A case study in science-to-service application of epilepsy self-management.

AIMS: Epilepsy self-management (ESM), the overall approach of reducing seizures and optimizing whole-health, is a targeted approach to improve population health for people with epilepsy (PWE). "Self-management for people with epilepsy and a history of negative health events" (SMART) is an 8-session group-format, remotely delivered ESM. This report describes the evolution of SMART development, testing and scale-up, taking advantage of ESM team expertise, community relationships and infrastructure established by social service agencies that deliver support to PWE. METHODS: This is a case-study dissemination and implementation (D&I) science-to-service model using the RE-AIM framework approach (Reach, Effectiveness, Adoption, Implementation, and Maintenance) focused on 5 dimensions of individual- and setting-level outcomes important to program adoption, impact and sustainability. Performance evaluations include participation representativeness, ESM attendance and acceptability as well as change in relevant health outcomes. RESULTS: SMART D & I is implemented via a collaboration of 3 unique regional, epilepsy-focused nonprofit social service organizations and a university team that developed SMART. The ongoing collaboration is expanding SMART delivery to PWE across 13 U.S. states. Thus far, we have trained 17 Nurse and Peer Educators (NEs and PEs). PEs (N = 10) have a mean age 51.1 (SD 10.4) years and a mean age of epilepsy diagnosis of 29.4 (SD 19.3). Of 128 participants offered SMART, and who provided age data (N = 86) mean age was 37.7 years (SD 14.4). Of participants who provided data on gender and race (N = 89), 65 were women (73.9 %), 18 African-American (20.2 %). Mean age of epilepsy diagnosis was 19.4 years (SD 16.6) and 59 (52.2 %) of PWE reported having seizures in the last 30 days pre-SMART sessions. Among those with attendance data (N = 103), mean number of SMART groups attended was 5.7 (SD 2.3). Mean values for past 30-day seizure frequency, 9-item Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder Inventory (GAD-7) and 10-item Quality of Life in Epilepsy Scale (QOLIE-10) for PWE that provided both pre and post SMART data were 7.6 (SD 15.8) vs 2.8 (SD 3.4) p = 0.3, 7.63 (SD 6.6) vs 6.3 (SD 5.7) p = 0.95, 6.6 (SD 5.7) vs 6.67(SD 5.3) p = 0.47 and 2.8 (SD 0.8) vs 2.7 (SD 1.0) p = 0.07 respectively. CONCLUSIONS: Implementing ESM using a RE-AIM/Iterative RE-AIM framework links intervention developers and community partners. While PWE have substantial barriers to health, including frequent seizures, they are able engage in the SMART program. Although a major limitation to patient-level evaluation is challenges in collecting post-SMART follow-up data, preliminary findings suggest a trend for improved quality of life.

Association Between Symptom Severity and Medication Adherence in Adults with Bipolar Disorder Reporting Adherence Challenges.

Background: Given the importance of medication adherence among individuals with bipolar disorder (BD), this analysis from an ongoing randomized controlled trial (RCT) examined the relationship between BD symptoms, functioning and adherence in 69 poorly adherent adults with BD. Method: Study inclusion criteria included being ≥ 18 years old with BD Type 1 or 2, difficulties with medication adherence and actively symptomatic as measured by Brief Psychiatric Rating Scale (BPRS) score ≥ 36, Young Mania Rating Scale (YMRS) > 8 or Montgomery Asberg Depression Rating Scale (MADRS) > 8. Adherence was measured in 2 ways: 1) the self-reported Tablets Routine Questionnaire (TRQ) and 2) electronic pill container monitoring (eCap pillbox). BD symptoms and functioning were measured with the MADRS, YMRS, Clinical Global Impressions Scale (CGI), and Global Assessment of Functioning (GAF). Only screening and baseline data were examined. Results: Mean age was 42.32 (SD = 12.99) years, with 72.46% (n = 50) female and 43.48% (n = 30) non-white. Mean past 7-day percentage of days with missed BD medications using TRQ was 40.63% (SD = 32.61) and 30.30% (SD = 30.41) at screening and baseline, respectively. Baseline adherence using eCap was 42.16% (SD = 35.85) in those with available eCap data (n = 41). Worse adherence based on TRQ was significantly associated with higher MADRS (p = 0.04) and CGI (p = .03) but lower GAF (p = 0.02). eCAP measured adherence was not significantly associated with clinical variables. Conclusion: While depression and functioning were approximate markers of adherence, reliance on patient self-report or BD symptom presentation may give an incomplete picture of medication-taking behaviors.

Clinical correlates of negative health events and disparities among adults with epilepsy enrolled in a self-management clinical trial.

AIMS: Despite advances in care, people with epilepsy experience negative health events (NHEs), such as seizures, emergency department (ED) visits and hospitalizations. This analysis using baseline data from an epilepsy self-management clinical trial targeting people from rural regions and other underserved populations assessed the relationship between demographic and clinical variables vs. NHEs. METHODS: Data to evaluate disparities and clinical correlates was collected using patient surveys from a baseline sample of 94 participants in a larger prospective study of 160 individuals with epilepsy who experienced an NHE within the last six months. Demographic characteristics, mental and physical functional status assessed using 36-Item Short Form Health Survey questionnaire version 2 (SF-36v2), depression assessed with the 9-item Patient Health Questionnaire (PHQ-9), quality of life assessed with the 10-item Quality of Life in Epilepsy Inventory (QOLIE-10), self-efficacy assessed the Epilepsy Self-Efficacy Scale (ESES), social support assessed with the Multidimensional Scale of Perceived Social Support (MSPSS), self-management assessed with the Epilepsy Self-Management Scale (ESMS), and stigma assessed with the Epilepsy Stigma Scale (ESS) were all examined in association with past 6-month total NHE frequency as well as NHE sub-categories of past 30-day and 6-month seizure counts, self-harm attempts, ED visits and hospitalizations. An exploratory evaluation of NHE correlates in relation to the Rural Urban Continuum Code (RUCC) residence classification compared 3 subgroups of increasing rurality. Descriptive statistics were generated for demographic and clinical variables and NHEs, and exploratory analyses compared the distribution of demographic, clinical, and NHE variables by RUCC categorization. RESULTS: The mean age was 38.5 years (SD 11.9), predominantly female (N= 62, 66.0%) and white (N=81, 86.2%). Just a little under half (N=43, 45.7%) of participants had annual incomes of less than $25,000, and 40% (N=38) were rural residents (RUCC >3). The past 6-month NHEs count was 20.4 (SD 32.0). Seizures were the most common NHE with a mean 30-day seizure frequency = 5.4 (SD 11.8) and 6-month seizure frequency of 18.7 (SD 31.6). Other NHE types were less common with a past 6-month self-harm frequency of 0.16 (SD 1.55), ED visit frequency of 0.72 (SD 1.10), and hospitalization frequency of 0.28 (SD 1.02). There were few significant demographic and clinical correlates for total and sub-categories of NHEs. Worse physical health status, as measured by the physical component summary (PCS) of the SF-36v2, was significantly associated with 6-month seizure counts (p=.04). There were no significant differences between the 3 RUCC subgroups on demographic variables. However, past 30-day seizure count, past 6-month seizure count and total past 6-month NHE counts were all higher among individuals from more rural settings (p-values <.01 for each). CONCLUSIONS: Rural adults with epilepsy were more likely to have a greater number of seizures and more epilepsy complications in general. Worse physical health function was also associated with more epilepsy complications. However, this analysis found few other demographic and clinical correlates of cumulative NHEs among adults with epilepsy. Additional efforts are needed to investigate health disparities among people with epilepsy who live in rural regions or who have poor physical health function.

Applying the Behavior Change Technique Taxonomy to Four Multicomponent Childhood Obesity Interventions.

Applying the Behavior Change Technique Taxonomy has the potential to facilitate identification of effective childhood obesity intervention components. This article evaluates the feasibility of coding Childhood Obesity Prevention and Treatment Consortium interventions and compares reliability between external taxonomy-familiar coders and internal intervention-familiar coders. After training, coder pairs independently coded prespecified portions of intervention materials. An adjudication process was used to explore coding discrepancies. Reliability between internal and external coders was moderate (prevalence and bias-adjusted kappa .38 to .55). Reliability for specific target behaviors varied with substantial agreement for physical activity (.63 to .76) and moderate for dietary intake (.44 to .63). Applying the taxonomy to these interventions was feasible, but agreement was modest. Coding discrepancies highlight the importance of refining coding to capture the complexities of childhood obesity interventions, which often engage multiple recipients (e.g., parents and/or children) and address multiple behaviors (e.g., diet, physical activity, screen time).

Two Family Interventions to Reduce BMI in Low-Income Urban Youth: A Randomized Trial.

BACKGROUND: Our primary aim was to evaluate the effects of 2 family-based obesity management interventions compared with a control group on BMI in low-income adolescents with overweight or obesity. METHODS: In this randomized clinical trial, 360 urban-residing youth and a parent were randomly assigned to 1 of 2 behaviorally distinct family interventions or an education-only control group. Eligible children were entering the sixth grade with a BMI ≥85th percentile. Interventions were 3 years in length; data were collected annually for 3 years. Effects of the interventions on BMI slope (primary outcome) over 3 years and a set of secondary outcomes were assessed. RESULTS: Participants were primarily African American (77%), had a family income of <25 000 per year, and obese at enrollment (68%). BMI increased over time in all study groups, with group increases ranging from 0.95 to 1.08. In an intent-to-treat analysis, no significant differences were found in adjusted BMI slopes between either of the family-based interventions and the control group (P = .35). No differences were found between the experimental and control groups on secondary outcomes of diet, physical activity, sleep, perceived stress, or cardiometabolic factors. No evidence of effect modification of the study arms by sex, race and/or ethnicity, household income, baseline levels of child and parent obesity, or exposure to a school fitness program were found. CONCLUSIONS: In this low-income, adolescent population, neither of the family-based interventions improved BMI or health-related secondary outcomes. Future interventions should more fully address poverty and other social issues contributing to childhood obesity.

Development of the Systems Thinking Scale for Adolescent Behavior Change.

This report describes the development and psychometric testing of the Systems Thinking Scale for Adolescent Behavior Change (STS-AB). Following item development, initial assessments of understandability and stability of the STS-AB were conducted in a sample of nine adolescents enrolled in a weight management program. Exploratory factor analysis of the 16-item STS-AB and internal consistency assessments were then done with 359 adolescents enrolled in a weight management program. Test-retest reliability of the STS-AB was .71, p = .03; internal consistency reliability was .87. Factor analysis of the 16-item STS-AB indicated a one-factor solution with good factor loadings, ranging from .40 to .67. Evidence of construct validity was supported by significant correlations with established measures of variables associated with health behavior change. We provide beginning evidence of the reliability and validity of the STS-AB to measure systems thinking for health behavior change in young adolescents.

An update on antidepressant use and suicidality in pediatric depression.

INTRODUCTION: In 2003, public health advisories in North America and Europe regarding suicidality associated with selective serotonin reuptake inhibitors (SSRIs) led to the addition of black box warnings to antidepressant package inserts in 2004. Subsequently, a series of events appeared to result from these regulatory actions. AREAS COVERED: This review provides an overview of the temporal associations of regulatory agencies' actions in North America and Europe with rates of depression diagnoses, pediatric antidepressant prescription rates, follow-up visits to physicians prescribing antidepressants, and rates of completed suicide and suicidal ideation in children and adolescents. In addition, evidence-based predictors of suicidal behavior and suicide risk, as provided by large, multisite studies of depressed children and adolescents, are outlined. Finally, this review considers key advancements in the study of young patients at risk for suicide and describes innovations in current research methodology, to more accurately identify suicidality and the relationship to antidepressant use within this vulnerable patient population. EXPERT OPINION: Evaluating the role of antidepressants in those youths who do not respond to evidence-based psychotherapeutic interventions may be a useful future research direction. Until more data are available, however, closely monitored antidepressant treatment in combination with CBT may provide the most benefit.