Mean age was 52.1 (standard deviation [SD] = 7.4) and mean body mass index was 31.4 (SD = 7.4). Compared to TAU, TEAM participants had significantly lower mean systolic blood pressure by 24 weeks, and there was also improvement in HbA and high-density lipoprotein cholesterol ( P = .03). Other biomarker and health behaviors were similar between groups. Qualitative results suggested improved awareness of risk factors as well as positive effects of group support.

ObjectiveAs poor medication adherence is common in bipolar disorder (BD), technology-assisted approaches may help to monitor and enhance adherence. This study evaluated preliminary feasibility, patient satisfaction and effects on adherence, BD knowledge, and BD symptoms associated with the use of a multicomponent technology-assisted adherence enhancement system.MethodsThis prospective study tested the system in five BD patients over a 15-day period. System components included: 1) an automated pill cap with remote monitoring sensor; 2) a multimedia adherence enhancement program; and 3) a treatment incentive program. This study evaluated system usability, patient satisfaction and effects on adherence (Morisky scale), knowledge (treatment knowledge test [TKT]), and symptoms (internal state scale [ISS]).ResultsMean age of the sample was 62 years, 4/5 (80%) Caucasian, and 4/5 (80%) single/divorced or widowed. Most participants (4/5, 80%) were on a single BD medication. Participants had BD for an average of 21 years. Challenges included attaching the pill sensor to standard pharmacy bottles for individuals using very large pill containers or those with multiday pill boxes. Three of five (60%) individuals completed the full 15-day period. Usability scores were high overall. Mean Morisky scores improved. Means on all four subscales of the ISS were all in the direction of improvement. On the TKT, there was a 40% increase in mean scores.ConclusionA multicomponent technology-assisted BD adherence enhancement system is feasible. Challenges include accommodating multiple types of pill containers and monitoring multiple drugs simultaneously. The system can also generate adherence information that is potentially useful for treatment planning.

Automated devices such as MEMS can assist investigators in evaluating adherence in patients with BD. Knowing the anticipated pitfalls allows study teams to implement preemptive procedures for successful implementation in BD adherence studies and can help pave the way for future refinements as automated adherence assessment technologies become more sophisticated and readily available.

Epilepsy is a chronic neurological condition that requires active self-management to reduce personal and population burden. The Managing Epilepsy Well Network, funded by the US Centers for Disease Control and Prevention, conducts research on epilepsy self-management. There is an urgent need to develop an integrated informatics platform to maximize the secondary use of existing Managing Epilepsy Well Network data. We have implemented multiple steps to develop an informatics platform, including: (a) a survey of existing outcome data, (b) identification of common data elements, and (c) an integrated database using an epilepsy domain ontology to reconcile data heterogeneity. The informatics platform enables assessment of epilepsy self-management samples by site and in aggregate to support data interpretations for clinical care and ongoing epilepsy self-management research. The Managing Epilepsy Well informatics platform is expected to help advance epilepsy self-management, improve health outcomes, and has potential application in other thematic research networks.