Adherence Patterns Research Articles

Prognosis of the geriatric nutritional risk index in medically admitted patients

Background: Schizophrenia leads to multifunctional disability, characterized by cognitive and social impairments, everyday skill and self-assessment difficulties, and negative symptoms. Long-term clinical stability, often achieved with antipsychotics, improves everyday functioning. Aim: The goal is to determine to determine the efficacy of different antipsychotic classes (%Prob of APDs' Resp) and adherence rates, as measured by the Behavioural Adherence Rating Scale (BARS). Methods: The study focuses on schizophrenia-spectrum disorders in adults and elderly psychiatric patients, using established diagnostic systems. The observational and retrospective study will be conducted at the Princess Aisha Bint Al Hussein Medical Centre from January 2021 to January 2023. The study will use positive and negative symptom domains to measure initial severity and assess ideal values for antipsychotic drugs. A Chi Square test will be used to analyze distribution rates and odds ratios. The study will use SPSS version 25 with a 5% significance level. Results: The binary logistic regression model was created using patient adherence patterns evaluated using BARS. The model aimed to predict positive responsiveness (Δ PANSS≥20%) and negative responsiveness (Δ PANSS<20%) using patient data. The model accurately identified 94.4% of cases, with a chi-square value of 4.412 and a p-value of 0.818. BARS testing revealed a probable range of APDs' reaction from 64.4% to 88.2%, with individuals determining this range. The study suggests that the specific range may be different depending on the Cox & Snell R2 or Nagelkerke R2 procedures used, but all factors should be considered. The model's accuracy is significant, and the findings suggest that individuals are responsible for determining this range. Conclusion: The study reveals that psychotic individuals require 68.5% adherence for optimal responsiveness. Adding LAIAP to oral APDs enhances responsiveness.

Patterns of Adherence to Home Blood Pressure Monitoring Among Older Adults With Ischemic Heart Disease: An Analysis From the RESILIENT Trial of Mobile Health Cardiac Rehabilitation.

Hypertension (HTN) is common and represents a major modifiable risk factor for ischemic heart disease in older adults. While home blood pressure monitoring (HBPM) is important in HTN management, patterns of HBPM engagement in older adults undergoing mobile health cardiac rehabilitation (mHealth-CR) are unknown. We aimed to identify patterns of adherence to HBPM in a cohort of older adults undergoing mHealth-CR to optimize HBPM use in the future. We used interim data from the ongoing Rehabilitation using Mobile Health for Older Adults with Ischemic Heart Disease in the Home Setting (RESILIENT) randomized trial, in which intervention arm participants (adults≥65years with ischemic heart disease) were instructed to monitor blood pressure (BP) at least weekly. Engagement groups were determined by latent class analysis and compared using ANOVA or Chi-Square tests. Longitudinal mixed effect modeling determined the associations between weekly HBPM and baseline covariates including uncontrolled HTN, obesity, diabetes, depression, alcohol, and tobacco use. Of the 111 participants, the mean age was 71.9±5.6years, and 83% had HTN. Over the 12-week study, mean HBPM engagement was 2.3±2.3d/wk. We observed 3 distinct patterns of engagement: high engagement (22%), gradual decline (10%), and sustained baseline engagement (68%). HBPM adherence decreased in two of the engagement groups over time. Of the covariates tested, only depression was associated with weekly HBPM after adjusting for relevant covariates (OR 9.09, P =.03). In this older adult cohort undergoing mHealth-CR, we found three main engagement groups with declining engagement over time in two of the three groups. These patterns can inform future mHealth-CR interventions.

A brief report: Lessons learned using wearable technology to collect data from adults receiving medications for opioid use disorder

ABSTRACT Background Incorporating wearable technology into substance use disorder research enables continuous, objective, and remote data collection, facilitating symptom monitoring to prevent relapse. However, implementation challenges may hinder data collection. This paper aims to assess adherence patterns to a wrist-worn wearable device, and to share lessons learned from incorporating wearable technology to collect physiological data from adults with opioid use disorder. Methods Employing a prospective observational design, we used convenience sampling to recruit adults receiving medications for opioid use disorder in outpatient settings. Wearable adherence was measured by days and nights worn over eight weeks, acceptability by a visual analog scale, and anecdotal notes tracked study activities and challenges. Results Twenty-three participants completed baseline, and 16 (70.0%) completed the study. Daytime and nighttime wearable adherence averaged 60.1% and 47.7%, respectively. Wearable adherence was highest at the earlier phase of the study (67.7%) and plateaued after overtime. User-related and technical challenges included digital illiteracy, protocol nonadherence, low motivation, measurement errors, and short battery life. Unique challenges included wearable design concerns and sleep problems. Conclusions This study demonstrates the feasibility of wearable use and highlights the potential to overcome challenges. Proactively sharing insights can facilitate wearable technology adoption for both participants and researchers.

Novel assessment of CPAP adherence data reveals distinct diurnal patterns.

Obstructive sleep apnea (OSA) is a prevalent condition effectively treated by continuous positive airway pressure (CPAP) therapy. CPAP adherence data, routinely gathered in clinical practice, include detailed information regarding both duration and timing of use. The purpose of the present study was to develop a systematic way to measure the diurnal pattern of CPAP adherence data and to see if distinct patterns exist in a clinical cohort. Machine learning techniques were employed to analyze CPAP adherence data. A cohort of 200 unselected patients was assessed and a cluster analysis was subsequently performed. Application of this methodology to 17 patients with different visually noted patterns was carried out to further assess performance. Each 30-day period of CPAP use for each patient was characterized by four variables describing the time of day of initiation and discontinuation of CPAP use, as well as the consistency of use during those times. Further analysis identified six distinct clusters, reflecting different timing and adherence patterns. Specifically, clusters with relatively normal timing versus delayed timing were identified. Finally, application of this methodology showed generally good performance with limitations in the ability to characterize shift worker and non-24 rhythms. This study demonstrates a methodology for analysis of diurnal patterns from CPAP adherence data. Furthermore, distinct timing and adherence patterns are demonstrated. The potential impact of these patterns on the beneficial effects of CPAP requires elucidation.

Guideline concordant opioid therapy in Veterans receiving VA and community care

Guideline concordant opioid therapy is a key part of the concerted effort to address the opioid crisis in the United States. The study aimed to compare the rates of guideline concordant care between veterans who solely used VA services (mono users) and veterans who used both VA services and community care (dual-system users). We used electronic health record data from the Washington DC and Baltimore VA Medical Centers from 2015 to 2019. We provided descriptive statistics as well as generalized estimating equations models to find associations between mono vs. dual-system users and each guideline outcome, controlling for demographic factors and comorbid conditions. The study found that overall rates of guideline concordant care were high in both mono and dual-system users with over 90% adherence rates for the majority of recommendations. However, there were variations in adherence to specific guidelines, with urine drug screening at initiation being the least commonly followed recommendation (8.9% of mono-user opioid initiators and 11.2% of dual-user initiators). This study also found that there was no consistent pattern of higher guideline adherence in mono vs. dual-system users but did show that through the course of this study (2015–2019) overall rates of guideline concordance increased. Future research will explore additional guideline recommendations and potential coordination issues among dual-system users.

Changes in Antipsychotic Medication Adherence Among Medicaid Beneficiaries with Schizophrenia During COVID-19.

To identify patterns of medication adherence during the pandemic and factors associated with these patterns among Medicaid-enrolled individuals with schizophrenia who had highly adherent medication use prior to the COVID-19 pandemic. We used Medicaid claims from Philadelphia to identify individuals with schizophrenia ≥ 18years of age, their demographic characteristics, and health service use. We used group trajectory models to identify adherence trends, and ANOVA to examine associations between adherence groups and demographic characteristics and service use. The sample included 1,622 individuals. A 4-group trajectory model best fit our data. Seventy percent of individuals averaged about 92% adherence throughout the study period; 10% experienced a pronounced decline when the pandemic started (pandemic non-adherers); 11% experienced a sharp decline mid-pandemic (late non-adherers); and 9% experienced a sharp decline at the beginning of the pandemic and returned to higher adherence after a year (disrupted adherers). Adherers were least likely to be diagnosed with a substance use disorder, and had more telehealth visits, mental health outpatient visits, and fewer emergency department visits on average. Late non-adherers were more likely than adherers to have substance use disorders and physical health conditions. Pandemic non-adherers had more co-occurring psychiatric disorders than adherers and had the lowest use of case management. Three in ten previously adherent individuals with schizophrenia became less adherent to antipsychotic medications, either at the onset or later in the pandemic. Our findings point to telehealth and case management as critical strategies for treatment engagement, especially during public health crises, and well as the need to address co-occurring conditions.

Interventional Pharmacoepidemiology: Origins, Current Status, and Future Possibilities.

Interventional pharmacoepidemiology applies quantitative analysis of patterns of medication use and outcomes to help design, guide and then evaluate programs to improve prescription drug use and outcomes. Surveillance of prescribing and drug-taking in large populations is increasingly practical because of the proliferation of detailed data on medication use decisions, often based on paid claims billing data. At the same time, increasingly granular clinical information is available on patient characteristics and outcomes. This can offer important opportunities to identify problematic use, focus interventions to address them, and measure their impact. Alexander et al (Am J Epidemiol. 0000;000(00):0000-0000) review the need for such research and provide methodological guidance for its performance. While randomized controlled trials of such interventions are ideal, real-world considerations often require other evaluation strategies, including stepped-wedge designs and interrupted time-series analysis. As drug therapy becomes more powerful and more costly, and the risks of poor medication choices as well as under-use of effective treatments become even better understood, the health care system will increasingly rely on such approaches to assess current patterns of prescribing and patient adherence, target programs to address problem areas, and measure the effectiveness of such interventions.

6818 Adherence Risk Management in Patients on Recombinant Human Growth Hormone Therapy, With Traffic Light Alerting Systems Tailored for Both Weekday and Weekend Adherence

Abstract Disclosure: S. Loche: Advisory Board Member; Self; SL has received advisory board fees from Merck KGaA, Darmstadt, Germany. Consulting Fee; Self; SL has received consultancy fees from Merck KGaA, Darmstadt, Germany. Speaker; Self; SL has received lecture fees from Merck KGaA, Darmstadt, Germany. P. van Dommelen: Consulting Fee; Self; PvD has a consultancy agreement with Merck KGaA, Darmstadt, Germany. V. Tornincasa: Employee; Self; VT is an employee of Ares Trading SA, an affiliate of Merck KGaA. L. Arnaud: Employee; Self; LA is an employee of Ares Trading SA, an affiliate of Merck KGaA. E. Koledova: Employee; Self; EK is an employee of Merck KGaA,Darmstadt, Germany. Stock Owner; Self; EK is an employee of Merck KGaA,Darmstadt, Germany. Background: The integration of data-driven strategies, such as clustering analysis with an alerting system, empowers healthcare professionals with actionable insights. In this study, we focused on clustering adherence patterns during the weekdays and weekends in the first 12 weeks of treatment. Our aim is to develop a data-driven clinical decision support system based on "traffic light" visualizations addressing adherence challenges during both weekdays and weekends in patients receiving Recombinant Human Growth Hormone Therapy. Data and Methods: Adherence data between March-November 2023 were extracted from the newly launched third generation of easypod™ device (EP3) and GrowZen Connect Next ecosystem. EP3 is the only connected device that delivers r-hGH and monitors real-time adherence to therapy. EP3 was perceived by health care professionals as more intuitive, comfortable, user-friendly, simpler, and easier to use than previous EP2. Patients with age 2-18 years at treatment start, a 7-day regimen and complete adherence data available between 1-12 weeks of treatment were selected. Patients’ adherence to therapy was represented using mean and standard deviation (SD) of adherence (%) and the interquartile range (IQR) of the timing of injections throughout the day in minutes aggregated by weekday (Monday-Thursday) and weekend day (Friday-Sunday). Cluster analysis was used to categorize adherence patterns using a Gaussian mixture model. Following a traffic lights-inspired visualization approach, the algorithm was set to create three clusters: high (green), medium (yellow), and low adherence (red). The area under the receiver operating characteristic curve (AUC-ROC) was used to find optimum thresholds for independent traffic lights. Results: Data for 232 patients (124 boys and 108 girls, median (Q25-Q75) age at treatment start was 10.5 (7.6-12.3)) were available. The most appropriate traffic light used the SD of adherence during the weekend, with an AUC-ROC value of 0.87. For the weekday, adherence-based traffic lights using optimum thresholds were >98% (SD<10.2), 88-98% (SD:10.2-22.8) and <88% (SD>22.8) for high, medium, and low adherence, respectively. For IQR of the timing of injections throughout the weekday, optimum thresholds were <38, 38-70 and >70 (min). For the weekend, optimum thresholds were >96% (SD<7.7), 86-96% (SD:7.7-21.5) and <86% (SD>21.5). For IQR of the timing of injections throughout the weekend, optimum thresholds were <56, 56-84 and >84 (min). Conclusions: Our research indicates that implementing a practical data-driven alert system, utilizing our proposed traffic-light coding, would empower healthcare practitioners to monitor patients' adherence to growth hormone therapy comprehensively. By understanding patient behavior during the weekdays and weekend, healthcare practitioners can tailor interventions for improved treatment outcomes. Presentation: 6/3/2024

6778 Visual Presentations for Adherence Risk Management In Patients Receiving Recombinant Human Growth Hormone Therapy

Abstract Disclosure: P. van Dommelen: Consulting Fee; Self; PvD has a consultancy agreement with Merck KGaA, Darmstadt, Germany. F. Michelis: Employee; Self; FL is an employee of Ares Trading SA, an affiliate of Merck KGaA. L. Arnaud: Employee; Self; LA is an employee of Ares Trading SA, an affiliate of Merck KGaA. S. Loche: Advisory Board Member; Self; SL has received advisory board fees from Merck KGaA, Darmstadt, Germany. Consulting Fee; Self; SL has received consultancy fees from Merck KGaA, Darmstadt, Germany. Speaker; Self; SL has received lecture fees from Merck KGaA, Darmstadt, Germany. E. Koledova: Employee; Self; EK is an employee of Merck KGaA,Darmstadt, Germany. Stock Owner; Self; EK holds shares in Merck KGaA, Darmstadt, Germany. Background: A data-driven clinical decision support system based on visual presentations for adherence risk management can support patients receiving recombinant human growth hormone (r-hGH) treatment. Our focus is on examining adherence patterns during the first 6 weeks of treatment, with a particular emphasis on the days of the week, the variability in injection timings and the summer holiday. Our aim is to assess whether these early patterns can serve as indicators for predicting adherence in the subsequent 7-12 weeks of treatment. Data and Methods: Adherence data between March-November 2023 were extracted from the newly launched third generation of easypod™ device (EP3) and GrowZen Connect Next ecosystem. EP3 is the only connected device that delivers r-hGH and monitors real-time adherence to therapy. EP3 was perceived by health care professionals as more intuitive, comfortable, user-friendly, simpler, and easier to use than previous EP2. Patients with age 2-18 years at treatment start, a 7-day regimen and complete adherence data available between 1-12 weeks of treatment were selected. Data about sex, age at start treatment, as well as adherence, classified as high (≥95%) versus low/medium <95%), standard deviation (SD) of adherence (%), log (to adjust for skewness) of the interquartile range (IQR) of the timing of injection throughout the day, median timing of the injection after midnight, and ≥50% versus <50% of the injections fall in the summer period (July-August) aggregated by day over the first 6 weeks of treatment were included in a generalized linear mixed model with adherence between 7-12 weeks as outcome. Results: In total, data for 232 patients (124 boys and 108 girls, median (Q25-Q75) age at treatment start was 10.5 (7.6-12.3)) were available. The model showed no difference in effect of adherence rates during Monday-Thursday. We, therefore, aggregated the data by weekday (Monday-Thursday) versus weekend day (Friday-Sunday, Friday was included due to the common practice of administering injections during the evening). Adherence, SD of adherence, IQR of timing of injections, and injections falling in summer were significant (p<0.05) predictors of adherence during a weekday and weekend between 7-12 weeks. Areas under the curves were both 0.96 during the weekday and weekend. Conclusions: Our research shows that adherence and timing of injections, as well as taking into account the summer holidays, can predict future adherence accurately. Visual presentations showing aggregated adherence rates and variation of timing of injections by days of the week, as well as highlighting the summer periods may improve adherence risk management and timely support. Presentation: 6/3/2024

Medication adherence patterns and factors associated with non – adherence among patients receiving psychotropic medication in a tertiary care hospital

Medication adherence patterns and factors associated with non – adherence among patients receiving psychotropic medication in a tertiary care hospital

Evaluation of health-related quality of life and adherence among pre-extensively drug-resistant tuberculosis patients receiving either Bedaquiline or Delamanid regimen at a teaching hospital in Eastern India

ABSTRACT Background: The foremost concern and challenge in managing drug-resistant tuberculosis is ensuring a high health-related quality of life (HRQoL). The effectiveness of pre-extensively drug-resistant (Pre-XDR) tuberculosis management hinges on patients adhering to therapy, a crucial factor in averting the development of drug-resistant strains, ultimately enhancing HRQoL. Methodology: This analytical longitudinal study spanned two years at a teaching hospital and involved collaboration between the Departments of Pharmacology and Pulmonary Medicine. A case record form was utilized to gather baseline data, encompassing patient demographics, medication details, WHO BREF HRQoL scores, and treatment adherence. Patients were classified as either adherent or nonadherent using three distinct criteria: the guidelines of the Revised National Tuberculosis Programme (RNTCP), the Morisky-Green-Levine Scale (MGLS), and the Batalla test. The sample size was determined based on 30% nonadherence rates from preliminary analysis of prior data, resulting in 86 patients included in the study. The association between the improvement of HRQoL score from the baseline with the predictor variables was assessed with a linear regression model. Comparison of nonadherence with the different predictors of the study population was assessed with binary logistic regression model. Results: Analysis of demographic data revealed no notable differences in age and BMI between the Bedaquiline and Delamanid groups. However, there was a gender-related difference in treatment distribution, with more men in the Bedaquiline group. Other factors, such as marital status, socioeconomic status, employment status, stigma/discrimination, comorbidity, and addiction, showed no significant differences between the groups. Comparing HRQoL scores at baseline and after six months showed substantial improvements in all domains, indicating a positive impact of the treatment. Linear regression analysis revealed a strong association between QoL improvement and adherence. Adherence patterns did not significantly differ between the two treatment groups, as assessed by various criteria. The patients with high stigma, newly diagnosed Pre-XDR cases, and the presence of adverse events had higher odds of nonadherence. Conclusion: This study highlights the substantial impact of Bedaquiline and Delamanid treatment on the HRQoL of Pre-XDR TB patients in Eastern India. Adherence to treatment plays a crucial role in improving QoL, and factors like stigma, newly diagnosed Pre-XDR patients, and adverse drug reactions influence adherence adversely. The findings emphasize the importance of patient support and education to enhance treatment outcomes.

Adherence Patterns and Health Outcomes in Spanish Young Women Participating in a Virtual-Guided HIIT Program: Insights from the Randomized Controlled WISE Trial

Background/Objectives. A notable decline in physical activity from late adolescence to early adulthood affects young women especially. This study aimed to investigate adherence to an unsupervised virtual-guided high-intensity interval training (HIIT) exercise program among young women in Spain. Methods. A total of 106 participants were recruited and randomized to the Women’s Involvement in Steady Exercise (WISE) trial exercise program, administered remotely via a mobile app, and a control group. The primary outcome was adherence measured through daily steps. Secondary variables were patient-reported outcomes of physical activity, quality of sleep, and quality of life, assessed with the International Physical Activity Questionnaire (IPAQ), the Pittsburgh Sleep Quality Index (PSQI), and the Health Lifestyle and Personal Control Questionnaire (HLPCQ), respectively. The assessments were performed over 6 months, before the intervention (T0), at the halfway of the program (T1), and at the end (T2). Results. Daily steps revealed a decrease from baseline to final assessment in both groups. Secondary outcomes indicated a shift in physical activity levels, showing a transition from low to moderate and high activity perception. While sleep quality deteriorated post-intervention, quality of life showed no changes. Conclusions. The WISE trial highlights the potential and challenges of an unsupervised virtual-guided HIIT program for young women. While an improvement in physical activity levels was noticed, it also led to a decrease in daily steps and poorer sleep quality. These findings suggest a complex relationship between exercise and lifestyle factors, which could potentially have the greatest impact.

Exploring disparities: A comparative analysis of insulin-naïve, regular users, and inertia patients among type 2 diabetes mellitus outpatients in India

ABSTRACT Introduction: Insulin utilization pattern varies greatly in type 2 diabetes mellitus (T2DM) patients. Clinical inertia in treatment intensification hinders glycemic control in T2DM management. This study investigated insulin prescription trends and various predictors among insulin naive, user, and insulin inertia (II) patients in T2DM. Methodology: A retrospective analysis of T2DM patient records from the diabetes clinic at a tertiary care center was conducted. Data on socio-demographics, anthropometry, disease characteristics, comorbidities, adherence, and medication prescribing patterns were collected. Analysis was done using tests of significance, odds ratio (OR), and multivariate logistic regression. Results: A total of 950 records were analyzed, with 17.3% of patients identified as insulin users (IU), 70.9% being insulin-naïve (IN), and 11.8% having II. IUs had significantly higher glycemic levels including HbA1c, fasting, postprandial, and random blood sugars compared to the other groups. Higher HbA1c levels were associated with significantly increased odds of insulin usage (OR: 3.46, confidence interval (CI): 1.94–6.16), while individuals taking sulfonylureas had lower odds of insulin usage (OR: 0.27, CI: 0.08–0.91). A significant association was also seen with the total number of oral antidiabetic drugs prescribed (four drugs; OR: 15.6, and five drugs; OR: 9.1). Other factors did not show a significant association. The regression model showed HbA1c level as low as 7.9% could indicate a future insulin requirement in 22% of patients. Conclusion: The study outlines differences in characteristics and parameters among T2DM patients who require or do not require insulin and highlights the challenges in insulin initiation in Indian T2DM patients. Findings on II underscore the need for timely treatment intensification.

Trajectories of Adherence to Oral Pre-exposure Prophylaxis and Risks of HIV and Sexually Transmitted Infections.

Pre-exposure prophylaxis (PrEP) effectiveness is highly dependent on medication adherence, which is associated with differential HIV risks and possibly sexually transmitted infection (STI). This retrospective cohort study of PrEP users (01/01/2012-12/31/2021) used the MarketScan database of commercially insured enrollees to examine PrEP adherence trajectory groups' associations with HIV and STI acquisition risks. Distinct PrEP adherence trajectories were identified by group-based trajectory modeling among individuals who used oral PrEP. The primary outcome was HIV acquisition incidence, and secondary was STI rate, compared among trajectory groups. Inverse probability treatment weighting time-varying Cox proportional hazards models assessed HIV acquisition, and Poisson regression models assessed STI. Among 23 258 oral PrEP users, 4 distinct PrEP adherence patterns were identified: minimal use (10.5% of the cohort), rapidly declining (25.4%), gradually declining (24.3%), and consistently high (39.8%). Compared with the minimal use group, the gradually declining (adjusted hazard ratio [AHR], 0.53; 95% CI, 0.31-0.90) and consistently high (AHR, 0.50; 95% CI, 0.30-0.84) PrEP adherence groups showed decreased HIV incidence risks. Compared with the minimal use group, the rapidly declining (adjusted incidence rate ratio [AIRR], 1.35; 95% CI, 1.07-1.72), gradually declining (AIRR, 1.73; 95% CI, 1.38-2.18), and consistently high (AIRR, 2.06; 95% CI, 1.64-2.58) groups were associated with increased STI risk. These findings underscore the benefits of continuing and remaining adherent to PrEP and may also inform public health strategies, clinical guidelines, and interventions aimed at maximizing the effectiveness of PrEP in reducing new HIV infections while developing targeted strategies to prevent STIs with PrEP use.

Abstract A162: The influence of parental barriers to healthcare on adolescent HPV vaccination uptake and completion among Latinos in Los Angeles

Abstract Objective: This study aims to investigate the association between parental barriers to healthcare access and HPV vaccination uptake among Latino adolescents in Los Angeles. Background: Human papillomavirus (HPV) induced cervical cancer (CC) remains a significant public health concern. Routine HPV vaccination has been recommended in the United States for girls since 2006 and boys since 2011 yet disparities in vaccine initiation and completion persist, particularly among Latino adolescents in Los Angeles. Methods: This cross-sectional study analyzed child data provided by mothers recruited from the Es Tiempo campaign (2016-2018). A total of 353 Latino adolescents aged 9 to 26 years were included in the sample. We used crosstabs to assess vaccine initiation and completion differences by child sex and birth order, while logistic regression models were used to evaluate the association between parental barriers to healthcare, such as lack of health insurance and access to a primary care provider (PCP), and HPV vaccination initiation. Results: Among the sample, 44% initiated the HPV vaccine, and 23% completed the series, with significantly higher rates among girls and firstborn children. Regarding barriers, lack of health insurance was associated with decreased odds of HPV vaccination uptake while access to a PCP showed a slight increase in vaccination uptake odds. Conclusion: HPV vaccination uptake among Latino adolescents in Los Angeles remains suboptimal, with disparities observed by gender and birth order. To improve public health outcomes, targeted interventions are needed to increase HPV vaccination uptake among Latino adolescent boys, and further research is needed to understand vaccine adherence patterns within families and among siblings. Moreover, while parental barriers to healthcare may influence vaccination uptake, future studies should also explore how factors like parental education level and socioeconomic status influence HPV vaccination status in combination with access barriers. Citation Format: Anju F. Kane, Lourdes Baezconde-Garbanati. The influence of parental barriers to healthcare on adolescent HPV vaccination uptake and completion among Latinos in Los Angeles [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A162.

Abstract B007: Racial/ethnic and socioeconomic disparities in over- and under-screening of cervical cancer among a national sample of commercially insured individuals

Abstract In the United States (US), disparities in cervical cancer screening uptake persist by race/ethnicity and socioeconomic status (SES). However, few have examined how race/ethnicity and SES contribute to specific guideline adherence patterns, which can exacerbate existing disparities. We investigated the impact of race/ethnicity and SES (education and household net worth [HHN]) on the probability of over- and under-screening. Optum Clinformatics Data Mart from 2012-2021 was used to identify average-risk females aged 30-64 and ≥1 cervical cancer screening with continuous health plan enrollment and no history of hysterectomy/cervical cancer. Over- and under-screening were defined as intervals between the index and subsequent screening which were shorter and longer than the interval recommended by the 2012 US Preventive Services Task Force guideline, respectively. Multivariate logistic regression was used to evaluate the association of race/ethnicity (Non-Hispanic [NH]-White, NH-Asian, Hispanic, NH-Black) and SES including HHN (<$250,000, $250,000-$500,000, >$500,000) and education level (<Bachelor’s Degree, >Bachelor’s Degree) with over- and under-screening. We tested for interactions between race/ethnicity and SES. Of the 686,884 eligible patients, 72.8% were NH-White, 71.4% had <Bachelor's Degree and 43.3% had HHN <$250,000. Only 7.2% were guideline adherent, 30.7% were under-screened, and 62.1% were over-screened. After regression adjustment, the odds of under-screening were higher among NH-Asian (OR, 1.2; 95%CI, 1.1- 1.2), NH-Black (OR, 1.1; 95%CI, 1.0-1.1), and Hispanic (OR, 1.2; 95%CI, 1.1-1.2) vs NH-White, <Bachelor’s degree (OR, 1.1; 95%CI, 1.0-1.1) vs >Bachelor’s degree, and HHN <$250,000 (OR, 1.3 95%CI, 1.2-1.3) and $250,000-$499,000 (OR, 1.1; 95%CI, 1.0-1.1) vs >$500,000. Odds of over-screening were higher among NH-Black (OR, 1.3; 95%CI, 1.2-1.3), and Hispanic (OR, 1.2; 95%CI, 1.1-1.2) vs NH-White, and lower among <Bachelor’s degree (OR, 0.9; 95%CI, 0.8-0.9) vs >Bachelor’s degree, and HHN <$250,000 (OR, 0.9; 95%CI, 0.9-1.0) and $250,000-$499,000 (OR, 0.9; 95%CI, 0.9-1.0) vs >$500,000. For under-screening, the interaction between race/ethnicity and HHN was significant, and the predicted probability (PP) increased with higher HHN among Hispanic but not in other groups (p<0.01). For over-screening, the interaction between race/ethnicity and HHN was significant and the PP increased with higher HHN among Hispanic and NH-White but decreased for NH-Black and NH-Asian. The interaction between race/ethnicity and education was significant and the PP increased with higher education among Hispanic and NH-White but decreased among NH-Black and NH-Asian. Even within a commercially insured population, we observed that the majority of patients received non-guideline adherent screening and SES contributed to disparities differently among racial/ethnic groups. Findings indicate the need to tailor interventions and policies for subpopulations experiencing over- and under-screening to address the overall screening quality and disparities in outcomes. Citation Format: Michelle B. Shin, Sarah Axeen, Jennifer Tsui. Racial/ethnic and socioeconomic disparities in over- and under-screening of cervical cancer among a national sample of commercially insured individuals [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B007.

Predicting Adherence to Computer-Based Cognitive Training Programs Among Older Adults: Study of Domain Adaptation and Deep Learning.

Cognitive impairment and dementia pose a significant challenge to the aging population, impacting the well-being, quality of life, and autonomy of affected individuals. As the population ages, this will place enormous strain on health care and economic systems. While computerized cognitive training programs have demonstrated some promise in addressing cognitive decline, adherence to these interventions can be challenging. The objective of this study is to improve the accuracy of predicting adherence lapses to ultimately develop tailored adherence support systems to promote engagement with cognitive training among older adults. Data from 2 previously conducted cognitive training intervention studies were used to forecast adherence levels among older participants. Deep convolutional neural networks were used to leverage their feature learning capabilities and predict adherence patterns based on past behavior. Domain adaptation (DA) was used to address the challenge of limited training data for each participant, by using data from other participants with similar playing patterns. Time series data were converted into image format using Gramian angular fields, to facilitate clustering of participants during DA. To the best of our knowledge, this is the first effort to use DA techniques to predict older adults' daily adherence to cognitive training programs. Our results demonstrated the promise and potential of deep neural networks and DA for predicting adherence lapses. In all 3 studies, using 2 independent datasets, DA consistently produced the best accuracy values. Our findings highlight that deep learning and DA techniques can aid in the development of adherence support systems for computerized cognitive training, as well as for other interventions aimed at improving health, cognition, and well-being. These techniques can improve engagement and maximize the benefits of such interventions, ultimately enhancing the quality of life of individuals at risk for cognitive impairments. This research informs the development of more effective interventions, benefiting individuals and society by improving conditions associated with aging.

Adherence to non-pharmaceutical interventions following COVID-19 vaccination: a federated cohort study

In pandemic mitigation, strategies such as social distancing and mask-wearing are vital to prevent disease resurgence. Yet, monitoring adherence is challenging, as individuals might be reluctant to share behavioral data with public health authorities. To address this challenge and demonstrate a framework for conducting observational research with sensitive data in a privacy-conscious manner, we employ a privacy-centric epidemiological study design: the federated cohort. This approach leverages recent computational advances to allow for distributed participants to contribute to a prospective, observational research study while maintaining full control of their data. We apply this strategy here to explore pandemic intervention adherence patterns. Participants (n = 3808) were enrolled in our federated cohort via the “Google Health Studies” mobile application. Participants completed weekly surveys and contributed empirically measured mobility data from their Android devices between November 2020 to August 2021. Using federated analytics, differential privacy, and secure aggregation, we analyzed data in five 6-week periods, encompassing the pre- and post-vaccination phases. Our results showed that participants largely utilized non-pharmaceutical intervention strategies until they were fully vaccinated against COVID-19, except for individuals without plans to become vaccinated. Furthermore, this project offers a blueprint for conducting a federated cohort study and engaging in privacy-preserving research during a public health emergency.

Current Insights on Treatment Adherence in Prevalent Dermatological Conditions and Strategies To Optimize Adherence Rates.

Adherence to prescribed medication regimens is crucial for treatment efficacy and patient safety, but it remains a challenge in the medical field, particularly in dermatology, where adherence to prescribed treatments is being intensively evaluated and improved. This narrative review provides a comprehensive overview of adherence behaviors in dermatological diseases, including fungal skin infections, psoriasis, acne, atopic dermatitis, and chronic urticaria, aiming to update scientific information on adherence patterns and management strategies in these highly prevalent conditions. Furthermore, the importance of a holistic approach that integrates patient-centered and physician-centered strategies to optimize treatment outcomes and enhance adherence in dermatological care is highlighted. The role of technological advancements in promoting adherence is also discussed, with an emphasis on the potential for digital solutions to facilitate medication management. Future perspectives underscore the need for targeted interventions to address the multifaceted barriers to adherence, including treatment complexity, healthcare accessibility, and patient-provider communication. By addressing these challenges, healthcare providers can enhance patient satisfaction, improve therapeutic outcomes, and mitigate the adverse consequences of non-adherence in dermatological practice.

Pattern of Utilization of Antenatal Care Services and Adherence Among Females Following Up at Primary Healthcare Centers in Al-Ahsa.

Background Antenatal care (ANC) is a crucial component of maternal and child health, yet disparities in utilization persist globally. This study aimed to assess the patterns of ANC service utilization and adherence among pregnant women attending primary healthcare centers (PHCCs) in Al-Ahsa, Saudi Arabia. Methodology A quantitative, cross-sectional study was conducted among 277 women attending PHCCs in Al-Ahsa. Data were collected through structured questionnaires, assessing demographic characteristics, ANC follow-up patterns, structural and personal barriers, and mental health conditions using the Depression, Anxiety, and Stress Scale. Results Significant regional variations in ANC follow-up patterns were observed, with higher proportions of pregnant women attending ANC in the Middle and Eastern regions. Prominent structural barriers included transportation challenges (structural barrier 3, 61.0%) and limited service availability (structural barrier 6, 56.0%), while personal barriers encompassed transportation problems (personal barrier 6, 36.8%) and forgetfulness regarding appointments (personal barrier 4, 19.9%). Mental health assessments revealed predominantly normal levels of depression, anxiety, and stress, with some regional variations in distress levels. Conclusions The study highlights regional disparities in ANC service utilization and adherence, influenced by structural barriers, personal barriers, and mental health conditions. Tailored interventions addressing these barriers, improving access to care, and providing targeted support are crucial for enhancing ANC service utilization and promoting maternal and child health in Al-Ahsa.