2.0, 95% confidence interval [CI] = 1.3-3.3), resided in a primary care health professional shortage area (OR = 1.8, 95% CI = 1.2-2.6), were obese (OR = 2.6, 95% CI = 1.7-4.1) and were 35-44 years old (OR = 2.3, 95% CI = 1.6-3.4), relative to their counterparts who did not have frequent mental distress, did not reside in a health professional shortage area, had a normal body mass index, and were 18-34 years old, respectively. Additionally, the odds of hypertension were lower among women who did not have a checkup within the last year compared to those who did have a checkup within the last year (OR = 0.6, 95% CI = 0.4-0.9). The AUC of the final model was 0.68.

CONCLUSIONS

There is evidence that frequent mental distress and disparities in healthcare access or utilization are predictors of hypertension among women of reproductive age in North Dakota. Further research is warranted to determine whether improved mental health can reduce the risk of hypertension in this population. Public health officials may consider promoting hypertension awareness and control programs in areas with limited access to healthcare professionals.

No Evidence on Association Between Prospective Exposure to Out-of-Pocket Cost Information and Appointment Cancelations or No-Shows: A Case-Control Pilot Study

Health care price transparency aims to empower patients to make better-informed purchasing decisions. However, the prospective availability of patients' out-of-pocket costs may lead to an increased rate of forgone care. The objective of this study was to examine whether obtaining a prospective out-of-pocket cost estimate is associated with the likelihood of canceling or not arriving at a scheduled outpatient health care appointment. We surveyed adult individuals with scheduled outpatient imaging appointments at a large health care system in Georgia. In this case-control pilot study, we estimated the adjusted association between obtaining an out-of-pocket cost estimate for a scheduled imaging appointment (did not obtain an estimate, did not seek an estimate but received it via an unsolicited phone call from the health care system, and actively sought and obtained an estimate) and not attending the appointment using multivariable logistic regression that controlled for the type of primary health insurance and patient demographics. Actively seeking an out-of-pocket cost estimate was not associated with appointment cancelation or no-show (adjusted odds ratio [aOR] = 0.81, P = .75). Passively receiving an out-of-pocket cost estimate via an unsolicited phone call from the health care system was marginally associated with lower odds of appointment cancelation or no-show (aOR = 0.24; P = .076). This study did not find evidence of an association between prospective exposure of patients to out-of-pocket cost information and the likelihood of health care appointment cancelation or no-show.

Evaluating Ovarian Cancer Risk-Reducing Salpingectomy Acceptance: A Survey

SIGNIFICANCE

This study found that many participants were willing to consider RRS to prevent ovarian cancer. Further research on RRS should be undertaken to understand how this can be best used for ovarian cancer prevention.

Peripheral magnetic stimulation for the treatment of fibromyalgia: a systematic review and meta-analysis

OBJECTIVES

To systematically review and conduct a meta-analysis of studies on peripheral magnetic stimulation (PMS) for fibromyalgia (FM) treatment.

METHODS

MEDLINE, EMBASE, CENTRAL, CINHAL, Web of Science, and ProQuest databases were searched from inception to July 2023 for studies in adult patients with FM treated with PMS. Studies using transcranial magnetic stimulation were excluded.

RESULTS

Six randomized controlled trials (RCTs) (n = 279 patients) were identified and included in the review. PMS regimens varied, ranging from 8 to 40 min per session over 3-84 days. All studies compared PMS to a visually and physically identical sham device without magnetic fields. Most of the included studies demonstrated positive findings for PMS on pain and functional outcomes. In our meta-analysis, PMS significantly reduced pain scores within 1-3 months (mean difference -1.86 on NRS, 95% confidence interval -2.85 to -0.87, p = 0.0002, I2 = 68%, 4 studies [154 participants], low quality of evidence), but not at ≥3 months (low quality of evidence). Minimal adverse effects were reported.

DISCUSSION

Evidence for PMS use in FM is encouraging for short-term benefit. However, heterogeneous patient populations, varied PMS regimens, and limited number of studies are important limitations. Large, high-quality RCTs are needed to confirm PMS benefits and to make definitive recommendations.

PROTOCOL REGISTRATION

PROSPERO Identifier is CRD42021235164.

Student perceptions of U.S. based school day physical activity best practices in relation to accelerometer-based sedentary behavior and activity

Objective

To examine associations between student perceptions of school physical activity best practices and accelerometer-based physical activity during school days.

Methods

The sample was 758 students in grades 3rd-4th or 6th-7th (female-58 %; 31 % Black/African American) from 33 schools across five school districts in a Mid-Atlantic state in the U.S. Students completed the Perceptions of the Environment at School survey to assess perceived implementation of 11 school physical activity best practices and wore an Actical ankle accelerometer for 7 days between 2017 and 2019. Accelerometer cutpoints were applied for percent time in sedentary, light, and moderate-vigorous physical activity (MVPA) during school hours. Adjusted mixed effects linear regression models were used to predict percent time in each physical activity category, with separate models for elementary and middle school.

Results

More best practices were perceived by elementary versus middle schoolers (sum score = 3.3 versus 1.5, p < .01). For every additional best practice perceived, elementary schoolers spent 0.64 % less time in sedentary behavior (B = -0.62; SE = 0.27, p = .02), equivalent to ∼12 fewer minutes/week in sedentary behaviors, and 0.58 % more time in light activity (B = 0.58; SE = 0.25, p = .02; ∼10 more minutes/week). No associations observed for middle schoolers or MVPA.

Conclusions

Few best practices were perceived as being implemented in school. Elementary schoolers who perceived more best practices spent more time in light activity and less in sedentary behavior, but this relationship was not found among middle schoolers. Future research should promote implementation of school physical activity best practices and examine the linkage between implementation, student perceptions, and behavior change.Trial Registration: Clinical Trials, NCT03432715; Registered on 02/2/2018.

Baseline Estimates for Companion Animals Living in Households in Hawai'i: Associated Socio-Demographic, and Select Health Variables, as Measured by a Household Survey

Information on companion animals in Hawai'i is lacking. The Hawai'i Department of Health's Hawai'i Health Survey, collected data on adults and households by telephone interview. National estimates of companion animals range from 50-67%. However, the estimate from Hawai'i was lower with 39% of households in Hawai'i having a companion animal that spends part or all of the day indoors, including 29.5% of households with dogs and 14.7% with cats. There may be multiple reasons the count is lower for Hawai'i and possible factors are identified. There were significant differences in companion animals by ethnicity with Whites having the highest percentage of cats (25.8%) and Japanese the highest percentage of dogs (33.8%). Differences were observed between Asian ethnicities and Native Hawaiians. Specifically, individuals of Japanese ethnicity were more likely to have dogs, while Native Hawaiians were more likely to have cats compared to other Asian and Other Pacific Island ethnicities. Furthermore, companion animals were associated with counties other than Honolulu, lower poverty, ownership of a car or home, women, education, and middle-aged adults. Thus, many households in Hawai'i may not have the resources for a companion animal. Adults who rated their general health excellent had the highest association with having a cat(s). Asthma was higher for women living with dogs than women without cats or dogs. Asthma was lowest for men with cats compared to other groups for men and women. This study contributes to the understanding of complex interrelationships of humans, animals, and their environment which is gaining momentum under the umbrella of "One Health" by supporting increased collaboration and new data sources.

Applying machine learning-based multiple imputation methods to nonparametric multiple comparisons in longitudinal clinical studies

Dependent samples, in which repeated measurements are made on the same subjects, eliminate potential differences among the subjects. In k-dependent samples, missing data can occur for various reasons. The Skillings-Mack test is used instead of the Friedman test for k-dependent samples with missing observations that are non-normally distributed. If a significant difference exists among groups, nonparametric multiple comparisons need to be performed. In this study, we propose an innovative approach by applying four methods to nonparametric multiple comparisons of incomplete k-dependent samples that are non-normally distributed. The four methods are two nonparametric multiple imputation methods based on machine learning (multiple imputations by chained equations utilizing classification and regression trees (MICE-CART) and random forest (MICE-RF)), one nonparametric imputation method (random hot deck imputation), and the listwise deletion method. We compare the four methods under two missing data mechanisms, four correlation coefficients, two sample sizes, and three percentages of missingness. After implementing different scenarios in a simulation study, the listwise deletion method is inferior to the other methods. MICE-CART and MICE-RF are superior to the other methods for moderate and small sample sizes with well-controlled type 1 error. The two nonparametric multiple imputation methods based on machine learning can be applied to nonparametric multiple comparisons. Therefore, we propose machine learning-based multiple imputation methods for nonparametric multiple comparisons of k-dependent samples with missing observations. The approach was also illustrated with a longitudinal dentistry clinical trial.

Heterogeneity in the consumption of fresh and ultra-processed foods by the Brazilian population ≥10 years of age

OBJECTIVE

To evaluate the heterogeneity in the consumption of fresh or minimally processed foods (FMPF) and ultra-processed foods (UPF) in the Brazilian population ≥10 years of age.

METHODS

Cross-sectional study that used data from the food consumption and resident module from the 2017-2018 edition of the Family Budget Survey. Variables relating to sex, region of residence, household status and per capita family income in minimum wages were used. The outcomes were dietary participation in percentage of FMPF and UPF. Heterogeneity was assessed using random effects produced by linear mixed-effects models.

RESULTS

Thirty-two random effects were obtained for the consumption of FMPF and 34 for UPF. Living in the urban area of the South and Southeast regions, as well as having a higher income were driving factors in the consumption of UPF and reducing the consumption of FMPF. Living in a rural area and having low income were mainly reducing factors in the consumption of UPF and driving factors in the consumption of FMPF.

CONCLUSIONS

The consumption of UPF and FMPF was determined by the set of factors that represented easy access to these foods, whether geographic or economic such as income.

What Effect Did COVID-19 Have on Adolescent Food Insufficiency in Africa and Asia? Evidence From the Global Early Adolescent Study

PURPOSE

This paper aims to explore the effect of COVID-19 and the roles of COVID-19-induced economic and community factors on adolescent food insufficiency across five urban poor settings in Africa and Asia.

METHODS

The analysis included respondents who completed a COVID-19 quantitative module as part of the longitudinal Global Early Adolescent Study. Data were divided into pre- and mid-COVID-19 periods to examine whether food insufficiency increased and modified by the pandemic and sociodemographical characteristics through longitudinal logistic regression. The roles of COVID-19-induced economic and community factors in food insufficiency were explored using multivariate logistic regression.

RESULTS

During COVID-19, food insufficiency among adolescents increased by 6.7% (95% confidence interval [CI]: 4.4%-8.9%) in Shanghai, 26.6% (95% CI: 13.3%-40.0%) in Kinshasa, 20.3% (95% CI: 8.0%-32.7%) in Denpasar, 6.9% (95% CI: -4.7% to 17.9%) in Semarang, and 24.2% (95% CI: 21.5%-27.0%) in Blantyre. We detected the impact of COVID-19 on food insufficiency was modified by gender, family wealth, caregiver type, and neighborhood safety in Blantyre. Food insufficiency during the pandemic was consistently associated with affordability challenges and positively linked to perceptions of anger toward distancing rules in three Asian sites.

DISCUSSION

This study reveals the increased trends of food insufficiency among adolescents living in urban poor settings following the onset of COVID-19. It expands our understanding of community factors associated with adolescent food insufficiency in Asia and Africa. Comprehensive strategies are needed to tackle economic and community disparities for adolescents at risk of food insufficiency.

Predicting the time to get back to work using statistical models and machine learning approaches

BACKGROUND

Whether machine learning approaches are superior to classical statistical models for survival analyses, especially in the case of lack of proportionality, is unknown.

OBJECTIVES

To compare model performance and predictive accuracy of classic regressions and machine learning approaches using data from the Inspiring Families programme.

METHODS

The Inspiring Families programme aims to support members of families with complex issues to return to work. We explored predictors of time to return to work with proportional hazards (Semi-Parametric Cox in Stata) and (Flexible Parametric Parmar-Royston in Stata) against the Survival penalised regression with Elastic Net penalty (scikit-survival), (conditional) Survival Forest algorithm (pySurvival), and (kernel) Survival Support Vector Machine (pySurvival).

RESULTS

At baseline we obtained data on 61 binary variables from all 3161 participants. No model appeared superior, with a low predictive power (concordance index between 0.51 and 0.61). The median time for finding the first job was about 254 days. The top five contributing variables were 'family issues and additional barriers', 'restriction of hours', 'available CV', 'self-employment considered' and 'education'. The Harrell's Concordance index was range from 0.60 (Cox model) to 0.71 (Random Survival Forest) suggesting a better fit for the machine learning approaches. However, the comparison for predicting median time on a selected scenario based showed only minor differences.

CONCLUSION

Implementing a series of survival models with and without proportional hazards background provides a useful insight as well as better interpretation of the coefficients affected by non-linearities. However, that better fit does not translate to substantially higher predictive power and accuracy from using machine learning approaches. Further tuning of the machine learning algorithms may provide improved results.

COVID-19 testing and financial toxicity in cancer survivors

PURPOSE

To investigate the financial strain placed upon cancer survivors during the COVID-19 pandemic.

METHODS

We investigated the association of COVID-19 testing with financial toxicity among individuals with a history of cancer from using cross-sectional data from the 2020 National Health Interview Survey. Multivariable logistic regression (MLR) analysis assessed associations between clinical and sociodemographic covariates with being unable to pay medical bills currently and having problems paying medical bills over the last 12 months.

RESULTS

Of the 4,130 individuals assessed, 420 (10.2%) reported difficulty paying bills currently and 758 (18.4%) reported difficulty paying bills over the last 12 months. Respondents who reported being currently unable and/or having problems paying medical bills over the last 12 months were, on average, younger than those who did not. MLR analysis demonstrated that older age and annual income > $35,000 were associated with lower odds of being unable to pay medical bills currently, while ever being tested for COVID-19 increased likelihood. Older age and annual income over $100,000 were associated with decreased odds of having difficulty paying medical bills over the last 12 months, whereas ever being tested for COVID-19 was associated with increased odds.

CONCLUSIONS

Cancer patients who report having difficulty paying medical bills were more likely to have been tested for COVID-19, indicating an association between COVID-19 testing and increased financial toxicity among cancer survivors.

IMPLICATIONS FOR CANCER SURVIVORS

Healthcare providers should be aware of the financial strain placed upon patients with cancer during the pandemic so sufficient support may be provided.

Patient-centered medical homes and vision care for children: a cross-sectional analysis with data from the national survey of children's health 2018-2019

BACKGROUND

Vision screening as part of well-child visits is recommended annually for US children 3 to 6 years. However, 63% of children do not get a vision screening in well-child visits. The Patient-Centered Medical Home (PCMH) improves the receipt of preventive care visits in other medical specialties but it is unknown if it improves receipt of vision screening. The objective of this study is to determine whether caregiver-reported receipt of care in a PCMH is associated with receiving a vision screening test in a well-child visit for children 3 to 6 years in a pediatrician/general doctor's office ('primary care').

METHOD

Population-based data for US children aged 3 to 6 years was derived from the National Survey of Children's Health (2018-2019). Children were excluded if they did not have a well-child visit in the previous 12 months. The primary exposure was receipt of care in a PCMH ('PCMH care'), and the primary outcome was receipt of a vision screening in primary care. Adjusted odds ratios (aOR) and predicted probabilities were computed for children with and without PCMH care.

RESULTS

Among 9,587 children with well-child visits, 4,984 (50.9%) were males. There were 1,107 (23.3%) Hispanic, 6704 (52.8%) White/Non-Hispanic and 545 (11.8%) Black/Non-Hispanic children. There were 5,482 (51.8%) children who received PCMH care. Of those with PCMH care, 2,629 (52.2%) received a vision screening in primary care. Those with PCMH care (52.2%) had a higher odds of receiving a vision screening (aOR, 1.31; 95% CI 1.11, 1.55) in primary care compared to children without PCMH care (42.8%). The predicted probability of vision screening in primary care was 50.8% (95% CI 48.2, 53.5) for children that received PCMH care, and 44.3% (95% CI 41.3, 47.3) without PCMH care.

CONCLUSIONS

Caregiver-reported receipt of PCMH care was associated with a greater likelihood of vision screening for children 3 to 6 years in a well-child visit. Further studies are needed to understand the mechanisms through which PCMH care contributes to the greater odds of vision screening in primary care to inform the creation of strategic interventions to prevent vision loss and its long-term implications.

Factors Associated with Medical Care-Seeking and Stool Sample Submission for Diarrheal Illness, FoodNet, United States, 2018-2019

Laboratory-based surveillance for enteric pathogens causing diarrhea is foundational for monitoring foodborne diseases in the United States. However, diarrheal illnesses are not always confirmed by laboratory testing, so estimates of the true number of illnesses must adjust for underdiagnosis, including underdiagnosis due to ill persons not seeking medical care or submitting a stool sample for laboratory testing. We assessed these factors among persons with an acute diarrheal illness who responded to the most recent Foodborne Diseases Active Surveillance Network (FoodNet) Population Survey (2018-2019). Multiple modes of administration (telephone, web-based) and multiple sampling frames were used to ask survey respondents in English or Spanish about diarrhea and other symptoms experienced in the 30 days before the interview and to ask if they had sought medical care or submitted a stool sample. Of 1018 respondents with an acute diarrheal illness, 22.0% had sought medical care and 4.7% submitted a stool sample. On multivariable analysis, older adults (aged 65 years and over), male respondents, and persons with a household income of ≥$40,000 per annum were significantly more likely to seek medical care, as were respondents reporting cough, fever, vomiting, recent international travel, or duration of diarrhea for ≥3 days. Older adults and persons with five or more loose stools in 24 h who sought medical care were significantly more likely to submit a stool sample. Ill respondents with a concurrent cough were less likely to submit a stool sample. Sociodemographic characteristics, symptoms, and international travel influence whether a patient with an acute diarrheal illness will seek care or submit a stool specimen. Accounting for these factors when analyzing surveillance data will likely produce more precise estimates of the true number of foodborne illnesses.

Determinants of the consumption of ultra-processed foods in the Brazilian population

This article aims to evaluate the sociodemographic determinants of ultra-processed foods (UPF) consumption in the Brazilian population ≥ 10 years of age. The study used data from the personal and resident food consumption module of the Family Budget Surveys, grouping foods according to the NOVA classification of food processing. The classification and regression tree (CART) was used to identify the factors determining the lowest to highest percentage participation of UPF in the Brazilian population. UPF accounted for 37·0 % of energy content in 2017-2018. In the end, eight nodes of UPF consumption were identified, with household situation, education in years, age in years and per capita family income being the determining factors identified in the CART. The lowest consumption of UPF occurred among individuals living in rural areas with less than 4 years of education (23·78 %), while the highest consumption occurred among individuals living in urban areas, < 30 years of age and with per capita income ≥ US$257 (46·27 %). The determining factors identified in CART expose the diverse pattern of UPF consumption in the Brazilian population, especially conditions directly associated with access to these products, such as penetration in urban/rural regions. Through the results of this study, it may be possible to identify focal points for action in policies and actions to mitigate UPF consumption.

Effectiveness of a dynamic seat cushion on recovery and recurrence of neck and low back pain in office workers: a secondary analysis of a randomized controlled trial

BACKGROUND

Neck and low back pain are prevalent issues among office workers due to prolonged sitting, necessitating effective interventions. Dynamic seat cushion, designed to promote postural shifts, have emerged as promising solutions to address this concern. This study aims to evaluate the effectiveness of a dynamic seat cushion on recovery and recurrence of neck and/or low back pain in office workers.

METHODS

This study used 6-month follow-up data of a randomized controlled trial, involving 66 office workers who reported neck and/or low back pain during the trial. At baseline, participants were cluster-randomized into an intervention group, which received a dynamic seat cushion designed to encourage postural shifts, or a control group, which received a placebo seat pad. Health outcomes included recovery duration and recurrence of pain. Analyses utilized log rank test and Cox proportional hazard models.

RESULTS

The recovery rate from neck and/or low back pain was 100% for the intervention group, and 86% for the control group. The median recovery duration of participants who reported pain during the 6-month period was 1 month in the intervention group and 3 months in the control group. The intervention group had a higher probability of recovery compared to the control group (HRadj 4.35, 95% CI 1.87-10.11; p < 0.01). The recurrence rate of neck and low back pain was 27% in the intervention group, which was 75% in the control group. The Hazard Ratio, after adjustment, for the intervention group compared to the control group was 0.50 (95% CI = 0.11-2.12).

CONCLUSIONS

A dynamic seat cushion that encourages postural shifts shortened recovery duration of neck and low back pain among office workers. Due to small numbers, a potentially relevant reduction in the recurrence of neck and low back pain could not be statistically confirmed. A power analysis was not conducted for this secondary analysis, and future studies should be designed with adequate sample sizes to explore the recurrence of pain with greater statistical power.

TRIAL REGISTRATION

This trial is retrospectively registered under the Thai Clinical Trials Registry: TCTR20230623002 (23/06/2023).

Imputation methods for mixed datasets in bioarchaeology

Missing data is a prevalent problem in bioarchaeological research and imputation could provide a promising solution. This work simulated missingness on a control dataset (481 samples × 41 variables) in order to explore imputation methods for mixed data (qualitative and quantitative data). The tested methods included Random Forest (RF), PCA/MCA, factorial analysis for mixed data (FAMD), hotdeck, predictive mean matching (PMM), random samples from observed values (RSOV), and a multi-method (MM) approach for the three missingness mechanisms (MCAR, MAR, and MNAR) at levels of 5%, 10%, 20%, 30%, and 40% missingness. This study also compared single imputation with an adapted multiple imputation method derived from the R package "mice". The results showed that the adapted multiple imputation technique always outperformed single imputation for the same method. The best performing methods were most often RF and MM, and other commonly successful methods were PCA/MCA and PMM multiple imputation. Across all criteria, the amount of missingness was the most important parameter for imputation accuracy. While this study found that some imputation methods performed better than others for the control dataset, each imputation method has advantages and disadvantages. Imputation remains a promising solution for datasets containing missingness; however when making a decision it is essential to consider dataset structure and research goals.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12520-024-02078-2.

Development and Validation of the Communities Geriatric Mild Cognitive Impairment Risk Calculator (CGMCI-Risk)

Objectives: The aim was to develop and validate the Communities Geriatric Mild Cognitive Impairment Risk Calculator (CGMCI-Risk), aiding community healthcare workers in the early identification of individuals at high risk of mild cognitive impairment (MCI). Methods: Based on nationally representative community survey data, backward stepwise regression was employed to screen the variables, and logistic regression was utilized to construct the CGMCI-Risk. Internal validation was conducted using bootstrap resampling, while external validation was performed using temporal validation. The area under the receiver operating characteristic curve (AUROC), calibration curve, and decision curve analysis (DCA) were employed to evaluate the CGMCI-Risk in terms of discrimination, calibration, and net benefit, respectively. Results: The CGMCI-Risk model included variables such as age, educational level, sex, exercise, garden work, TV watching or radio listening, Instrumental Activity of Daily Living (IADL), hearing, and masticatory function. The AUROC was 0.781 (95% CI = 0.766 to 0.796). The calibration curve showed strong agreement, and the DCA suggested substantial clinical utility. In external validation, the CGMCI-Risk model maintained a similar performance with an AUROC of 0.782 (95% CI = 0.763 to 0.801). Conclusions: CGMCI-Risk is an effective tool for assessing cognitive function risk within the community. It uses readily predictor variables, allowing community healthcare workers to identify the risk of MCI in older adults over a three-year span.

Does income matter for the policy effect of public long-term care insurance on informal care use in China? A quasi-experimental study

OBJECTIVE

Since 2016, the Chinese government has been piloting a public long-term care insurance (LTCI) scheme. This study examined whether the LTCI scheme reduced the use of informal care and how this has varied across income groups.

METHOD

We used data from the 2011, 2014, and 2018 waves of Chinese Longitudinal Healthy Longevity Survey, focusing on community-dwelling older adults aged 65 years and older. We used staggered difference-in-differences analyses with propensity score matching to examine the effects of the policy.

RESULTS

The LTCI scheme reduced the probability and intensity of informal care use by 5.7% (p < .05) and 17.4% (p < .05), respectively. The policy impact was limited to older people in the middle-income group, reducing the probability and intensity of informal care use by 15.6% (p < .001) and 43.1% (p < .05), respectively. We did not find a statistically significant policy effect for older adults with high or low incomes.

CONCLUSIONS

The LTCI scheme had different effects on reducing the informal care burden for family caregivers by income level. We suggest that the scheme should entitle people with low incomes to a preferential co-payment rate, thereby enhancing their access to formal care.

Training for Elite Team-Pursuit Track Cyclists-Part II: A Comparison of Preparation Phases in Consecutive World-Record-Breaking Seasons

PURPOSE

To compare the training characteristics of an elite team pursuit cycling squad in the 3-month preparation phases prior to 2 successive world-record (WR) performances.

METHODS

Training data of 5 male track endurance cyclists (mean [SD]; age 23.4 [3.46] y; body mass 80.2 [2.74] kg; 4.5 [0.17] W·kg-1 at LT2; maximal aerobic power 6.2 [0.27] W·kg-1; maximal oxygen uptake 65.9 [2.89] mL·kg-1·min-1) were analyzed with weekly total training volume by training type and heart rate, power output, and torque intensity distributions calculated with reference to the respective WRs' performance requirements.

RESULTS

Athletes completed 805 (82.81) and 725 (68.40) min·wk-1 of training, respectively, in each season. In the second season, there was a 32% increase in total track volume, although track sessions were shorter (ie, greater frequency) in the second season. A pyramidal intensity distribution was consistent across both seasons, with 81% of training, on average, performed below LT1 power output each week, whereas 6% of training was performed above LT2. Athletes accumulated greater volume above WR team pursuit lead power (2.4% vs 0.9%) and torque (6.2% vs 3.2%) in 2019. In one athlete, mean single-leg-press peak rate of force development was 71% and 46% higher at mid- and late-phases, respectively, during the preparation period.

CONCLUSIONS

These findings provide novel insights into the common and contrasting methods contributing to successive WR team pursuit performances. Greater accumulation of volume above race-specific power and torque (eg, team pursuit lead), as well as improved neuromuscular force-generating capacities, may be worthy of investigation for implementation in training programs.

Training for Elite Team-Pursuit Track Cyclists-Part I: A Profile of General Training Characteristics

PURPOSE

To profile the training characteristics of an elite team pursuit cycling squad and assess variations in training intensity and load accumulation across the 36-week period prior to a world-record performance at the 2018 Commonwealth Games.

METHODS

Training data of 5 male track endurance cyclists (mean [SD]; age 21.9 [3.52] y; 4.4 [0.16] W·kg-1 at anaerobic threshold; 6.2 [0.28] W·kg-1 maximal oxygen uptake 68.7 [2.99] mL kg·min-1) were analyzed with weekly total training volume and heart rate, power output, and torque intensity distributions calculated with reference to their 3:49.804 min:s.ms performance requirements for a 4-km team pursuit.

RESULTS

Athletes completed 543 (37) h-1 of training across 436 (16) sessions. On-bike activities accounted for 69.9% of all training sessions, with participants cycling 11,246 (1139) km-1 in the training period of interest, whereas 12.7% of sessions involved gym/strength training. A pyramidal intensity distribution was evident with over 65% and 70% of training, respectively, performed at low-intensity zone heart rate and power output, whereas 5.3% and 7.7% of training was performed above anaerobic threshold. The athletes accumulated 4.4% of total training volume at, or above, their world-record team pursuit lead position torque (55 N·m).

CONCLUSIONS

These data provide updated and novel insight to the power and torque demands and load accumulation contributing to world-record team pursuit performance. Although the observed pyramidal intensity distribution is common in endurance sports, the lack of shift toward a polarized intensity distribution during taper and competition peaking differs from previous research.

The impact of chiropractic care on prescription opioid use for non-cancer spine pain: protocol for a systematic review and meta-analysis

BACKGROUND

In recent studies, receipt of chiropractic care has been associated with lower odds of receiving prescription opioids and, among those already prescribed, reduced doses of opioids among patients with non-cancer spine pain. These findings suggest that access to chiropractic services may reduce reliance on opioids for musculoskeletal pain.

OBJECTIVE

To assess the impact of chiropractic care on initiation, or continued use, of prescription opioids among patients with non-cancer spine pain.

METHODS

We will search for eligible randomized controlled trials (RCTs) and observational studies indexed in MEDLINE, Embase, AMED, CINAHL, Web of Science, and the Index to Chiropractic Literature from database inception to June 2024. Article screening, data extraction, and risk-of-bias assessment will be conducted independently by pairs of reviewers. We will conduct separate analyses for RCTs and observational studies and pool binary outcomes (e.g. prescribed opioid receipt, long-term opioid use, and higher versus lower opioid dose) as odds ratios (ORs) with associated 95% confidence intervals (CIs). When studies provide hazard ratios (HRs) or relative risks (RRs) for time-to-event data (e.g. time-to-first opioid prescription) or incidence rates (number of opioid prescriptions over time), we will first convert them to an OR before pooling. Continuous outcomes such as pain intensity, sleep quality, or morphine equivalent dose will be pooled as weighted mean differences with associated 95% CIs. We will conduct meta-analyses using random-effects models and explore sources of heterogeneity using subgroup analyses and meta-regression. We will evaluate the certainty of evidence of all outcomes using the GRADE approach and the credibility of all subgroup effects with ICEMAN criteria. Our systematic review will follow the PRISMA statement and MOOSE guidelines.

DISCUSSION

Our review will establish the current evidence informing the impact of chiropractic care on new or continued prescription opioid use for non-cancer spine pain. We will disseminate our results through peer-reviewed publication and conference presentations. The findings of our review will be of interest to patients, health care providers, and policy-makers.

TRIAL REGISTRATION

Systematic review registration: PROSPERO CRD42023432277.

Sense of belonging to community and avoidable hospitalization: a population-based cohort study of 456,415 Canadians

A sense of belonging to a community is a dimension of subjective well-being that is of growing population health interest. We evaluated sex-stratified associations between community belonging and risk of avoidable hospitalization. Adult men and women from the Canadian Community Health Survey (2000-2014) were asked to rate their sense of community belonging (N = 456,415) and were also linked to acute inpatient hospitalizations to 31 March 2018. We used Cox proportional hazards models to assess the association between community belonging and time to hospitalization related to ambulatory care sensitive conditions (ACSCs) and adjusted for a range of sociodemographic, health, and behavioural confounders. Compared to those who reported intermediate levels of belonging, both very weak and very strong sense of belonging were associated with greater risk of avoidable hospitalization for women (HR 1.29, 95% CI 1.12, 1.47, very weak; HR 1.15, 95% CI 1.03, 1.27, very strong), but not for men (HR 1.12, 95% CI 0.97, 1.29, very weak; HR 1.08, 95% CI 0.98, 1.19, very strong). This study suggests that community belonging is associated with risk of ACSC hospitalization for women and provides a foundation for further research on community belonging and population health.

The association of physical activity and leisure-time sedentary behavior with perceived stress among Chinese adults: A cross-sectional study based on the Chinese health and nutrition survey data

Objective

Physical activity (PA) and sedentary behavior (SB) include several domains, whether the association of PA and SB with perceived stress is domain-specific is not clear. This study aims to identify associations of physical activity (exercise and housework) and leisure-time sedentary behavior (LTSB) with perceived stress among Chinese adults.

Methods

The data were collected from the 2015 China Health and Nutrition Survey (CHNS). Respondents completed multiple questionnaires developed by the CHNS team, from which we extracted and sorted PA and LTSB data. Perceived stress was measured using the 14-item Perceived Stress Scale. PA was measured using a questionnaire covering 7 types of commonly practiced exercises and 4 types of housework activities among Chinese individuals. Consecutive questions were used to inquire about the time spent on each type of PA. The measurement of LTSB was conducted in the same manner. Data analysis involved Chi-square test and logistic regression.

Results

11,471 adults were included, with an average age of 52.3 years, and 48.3 % were male. 69.9 % (8,019) of respondents reported high perceived stress. Following adjustment for age, gender and other factors, perceived stress was lower for adults reporting medium exercise time (1-2 h) compared with excessively (≥2 h) (OR=1.314 [95 %CI 1.071, 1.612], P<0.001) and least (<1 h) (OR=1.273 [95 %CI 1.115, 1.413], P<0.001) active adults. Perceived stress was higher for adults reporting less housework time (<1 h) compared with adults spending medium (1-2 h) (OR=0.860 [0.744, 0.993], P<0.05) and long (≥2 h) (OR=0.725 [95 %CI 0.628, 0.838], P<0.001) time on housework. Low-level LTSB (<2 h) was associated with higher perceived stress than medium- (2-4 h) (OR=0.817 [0.718, 0.930], P<0.01) and high-level LTSB (≥4 h) (OR=0.668 [0.577, 0.773], P<0.001).

Conclusions

The association of PA and SB with perceived stress is domain-specific. Medium exercise time and extended housework time are associated with reduced perceived stress. Additionally, our findings suggesting that increasing the time spent on LTSB is linked to lower perceived stress levels.

District-level monitoring of universal health coverage, India

Objective

To develop a framework and index for measuring universal health coverage (UHC) at the district level in India and to assess progress towards UHC in the districts.

Methods

We adapted the framework of the World Health Organization and World Bank to develop a district-level UHC index (UHC d ). We used routinely collected health survey and programme data in India to calculate UHC d for 687 districts from geometric means of 24 tracer indicators in five tracer domains: reproductive, maternal, newborn and child health; infectious diseases; noncommunicable diseases; service capacity and access; and financial risk protection. UHC d is on a scale of 0% to 100%, with higher scores indicating better performance. We also assessed the degree of inequality within districts using a subset of 14 tracer indicators. The disadvantaged subgroups were based on four inequality dimensions: wealth quintile, urban-rural location, religion and social group.

Findings

The median UHC d was 43.9% (range: 26.4 to 69.4). Substantial geographical differences existed, with districts in southern states having higher UHC d than elsewhere in India. Service coverage indicator levels were greater than 60%, except for noncommunicable diseases and for service capacity and access. Health insurance coverage was limited, with about 10% of the population facing catastrophic and impoverishing health expenditure. Substantial wealth-based disparities in UHC were seen within districts.

Conclusion

Our study shows that UHC can be measured at the local level and can help national and subnational government develop prioritization frameworks by identifying health-care delivery and geographic hotspots where limited progress towards UHC is being made.

Demographic factors impact the rate of hearing decline across the adult lifespan

BACKGROUND

Little is known about the natural history of hearing loss in adults, despite it being an important public health problem. The purpose of this study is to describe the rate of hearing change per year over the adult lifespan.

METHODS

The 1436 participants are from the MUSC Longitudinal Cohort Study of Age-related Hearing Loss (1988-present). Outcomes are audiometric thresholds at 250, 500, 1000, 2000, 3000, 4000, 6000, and 8000 Hz, averaged across right and left ears, and pure-tone average (PTA). Demographic factors are sex (female/male), race, which is categorized as white or racial Minority, and baseline age group (18-39, 40-59, 60-69, 70+ years). Linear mixed regression models are used to estimate the effect of age (per year) on the rate of threshold and PTA change.

RESULTS

Participants' mean age is 63.1 (SD 14.9) years, 57.7% are female, and 17.8% are racial Minority (17.1% were Black or African American). In sex-race-adjusted models, rates of threshold change are 0.42 to 1.44 dB across thresholds. Rates of change differ by sex at most individual thresholds, but not PTA. Females (versus males) showed higher rates of threshold change in higher frequencies but less decline per year in lower frequencies. Black/African American (versus white) participants have lower rates of threshold and PTA change per year. Hearing thresholds decline across the adult lifespan, with older (versus younger) baseline age groups showing higher rates of decline per year.

CONCLUSIONS

Declines to hearing occur across the adult lifespan, and the rate of decline varies by sex, race, and baseline age.

Identify the most appropriate imputation method for handling missing values in clinical structured datasets: a systematic review

BACKGROUND AND OBJECTIVES

Comprehending the research dataset is crucial for obtaining reliable and valid outcomes. Health analysts must have a deep comprehension of the data being analyzed. This comprehension allows them to suggest practical solutions for handling missing data, in a clinical data source. Accurate handling of missing values is critical for producing precise estimates and making informed decisions, especially in crucial areas like clinical research. With data's increasing diversity and complexity, numerous scholars have developed a range of imputation techniques. To address this, we conducted a systematic review to introduce various imputation techniques based on tabular dataset characteristics, including the mechanism, pattern, and ratio of missingness, to identify the most appropriate imputation methods in the healthcare field.

MATERIALS AND METHODS

We searched four information databases namely PubMed, Web of Science, Scopus, and IEEE Xplore, for articles published up to September 20, 2023, that discussed imputation methods for addressing missing values in a clinically structured dataset. Our investigation of selected articles focused on four key aspects: the mechanism, pattern, ratio of missingness, and various imputation strategies. By synthesizing insights from these perspectives, we constructed an evidence map to recommend suitable imputation methods for handling missing values in a tabular dataset.

RESULTS

Out of 2955 articles, 58 were included in the analysis. The findings from the development of the evidence map, based on the structure of the missing values and the types of imputation methods used in the extracted items from these studies, revealed that 45% of the studies employed conventional statistical methods, 31% utilized machine learning and deep learning methods, and 24% applied hybrid imputation techniques for handling missing values.

CONCLUSION

Considering the structure and characteristics of missing values in a clinical dataset is essential for choosing the most appropriate data imputation technique, especially within conventional statistical methods. Accurately estimating missing values to reflect reality enhances the likelihood of obtaining high-quality and reusable data, contributing significantly to precise medical decision-making processes. Performing this review study creates a guideline for choosing the most appropriate imputation methods in data preprocessing stages to perform analytical processes on structured clinical datasets.

Data Science Methods for Real-World Evidence Generation in Real-World Data

In the healthcare landscape, data science (DS) methods have emerged as indispensable tools to harness real-world data (RWD) from various data sources such as electronic health records, claim and registry data, and data gathered from digital health technologies. Real-world evidence (RWE) generated from RWD empowers researchers, clinicians, and policymakers with a more comprehensive understanding of real-world patient outcomes. Nevertheless, persistent challenges in RWD (e.g., messiness, voluminousness, heterogeneity, multimodality) and a growing awareness of the need for trustworthy and reliable RWE demand innovative, robust, and valid DS methods for analyzing RWD. In this article, I review some common current DS methods for extracting RWE and valuable insights from complex and diverse RWD. This article encompasses the entire RWE-generation pipeline, from study design with RWD to data preprocessing, exploratory analysis, methods for analyzing RWD, and trustworthiness and reliability guarantees, along with data ethics considerations and open-source tools. This review, tailored for an audience that may not be experts in DS, aspires to offer a systematic review of DS methods and assists readers in selecting suitable DS methods and enhancing the process of RWE generation for addressing their specific challenges.

The prevalence of common mental disorders across 18 ethnic groups in Britain during the COVID-19 pandemic: Evidence for Equality National Survey (EVENS)

BACKGROUND

The COVID-19 pandemic negatively impacted mental health in the general population in Britain. Ethnic minority people suffered disproportionately, in terms of health and economic outcomes, which may contribute to poorer mental health. We compare the prevalence of depression and anxiety across 18 ethnic groups in Britain during the COVID-19 pandemic.

METHODS

Secondary analysis of cross-sectional data (February-November 2021) from 12,161 participants aged 18-60 years old (N with data on outcomes = 11,540 for depression & 11,825 for anxiety), obtained from the Evidence for Equality National Survey (EVENS). Data were weighted to account for selection bias and coverage bias. Weighted regression models examined ethnic differences in depression (Centre for Epidemiologic Studies Depression Scale) and anxiety (Generalised Anxiety Disorder-7). Effect modification analyses explored whether ethnic differences in outcomes were consistent within age and sex sub-groups.

RESULTS

Compared to White British people, greater odds of anxiety caseness (and greater anxiety symptoms) were observed for Arab (OR = 2.57; 95 % CI = 1.35-4.91), Mixed White and Black Caribbean (1.57; 1.07-2.30), any other Black (2.22, 1.28-3.87) and any other Mixed (1.58; 1.08-2.31) ethnic groups. Lower odds of depression caseness (and lower depressive symptoms) were identified for Chinese (0.63; 0.46-0.85), Black African (0.60; 0.46-0.79), and any other Asian (0.55; 0.42-0.72) ethnic groups.

LIMITATIONS

Cross-sectional data limits the opportunity to identify changes in ethnic inequalities in mental health over time.

CONCLUSIONS

We have identified certain ethnic groups who may require more targeted mental health support to ensure equitable recovery post-pandemic. Despite finding lower levels of depression for some ethnic groups, approximately one third of people within each ethnic group met criteria for depression.

Agreement between audiometric hearing loss and self-reported hearing difficulty on the Revised Hearing Handicap Inventory differs by demographic factors

BACKGROUND

New standardised measures of self-reported hearing difficulty can be validated against audiometric hearing loss. This study reports the influence of demographic factors (age, sex, race and socioeconomic position (SEP)) on the agreement between audiometric hearing loss and self-reported hearing difficulty.

METHODS

Participants were 1558 adults (56.9% female; 20.0% racial minority; mean age 63.7 (SD 14.1) years) from the Medical University of South Carolina Longitudinal Cohort Study of Age-Related Hearing Loss (1988-current). Audiometric hearing loss was defined as the average of pure-tone thresholds at frequencies 0.5, 1.0, 2.0 and 4.0 kHz >25 dB HL in the worse ear. Self-reported hearing difficulty was defined as ≥6 points on the Revised Hearing Handicap Inventory (RHHI) or RHHI screening version (RHHI-S). We report agreement between audiometric hearing loss and the RHHI(-S), defined by sensitivity, specificity, accuracy, positive predictive value, negative predictive value and observed minus predicted prevalence. Estimates were stratified to age group, sex, race and SEP proxy.

RESULTS

The prevalence of audiometric hearing loss and self-reported hearing difficulty were 49.0% and 48.8%, respectively. Accuracy was highest among participants aged <60 (77.6%) versus 60-70 (71.4%) and 70+ (71.9%) years, for white (74.6%) versus minority (68.0%) participants and was similar by sex and SEP proxy. Generally, agreement of audiometric hearing loss and RHHI(-S) self-reported hearing difficulty differed by age, sex and race.

CONCLUSIONS

Relationships of audiometric hearing loss and self-reported hearing difficulty vary by demographic factors. These relationships were similar for the full (RHHI) and screening (RHHI-S) versions of this tool.

Missing Data Analysis

Methods for handling missing data in clinical psychology studies are reviewed. Missing data are defined, and a taxonomy of main approaches to analysis is presented, including complete-case and available-case analysis, weighting, maximum likelihood, Bayes, single and multiple imputation, and augmented inverse probability weighting. Missingness mechanisms, which play a key role in the performance of alternative methods, are defined. Approaches to robust inference, and to inference when the mechanism is potentially missing not at random, are discussed.

Prevalence of self-reported hearing difficulty on the Revised Hearing Handicap Inventory and associated factors

BACKGROUND

Hearing loss is common in aging adults and is an important public health concern. Self-reported measures of hearing difficulty are often used in research and clinical practice, as they capture the functional impacts of hearing loss on individuals. However, little research has evaluated the prevalence or factors associated with self-reported hearing difficulty. Therefore, the purpose of this study was to determine the prevalence of self-reported hearing difficulty, measured by the Revised Hearing Handicap Inventory (RHHI), and associated factors.

METHODS

This study was conducted in a community-based cohort study based in Charleston, SC. We determined the prevalence of RHHI self-reported hearing difficulty (score ≥ 6 points) and evaluated associated factors with logistic regression models. Results are presented as odds ratios (OR) with corresponding 95% confidence intervals (95% CI).

RESULTS

There were 1558 participants included in this study (mean age 63.7 [SD 14.4], 56.9% female, 20.0% Minority race). The prevalence of RHHI self-reported hearing difficulty was 48.8%. In a multivariable model, older age (per + 1 year; OR 0.97 [95% CI 0.96, 0.98]), Minority (vs. White) race (OR 0.68 [95% CI 0.49, 0.94]), and speech-in-noise scores that are better than predicted (OR 0.99 [95% CI 0.98, 1.00]) were associated with lower odds of RHHI self-reported hearing difficulty. Furthermore, female (vs. male) sex (OR 1.39 [95% CI 1.03, 1.86]), higher PTA in the worse ear (per + 1 dB; OR 1.10 [95% CI 1.09, 1.12]), more comorbid conditions (vs. 0; 1 condition: OR 1.50 [95% CI 1.07, 2.11]; 2 conditions: OR 1.96 [95% CI 1.32, 2.93]; 3 + conditions: OR 3.00 [95% CI 1.60, 5.62]), noise exposure (OR 1.54 [95% CI 1.16, 2.03]), bothersome tinnitus (OR 2.16 [95% CI 1.59, 2.93]), and more depressive symptoms (OR 1.04 [95% CI 1.01, 1.07]) were associated with higher odds of RHHI self-reported hearing difficulty.

CONCLUSIONS

The prevalence of RHHI self-reported hearing difficulty is high, and associated factors included demographics, audiometric hearing and other hearing-related factors, and physical and mental health. The RHHI likely captures functional impacts of hearing loss that are not captured by audiometry alone. Study findings can support the correct interpretation of the RHHI in research and clinical settings.

Disorder-specific versus transdiagnostic cognitive mechanisms in anxiety and depression: Machine-learning-based prediction of symptom severity

INTRODUCTION

Psychiatric evaluation of anxiety and depression is currently based on self-reported symptoms and their classification into discrete disorders. Yet the substantial overlap between these disorders as well as their within-disorder heterogeneity may contribute to the mediocre success rates of treatments. The proposed research examines a new framework for diagnosis that is based on alterations in underlying cognitive mechanisms. In line with the Research Domain Criteria (RDoC) approach, the current study directly compares disorder-specific and transdiagnostic cognitive patterns in predicting the severity of anxiety and depression symptoms.

METHODS

The sample included 237 individuals exhibiting differing levels of anxiety and depression symptoms, as measured by the STAI-T and BDI-II. Random Forest regressors were used to analyze their performance on a battery of six computerized cognitive-behavioral tests targeting selective and spatial attention, expectancy, interpretation, memory, and cognitive control biases.

RESULTS

Unique anxiety-specific biases were found, as well as shared anxious-depressed bias patterns. These cognitive biases exhibited relatively high fitting rates when predicting symptom severity (questionnaire scores common range 0-60, MAE = 6.03, RMSE = 7.53). Interpretation and expectancy biases exhibited the highest association with symptoms, above all other individual biases.

LIMITATIONS

Although internal validation methods were applied, models may suffer from potential overfitting due to sample size limitations.

CONCLUSION

In the context of the ongoing dispute regarding symptom-centered versus transdiagnostic approaches, the current study provides a unique comparison of these two views, yielding a novel intermediate approach. The results support the use of mechanism-based dimensional diagnosis for adding precision and objectivity to future psychiatric evaluations.

Patterns and socioeconomic differences in secondhand exposure to cigarettes, e-cigarettes, and heated tobacco products at home in Hong Kong adolescents

INTRODUCTION

Smoke or aerosols from cigarettes, e-cigarettes (ECs), or heated tobacco products (HTPs) are harmful. Yet, there is little knowledge about the specific patterns of secondhand tobacco exposure by source within household settings and the socioeconomic status (SES) differences in adolescents.

METHODS

We used territory-representative student data from a cross-sectional school-based survey in 2020-2021 to calculate the weighted prevalence of secondhand exposure to cigarettes, e-cigarettes, and HTPs in the past seven days. Parental education and perceived family affluence were used as indicators of socioeconomic status. Generalized linear mixed models were used to analyze associations.

RESULTS

Among 22039 participants, 29.8% reported any secondhand tobacco exposure (SH-Any) at home, primarily from cigarettes (27.4%), followed by e-cigarettes (4.0%) and HTPs (0.9%). Tertiary parental education level was associated with lower SH-Any exposure (Adjusted odds ratio, AOR=0.49; 95% CI: 0.45-0.53, p<0.001), fewer exposure days (β= -0.685, p<0.001), lower exposure to cigarettes (SH-CC) (AOR=0.49; 95% CI: 0.45-0.54, p<0.001) and to e-cigarettes or HTPs (SH-EC/HTP) (AOR=0.57; 95% CI: 0.45-0.71, p<0.001). 'Poor' family affluence was associated with higher exposures [AOR(SH-Any) =1.14; 95% CI: 1.06-1.22, p=0.001; β(days)=0.160, p<0.001; AOR(SH-CC) =1.15; 95% CI: 1.07-1.24, p<0.001], except for SH-EC/HTP exposure, which was higher in students in an affluent family (AOR =1.66; 95% CI: 1.25-2.21, p<0.001). Significant SES differences in SH-EC/HTP exposure were found only in groups with low parental education level. Dose-response relationships were found between lower SH-Any and SH-CC and higher SES categories (p for trend<0.001).

CONCLUSIONS

Adolescents experienced a high prevalence of tobacco smoke exposure at home, primarily from cigarettes. Higher SES was associated with lower tobacco exposure, except for SH-EC/HTP, which was higher among adolescents from affluent families. Additionally, high parental education level was protective against exposure to SH-EC/HTP. Comprehensive control measures to reduce the use of these tobacco products are needed to protect adolescents of diverse socioeconomic backgrounds.

Exploring Emotional Dysregulation and Avoidance with Caregivers as the Mechanisms Linking Social Communication Understanding and Aggressive Behaviours

Many autistic adolescents and young adults present with aggressive behaviours, which can be challenging for caregivers. The present study aimed to explore the underlying mechanisms between social communication understanding and aggressive behaviours in autistic and non-autistic adolescents, specifically the role of emotional dysregulation and its impact on avoidance with caregivers. Caregivers of autistic (n = 275) and non-autistic adolescents (n = 123) completed standardised caregiver-report questionnaires measuring social communication understanding, emotional dysregulation, avoidance between the adolescent and caregiver and aggressive behaviours. A serial mediation analysis indicated that levels of social communication understanding were indirectly associated with aggressive behaviours. This occurred through increased emotional dysregulation, which may have led to increased avoidance between the autistic and non-autistic adolescents and their caregivers. These findings support a sequential process by which adolescents with low social communication understanding are more likely to behave aggressively through being emotionally dysregulated and the impact of this on the increased avoidance within the caregiver-adolescent dyad. This process was found within autistic and non-autistic adolescents, suggesting a mechanism across individuals with aggression. These findings indicate that interventions based on improving emotion regulation ability and responses between adolescents and their caregivers may aid in reducing aggressive behaviours in adolescents and young adults with lower social communication understanding.

Performance of a Claims-Based Frailty Proxy Using Varying Frailty Ascertainment Lookback Windows

BACKGROUND

Frailty is an aging-related syndrome of reduced physiological reserve to maintain homeostasis. The Faurot frailty index has been validated as a Medicare claims-based proxy for predicting frailty using billing information from a user-specified ascertainment window.

OBJECTIVES

We assessed the validity of the Faurot frailty index as a predictor of the frailty phenotype and 1-year mortality using varying frailty ascertainment windows.

RESEARCH DESIGN

We identified older adults (66+ y) in Round 5 (2015) of the National Health and Aging Trends Study with Medicare claims linkage. Gold standard frailty was assessed using the frailty phenotype. We calculated the Faurot frailty index using 3, 6, 8, and 12 months of claims prior to the survey or all-available lookback. Model performance for each window in predicting the frailty phenotype was assessed by quantifying calibration and discrimination. Predictive performance for 1-year mortality was assessed by estimating risk differences across claims-based frailty strata.

RESULTS

Among 4253 older adults, the 6 and 8-month windows had the best frailty phenotype calibration (calibration slopes: 0.88 and 0.87). All-available lookback had the best discrimination (C-statistic=0.780), but poor calibration. Mortality associations were strongest using a 3-month window and monotonically decreased with longer windows. Subgroup analyses revealed worse performance in Black and Hispanic individuals than counterparts.

CONCLUSIONS

The optimal ascertainment window for the Faurot frailty index may depend on the clinical context, and researchers should consider tradeoffs between discrimination, calibration, and mortality. Sensitivity analyses using different durations can enhance the robustness of inferences. Research is needed to improve prediction across racial and ethnic groups.

Adherence to the ultra-processed dietary pattern and risk of depressive outcomes: Findings from the NutriNet Brasil cohort study and an updated systematic review and meta-analysis

BACKGROUND & AIMS

We aimed to analyze the prospective association between adherence to the ultra-processed dietary pattern and risk of depressive outcomes using original data from the NutriNet Brasil cohort and via a systematic review and meta-analysis of observational studies that have investigated the same association.

METHODS

In our original research analysis, we used data from 15,960 adults (≥18 y) participating in the NutriNet Brasil cohort study, free of depression or depressive symptoms during the baseline (77.5% women, 45.8 ± 13.0 y). The mean dietary share of ultra-processed foods (%Kcal/d), calculated from two baseline 24-h dietary recalls, was used to measure the adherence to the ultra-processed dietary pattern. New cases of depressive symptoms were assessed using the Patient Health Questionnaire-9 over the follow-up period (mean: 18.3 months). Cox proportional hazards models were used for the main analyses. In our systematic review and meta-analysis, we incorporated effect estimates from six prospective cohort studies that have examined the same association, including ours.

RESULTS

In the adjusted model, each 10% increase in the dietary share of ultra-processed foods was associated with a 10% increase in the hazard of incident cases of depressive symptoms (HR:1.10; 95%CI: 1.07-1.14). This association was slightly attenuated in the models including potential mediators. In our meta-analysis of six prospective studies, high versus low exposure to ultra-processed foods was associated with a summary hazard ratio of depressive outcomes of 1.32; 95%CI: 1.19-1.46; I2: 71%.

CONCLUSION

A higher adherence to the ultra-processed dietary pattern was associated with a higher risk of developing depressive outcomes in the NutriNet Brasil cohort and in the meta-analysis.

Use of Sequential Hot-Deck Imputation for Missing Health Care Systems Data for Population Health Research

Electronic medical record (EMR) data present many opportunities for population health research. The use of EMR data for population risk models can be impeded by the high proportion of missingness in key patient variables. Common approaches like complete case analysis and multiple imputation may not be appropriate for some population health initiatives that require a single, complete analytic data set. In this study, we demonstrate a sequential hot-deck imputation (HDI) procedure to address missingness in a set of cardiometabolic measures in an EMR data set. We assessed the performance of sequential HDI within the individual variables and a commonly used composite risk score. A data set of cardiometabolic measures based on EMR data from 2 large urban hospitals was used to create a benchmark data set with simulated missingness. Sequential HDI was applied, and the resulting data were used to calculate atherosclerotic cardiovascular disease risk scores. The performance of the imputation approach was assessed using a set of metrics to evaluate the distribution and validity of the imputed data. Of the 567,841 patients, 65% had at least 1 missing cardiometabolic measure. Sequential HDI resulted in the distribution of variables and risk scores that reflected those in the simulated data while retaining correlation. When stratified by age and sex, risk scores were plausible and captured patterns expected in the general population. The use of sequential HDI was shown to be a suitable approach to multivariate missingness in EMR data. Sequential HDI could benefit population health research by providing a straightforward, computationally nonintensive approach to missing EMR data that results in a single analytic data set.

Associations between mindfulness and mental health after collective trauma: results from a longitudinal, representative, probability-based survey

BACKGROUND/OBJECTIVES

Trait mindfulness (TM) may protect against post-trauma mental health ailments and related impairment. Few studies have evaluated this association in the context of collective traumas using representative samples or longitudinal designs.

DESIGN/METHOD

We explored relationships between TM and collective trauma-related outcomes in a prospective, representative, probability-based sample of 1846 U.S. Gulf Coast residents repeatedly exposed to catastrophic hurricanes, assessed twice during the COVID-19 outbreak (Wave 1: 5/14/20-5/27/20; Wave 2: 12/21/21-1/11/22). Generalized estimating equations examined longitudinal relationships between TM, COVID-19-related fear/worry, hurricane-related fear/worry, global distress, and functional impairment; ordinary least squares regression analyses examined the cross-sectional association between TM and COVID-19-related posttraumatic stress symptoms (PTSS) at Wave 1. Event-related stressor exposure was explored as a moderator.

RESULTS

In covariate-adjusted models including pre-event mental health ailments and demographics, TM was negatively associated with COVID-19-related fear/worry, hurricane-related fear/worry, global distress, and functional impairment over time; in cross-sectional analyses, TM was negatively associated with COVID-19-related PTSS. TM moderated the relationship between COVID-19 secondary stressor exposure (e.g., lost job/wages) and both global distress and functional impairment over time.

CONCLUSIONS

Results suggest TM may buffer adverse psychosocial outcomes following collective trauma, with some evidence TM may protect against negative effects of secondary stressor exposure.

Prepregnancy weight loss and maternal metabolic and inflammatory biomarkers during pregnancy: An analysis of National Health and Nutrition Examination Survey

AIM

Women with overweight or obesity are recommended to lose weight before conception to optimize pregnancy outcomes. However, the obstetrical implications of prepregnancy weight loss have been minimally examined. The objective of this study was to investigate the association between prepregnancy weight loss and maternal metabolic and inflammatory profiles during a subsequent pregnancy.

METHODS

This study was a retrospective analysis of National Health and Nutrition Examination Survey data (2003-2018). Participants were women who were pregnant at the time of assessment. Prepregnancy weight loss was described as percent weight change based on self-reported baseline (1 year before pregnancy) and prepregnancy weight. Metabolic (e.g., blood pressure [BP]) and inflammatory biomarkers (i.e., high-sensitivity C-reactive protein [hs-CRP]) were determined by standard medical tests. Statistical analyses included linear regressions with appropriate imputation, weighting, and variance estimation techniques.

RESULTS

Participants (N = 236) reported a mean percent weight loss of 4.6% (standard error [SE] = 0.3%) during the year before pregnancy. Regression models showed that prepregnancy weight loss was inversely associated with levels of total cholesterol (β = -1.24, p = 0.01), low-density lipoprotein-cholesterol (β = -0.79, p < 0.01), and high-density lipoprotein-cholesterol (β = -0.18, p < 0.01). The effect of prepregnancy weight loss on BP, insulin sensitivity, and hs-CRP was not significant, although there was a trend toward higher levels of diastolic BP (β = 0.24, p = 0.07) and hs-CRP (β = 0.10, p = 0.08).

CONCLUSIONS

This study found favorable changes in lipid profiles following prepregnancy weight loss. Due to limitations such as a relatively small sample size, self-reported weight measures, and missing data on several outcome variables, future studies are needed to confirm study findings.

The impact of co-occurring mental health problems on referral to and initiation of treatment among youth under probation supervision: Findings from a cluster randomized trial

INTRODUCTION

Many youth under community supervision have substance use and co-occurring mental health issues. Yet, access to treatment is limited, and many programs cannot address co-occurring disorders. This study examines how co-occurring symptoms among youth on probation affect referral to and initiation of treatment. We hypothesize that both referral and initiation rates will be lower for youth with any co-occurring indicators.

METHODS

This study collected administrative data from 14 sites in three states between March 2014 and November 2017 using JJ-TRIALS, a cluster randomized trial. Among 8552 youth in need of treatment (screened as having a substance use problem, drug possession arrest, positive drug test, etc.), 2069 received a referral to treatment and 1630 initiated treatment among those referred. A co-occurring indicator (n = 2828) was based on symptoms of an internalizing and/or externalizing issue. Descriptive analyses compared referral and initiation by behavioral health status. Two-level mixed effects logistic regression models estimated effects of site-level variables.

RESULTS

Among youth in need with co-occurring internal, external, or both indicators, only 16 %, 18 %, and 20 % were referred to treatment and of those referred, 63 %, 69 %, and 57 % initiated treatment, respectively. Comparatively, 27 % and 83 % of youth with a substance use only indicator were referred and initiated treatment respectively. Multi-level multivariate models found that, contrary to our hypothesis, co-occurring-both (p = 0.00, OR 1.44) and co-occurring-internal indicators (p = 0.06, OR 1.25) predicted higher referral but there were no differences in initiation rates. However, there was substantial site-level variation.

CONCLUSIONS

Youth on probation in need of substance use treatment with co-occurring issues have low referral rates. Behavioral health status may influence youth referral to treatment depending on where a youth is located. Depending on the site, there may be a lack of community programs that can adequately treat youth with co-occurring issues and reduce unmet service needs.

Peripheral magnetic stimulation for chronic peripheral neuropathic pain: A systematic review and meta-analysis

OBJECTIVES

To provide a systematic review of the literature on the effects of peripheral magnetic stimulation (PMS) in the treatment of chronic peripheral neuropathic pain.

METHODS

A systematic search of MEDLINE, EMBASE, CENTRAL, CINHAL, Web of Science, and ProQuest was conducted from inception to July 2023 to identify studies of any design published in English language that enrolled adult patients (≥18 years) that received PMS for treatment of a chronic peripheral neuropathic pain disorder (pain > 3 months).

RESULTS

Twenty-three studies were identified which included 15 randomized controlled trials (RCTs), five case series, two case reports, and one non-randomized trial. PMS regimens varied across studies and ranged from 5 to 240 min per session over 1 day to 1 year of treatment. Results across included studies were mixed, with some studies suggesting benefits while others showing no significant differences. Of nine placebo-controlled RCTs, four reported statistically significant findings in favor of PMS use. In the meta-analysis, PMS significantly reduced pain scores compared to control within 0-1 month of use (mean difference -1.64 on a 0-10 numeric rating scale, 95% confidence interval -2.73 to -0.56, p = 0.003, I2 = 94%, 7 studies [264 participants], very low quality of evidence), but not at the 1-3 months and >3 months of PMS use (very low and low quality of evidence, respectively). Minimal to no adverse effects were reported with PMS use.

DISCUSSION

There is limited and low-quality evidence to make definitive recommendations on PMS usage, however, the available data is encouraging, especially for short-term applications of this novel modality. Large high-quality randomized controlled trials are required to establish definitive efficacy and safety effects of PMS.