Associations of Comorbid Anxiety With Medication Adherence and Psychiatric Symptomatology in a Population of Nonadherent Bipolar Disorder Subjects.
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ABSTRACT:
SUBMITTER: Aftab A
PROVIDER: S-EPMC5876117 | biostudies-literature | 2018 Apr
REPOSITORIES: biostudies-literature
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Project description:Objective Serious mental illness and type II diabetes mellitus have a high comorbidity, and both have a higher prevalence of anxiety disorders compared to the general population. Targeted Training in Illness Management is a group-based self-management training approach which targets serious mental illness and type II diabetes mellitus concurrently. This analysis examines data from a randomized controlled trial of Targeted Training in Illness Management intervention to examine the impact of comorbid anxiety on baseline psychiatric symptomatology and diabetic control, and on longitudinal treatment outcomes. Methods We conducted secondary analyses on data from a prospective, 60-week, randomized controlled trial testing Targeted Training in Illness Management versus treatment as usual in 200 individuals with serious mental illness and diabetes. Primary outcomes included measures related to serious mental illness symptoms, functional status, general health status, and diabetes control. Measures were compared between those participants with anxiety disorders versus those without anxiety at baseline as well as over time using linear mixed effects analyses. Results Forty seven percent of the participants had one or more anxiety disorders. At baseline, those with an anxiety diagnosis had higher illness severity, depressive, and other psychiatric symptomatology and disability. Diabetic control (HbA1c) was not significantly different at baseline. In the longitudinal analyses, no significant mean slope differences over time (group-by-time interaction effect) between those with anxiety diagnoses and those without in treatment as usual group were found for primary outcomes. Within the Targeted Training in Illness Management arm, those with anxiety disorders had significantly greater improvement in mental health functioning. Those with anxiety comorbidity in the Targeted Training in Illness Management group demonstrated significantly lower HbA1c levels compared to no anxiety comorbidity and also demonstrated a greater improvement in HbA1c over the first 30 weeks compared to those without anxiety comorbidity. Conclusion Comorbid anxiety in serious mental illness and type II diabetes mellitus population is associated with increased psychiatric symptomatology and greater disability. Individuals from this population appear to experience greater improvement in functioning from baseline with the Targeted Training in Illness Management intervention. Anxiety comorbidity in the serious mental illness and type II diabetes mellitus population does not appear to have a negative impact on diabetic control. These complex relationships need further study. Clinical Trials Registration ClinicalTrials.gov: Improving outcomes for individuals with serious mental illness and diabetes (NCT01410357).
| S-EPMC5919280 | biostudies-literature
Project description:BACKGROUND:Selective serotonin reuptake inhibitors (SSRIs) are the recommended first-line pharmacotherapy for pediatric anxiety disorders but adherence remains difficult to predict. OBJECTIVES:To estimate SSRI adherence in children with anxiety disorders and determine if prior parental medication adherence is predictive of child high SSRI adherence. METHODS:We identified children (3-17?y) initiating SSRI treatment after an anxiety disorder diagnosis in a commercial claims database (2005-2014). We evaluated parent SSRI, statin, and antihypertensive adherence [6-mo proportion days covered (PDC), high adherence=PDC?0.80] in the year before child SSRI initiation. We estimated risk differences (RD) of child high SSRI adherence (6-mo PDC) stratified by parent adherence and multivariable risk ratios using modified Poisson regression. We estimated change in c-statistic and risk reclassification when adding parent-level covariates with child-level covariates to predict child adherence. RESULTS:In 70,979 children with an anxiety disorder (59%=female, 14=median age), the mean 6-month SSRI PDC was 0.72, with variation by anxiety disorder. Overall 64% of children had high adherence if their parent had high SSRI adherence versus 53% of children with parents with low SSRI adherence (RD, 12%; multivariable risk ratios, 1.17; 95% confidence interval, 1.14-1.20). Findings were similar for parent statin (RD=10%) and antihypertensive adherence (RD=8%) and when stratified by child age and parent sex. There was minor improvement in risk reclassification and the c-statistic after adding parent adherence and parent-level covariates. CONCLUSIONS:Parental medication adherence could help providers identify children at risk of nonadherence to inform the treatment decision, reduce unnecessary medication switches, and lead to broader effective interventions.
| S-EPMC5945329 | biostudies-literature
Project description:Adherence to medications remains poor despite numerous efforts to identify and intervene upon nonadherence. One potential explanation is the limited focus of many interventions on one barrier. Little is known about the prevalence and impact of having multiple barriers in contemporary practice. Our objective was to quantify adherence barriers for patients with poorly controlled cardiometabolic condition, identify patient characteristics associated with having multiple barriers, and determine its impact on adherence. We used a linked electronic health records and insurer claims dataset from a large health system from a recent pragmatic trial. Barriers to medication taking before the start of the intervention were elicited by clinical pharmacists using structured interviews. We used multivariable modified Poisson regression models to examine the association between patient factors and multiple barriers and multivariable linear regression to evaluate the relation between multiple barriers and claims-based adherence. Of the 1,069 patients (mean: 61 years of age) in this study, 25.1% had multiple barriers to adherence; the most common co-occurring barriers were forgetfulness and health beliefs (31%, n?=?268). Patients with multiple barriers were more likely to be non-white (relative risk [RR] 1.57, 95% confidence interval [CI] 1.21 to 1.74), be single/unpartnered (RR 1.36, 95% CI 1.06 to 1.74), use tobacco (RR 1.54, 95% CI 1.13 to 2.11), and have poor glycemic control (RR 1.77, 95% CI 1.31 to 2.39) versus those with 0 or 1 barrier. Each additional barrier worsened average adherence by 3.1% (95% CI -4.6%, -1.5%). In conclusion, >25% of nonadherent patients present with multiple barriers to optimal use, leading to meaningful differences in adherence. These findings should inform quality improvement interventions aimed at nonadherence.
| S-EPMC6957723 | biostudies-literature
Project description:BackgroundMedication nonadherence in patients with schizophrenia presents a serious clinical problem. Research on interventions incorporating motivational interviewing (MI) to improve adherence have shown mixed results.AimsPrimary aim is to determine the effectiveness of a MI intervention on adherence and hospitalization rates in patients, with multi-episode schizophrenia or schizoaffective disorder, who have experienced a psychotic relapse following medication nonadherence. Secondary aim is to evaluate whether MI is more effective in specific subgroups.MethodsWe performed a randomized controlled study including 114 patients who experienced a psychotic relapse due to medication nonadherence in the past year. Participants received an adapted form of MI or an active control intervention, health education (HE). Both interventions consisted of 5-8 sessions, which patients received in adjunction to the care as usual. Patients were assessed at baseline and at 6 and 12 months follow-up.ResultsOur results show that MI did not improve medication adherence in previously nonadherent patients who experienced a psychotic relapse. Neither were there significant differences in hospitalization rates at follow-up between MI and HE (27% vs 40%, P = .187). However, MI resulted in reduced hospitalization rates for female patients (9% vs 63%, P = .041), non-cannabis users (20% vs 53%, P = .041), younger patients (14% vs 50%, P = .012), and patients with shorter illness duration (14% vs 42%, P = .040).ConclusionsTargeted use of MI may be of benefit for improving medication adherence in certain groups of patients, although this needs further examination.
| S-EPMC3796095 | biostudies-literature
Project description:BACKGROUND:Individuals with co-existing serious mental illness and non-psychiatric medical illness are at high risk of acute care utilization. Mining of electronic health record data can help identify and categorize predictors of psychiatric hospital readmission in this population. OBJECTIVE:This study aimed to identify modifiable predictors of psychiatric readmission among individuals with comorbid bipolar disorder and medical illness. This goal was accomplished by applying objective variable selection via machine learning techniques. METHOD:This was a retrospective analysis of electronic health record data derived from 77,296 episodes of care from 2006 to 2016 within the University of California Health Care System. Data included 1,250 episodes of care involving patients with bipolar disorder and serious comorbid medical illnesses (defined by transfer between medicine and psychiatry services or concomitant primary medical and psychiatric admission diagnoses). Machine learning (classification trees) was used to identify potential predictors of 30-day psychiatric readmission across hospital encounters. Predictors included demographics, medical and psychiatric diagnoses, medication regimen, and disposition. The algorithm was internally validated using 10-fold cross-validation. RESULTS:The model predicted 30-day readmission with high accuracy (98% unbalanced model, 88% balanced model). Modifiable predictors of readmission were length of stay, transfers between medical and psychiatric services, discharge disposition to home, and all-cause acute health service utilization in the year before the index hospitalization. CONCLUSION:Among bipolar disorder patients with comorbid medical conditions, characteristics of the index hospitalization (e.g., duration, transfer, and disposition) emerged as more predictive than static properties of the patient (e.g., sociodemographic factors and psychiatric comorbidity burden). Findings identified phenotypes of patients at high risk for rehospitalization and suggest potential ways of modifying the risk of early readmission.
| S-EPMC7071814 | biostudies-literature
Project description:OBJECTIVE:To explore the effect of patient characteristics and health beliefs on their medication adherence. METHODS:Patients (n=167) with chronic conditions (mean age 58.9; SD=13.54, 53% males) were recruited from March 2009- to March 2010 using a cross sectional study design. Data collected included patients' demographics, medical conditions, medications therapeutic regimen, frequency of physician visits and health beliefs. Patient self-reported adherence to medications was assessed by the researcher using a validated and published scale. Treatment related problems (TRPs) were evaluated for each patient by competent clinical pharmacists. Associations between patient characteristics/health beliefs with adherence were explored. RESULTS:About half of the patients (46.1%) were non-adherent. A significant association was found between lower adherence and higher number of disease states (p<0.001), higher number of medications (p=0.001), and higher number of identified TRPs (p = 0.003). Patient adherence was positively affected by older age, higher educational level, and higher number of physician visits per month, while it was negatively affected by reporting difficulties with getting prescription refills on time. CONCLUSION:This study identified different factors that may negatively affect adherence, including higher number of medications and disease states, higher number of identified TRPs and inability to getting prescription refills on time. Hence, more care needs to be provided to patients with complex therapeutic regimens in order to enhance adherence.
| S-EPMC4800011 | biostudies-literature
Project description:BackgroundThis study assesses the feasibility of using machine learning methods such as Random Forests (RF), Artificial Neural Networks (ANN), Support Vector Regression (SVR) and Self-Organizing Feature Maps (SOM) to identify and determine factors associated with hypertensive patients' adherence levels. Hypertension is the medical term for systolic and diastolic blood pressure higher than 140/90 mmHg. A conventional medication adherence scale was used to identify patients' adherence to their prescribed medication. Using machine learning applications to predict precise numeric adherence scores in hypertensive patients has not yet been reported in the literature.MethodsData from 160 hypertensive patients from a tertiary hospital in Kuala Lumpur, Malaysia, were used in this study. Variables were ranked based on their significance to adherence levels using the RF variable importance method. The backward elimination method was then performed using RF to obtain the variables significantly associated with the patients' adherence levels. RF, SVR and ANN models were developed to predict adherence using the identified significant variables. Visualizations of the relationships between hypertensive patients' adherence levels and variables were generated using SOM.ResultMachine learning models constructed using the selected variables reported RMSE values of 1.42 for ANN, 1.53 for RF, and 1.55 for SVR. The accuracy of the dichotomised scores, calculated based on a percentage of correctly identified adherence values, was used as an additional model performance measure, resulting in accuracies of 65% (ANN), 78% (RF) and 79% (SVR), respectively. The Wilcoxon signed ranked test reported that there was no significant difference between the predictions of the machine learning models and the actual scores. The significant variables identified from the RF variable importance method were educational level, marital status, General Overuse, monthly income, and Specific Concern.ConclusionThis study suggests an effective alternative to conventional methods in identifying the key variables to understand hypertensive patients' adherence levels. This can be used as a tool to educate patients on the importance of medication in managing hypertension.
| S-EPMC7075362 | biostudies-literature
Project description:BackgroundPediatric patients with nephrotic syndrome take medications long-term with significant toxicity and complex regimens, yet data on medication adherence are limited.MethodsIn a multicenter observational study of patients with nephrotic syndrome, NEPTUNE (NCT01209000), we surveyed caregivers of patients <19 years old and adolescent patients on medication adherence during longitudinal follow-up beginning in June 2015. Data extraction was in October 2020. We described the proportion of nonadherent patients at first survey. Participant social and economic factors, condition-related factors, therapy-related factors, and patient-related factors were examined for relationships with nonadherence by generalized linear mixed models using the longitudinal data. In exploratory fashion, we assessed the relationship between adherence and subsequent steroid response classification by binary logistic regression and adherence with healthcare utilization by Poisson regression.ResultsA total of 225 participants completed a median of 3 surveys during follow-up (IQR, 2-5), with a total of 743 surveys. Overall, 80 (36%) reported nonadherence with medications. In adjusted analysis, older age (per 1 year; OR 1.08; 95% CI, 1.03 1.12), lower maternal educational level (≥ high school vs. < high school; OR 0.47; 95% CI 0.25 to 0.89), and increased parent and self-identification of medications barriers (per 1 point; OR 1.57; 95% CI, 1.15-2.15) were significantly associated with nonadherence. No relationship between nonadherence and subsequent frequency of healthcare utilization was observed. A trend toward increased subsequent steroid resistance classification was seen with nonadherence, though not statistically significant.ConclusionsMedication nonadherence is common in pediatric nephrotic syndrome. Investigations into the use of surveys in the clinic setting to identify at-risk patients and ways to support families over time are needed. A higher resolution version of the Graphical abstract is available as Supplementary information.
| S-EPMC10182827 | biostudies-literature
Project description:ObjectiveThe authors examined psychiatric comorbidities associated with alcohol use disorders and tobacco use disorders among heterosexual, bisexual, and gay and lesbian men and women in the United States and whether stress-related factors were predictive of comorbidities.MethodsThe authors used data from the National Epidemiologic Survey on Alcohol and Related Conditions-III (2012-2013, N=36,309) to examine the co-occurrence of past-year alcohol or tobacco use disorder with past-year anxiety disorders, mood disorders, and posttraumatic stress disorder by sexual identity (heterosexual, bisexual, gay or lesbian) and sex. The authors also examined the association of stress-related factors and social support with the presence of comorbidities.ResultsComorbidities were more prevalent among women and sexual minorities, particularly bisexual women. More than half of bisexual (55%) and gay or lesbian (51%) individuals who met criteria for a past-year alcohol use disorder had a psychiatric comorbidity, while only one-third of heterosexual individuals who met criteria for a past-year alcohol use disorder did. Similar differences were found among those who met criteria for a past-year tobacco use disorder. Among sexual minorities, the frequency of sexual orientation discrimination (adjusted odds ratio range=1.08-1.10), number of stressful life events (adjusted odds ratio range=1.25-1.43), and number of adverse childhood experiences (adjusted odds ratio range=1.04-1.18) were significantly associated with greater odds of comorbidities. Greater social support was significantly inversely associated with tobacco use disorder comorbidities (adjusted odds ratio range=0.96-0.97).ConclusionsThis research suggests that integrated substance use and mental health prevention and treatment programs are needed, particularly for individuals who identify as sexual minorities. The increased stressors experienced by sexual minority individuals may be important drivers of these high levels of comorbidities.
| S-EPMC7606786 | biostudies-literature
Project description:In low-income countries, clinicians must seek strategies to improve treatment adherence that are non-resource intensive and easily integrated into existing treatment structures. We conducted a prospective observational cohort study to investigate the relationship of family engagement in treatment during hospitalisation with post-discharge appointment and medication adherence in 81 patients from a Nigerian psychiatric hospital. After controlling for gender, diagnosis, mental state at discharge, and marital status, family involvement was significantly associated with appointment (P=0.047) but not medication adherence (P=0.590). Studies are needed to determine whether interventions based on engaging families in treatment can improve post-discharge adherence in this setting.
| S-EPMC5156562 | biostudies-literature