Brief interventions for improving adherence in schizophrenia: A pilot study using electronic medication event monitoring

Efficacy of a Smartphone App in Enhancing Medication Adherence and Accuracy in Individuals With Schizophrenia During the COVID-19 Pandemic: Randomized Controlled Trial

BACKGROUND

Poor medication adherence or inaccuracy in taking prescribed medications plays an important role in the recurrence or worsening of psychiatric symptoms in patients with schizophrenia, and the COVID-19 pandemic impacted their medication adherence with exacerbated symptoms or relapse. The use of mobile health services increased during the COVID-19 pandemic, and their role in improving mental health is becoming clearer.

OBJECTIVE

This study aimed to explore the effectiveness of a smartphone app (MedAdhere) on medication adherence and accuracy among patients with schizophrenia and to measure their psychiatric symptoms and cognitive functions.

METHODS

In this 12-week experimental study, participants were provided interventions with the MedAdhere app, and data were collected between June 2021 and September 2022. A total of 105 participants were randomly assigned to either the experimental or control groups. We used the Positive and Negative Syndrome Scale and Mini-Mental State Examination to measure the participants' psychiatric symptoms and cognitive functions. Generalized estimating equations were used for data analysis.

RESULTS

A total of 94 participants met the inclusion criteria and completed the protocol, and the medication adherence rate of the experimental group was 94.72% (2785/2940) during the intervention. Psychotic symptoms (positive, negative, and general psychopathology symptoms) and cognitive functions (memory, language, and executive function) were significantly improved in the experimental group compared to the control group after the intervention.

CONCLUSIONS

The MedAdhere app effectively and significantly improved medication adherence and, thereby, the psychiatric symptoms of patients with schizophrenia. This artificial intelligence assisted app could be extended to all patients who need to be reminded to take medication on schedule.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05892120; https://clinicaltrials.gov/study/NCT05892120.

Digital health interventions to improve adherence to oral antipsychotics among patients with schizophrenia: a scoping review

OBJECTIVES

To assess the current evidence on the potential of digital health interventions (DHIs) to improve adherence to oral antipsychotics among patients with schizophrenia by assessing the methodologies, feasibility and effectiveness of DHIs as well as the perceptions of relevant stakeholders.

DESIGN

The scoping review was conducted based on the methodologies outlined by Levac et al and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines.

DATA SOURCES

PubMed, Embase, Web of Science, Scopus, CINAHL, PsycINFO and the Cochrane Library were searched in August 2023 to identify relevant publications from the previous decade.

ELIGIBILITY CRITERIA

Studies published in English focused on improving medication adherence among adult patients with schizophrenia or schizoaffective disorder via DHIs were selected. Protocols, editorials, comments, perspectives, reviews, correspondence and conference abstracts were excluded.

DATA EXTRACTION AND SYNTHESIS

The extracted data included general information about the study, framework, participants, features and strategies of DHIs, measurement tools for adherence used, and main findings.

RESULTS

In total, 64 studies were included in the qualitative synthesis. Features used in DHIs to improve medication adherence included phone calls, text messages, mobile apps, sensors, web-based platforms and electronic devices. Strategies included medication reminders and monitoring, providing medication-related information and suggestions, other illness management suggestions and individual support. Texting and mobile apps were commonly used as medication reminders and monitoring methods. Additionally, the use of sensors combined with other digital technologies has garnered significant attention. All the interventions were considered acceptable and feasible, and several were assessed in pilot trials. Preliminary findings suggest that DHIs could enhance medication adherence in patients with schizophrenia. However, further validation of their effectiveness is required.

CONCLUSION

DHIs are a promising approach to enhancing medication adherence among patients with schizophrenia. Future interventions should be interactive, focusing on user preference, experience and privacy.

Efficacy of technology-based interventions in psychosis: a systematic review and network meta-analysis

BACKGROUND

Technology-based interventions (TBIs) are a useful approach when attempting to provide therapy to more patients with psychosis.

METHODS

Randomized controlled trials of outcomes of TBIs v. face-to-face interventions in psychosis were identified in a systematic search conducted in PubMed/Ovid MEDLINE. Data were extracted independently by two researchers, and standardized mean changes were pooled using a three-level model and network meta-analysis.

RESULTS

Fifty-eight studies were included. TBIs complementing treatment as usual (TAU) were generally superior to face-to-face interventions (g = 0.16, p ≤ 0.0001) and to specific outcomes, namely, neurocognition (g = 0.13, p ≤ 0.0001), functioning (g = 0.25, p = 0.006), and social cognition (g = 0.32, p ≤ 0.05). Based on the network meta-analysis, the effect of two TBIs differed significantly from zero; these were the TBIs cognitive training for the neurocognitive outcome [g = 0.16; 95% confidence interval (CI) 0.09-0.23] and cognitive behavioral therapy for quality of life (g = 1.27; 95% CI 0.46-2.08). The variables educational level, type of medication, frequency of the intervention, and contact during the intervention moderated the effectiveness of TBIs over face-to-face interventions in neurocognition and symptomatology.

CONCLUSIONS

TBIs are effective for the management of neurocognition, symptomatology, functioning, social cognition, and quality of life outcomes in patients with psychosis. The results of the network meta-analysis showed the efficacy of some TBIs for neurocognition, symptomatology, and quality of life. Therefore, TBIs should be considered a complement to TAU in patients with psychosis.

Pipamperone Population Pharmacokinetics Related to Effectiveness and Side Effects in Children and Adolescents

Background

Pipamperone is a frequently prescribed antipsychotic in children and adolescents in the Netherlands, Belgium, and Germany. However, pediatric pharmacokinetics and the relationship with side effects and efficacy are unknown. Currently, divergent pediatric dosing recommendations exist.

Objectives

The objective of this study was to describe the population pharmacokinetics of pipamperone in children and adolescents; to correlate measured and predicted pipamperone trough concentrations and predicted 24-h area under the curves with effectiveness, extrapyramidal symptoms, and sedation; and to propose dose recommendations based on simulations.

Methods

Pipamperone concentrations were collected from Dutch pediatric patients in a prospective naturalistic trial (n = 8), and German pediatric patients in a therapeutic drug monitoring service (n = 22). A total of 70 pipamperone concentrations were used to develop a population pharmacokinetic model with non-linear mixed-effects modeling (NONMEM^®). Additionally, an additional random sample of 21 German patients with 33 pipamperone concentrations from the same therapeutic drug monitoring service was used for external validation. Pharmacokinetic parameters were related to clinical improvement, sedation, and extrapyramidal symptoms. Simulations were performed to determine optimal dosages.

Results

In a one-compartment model, the apparent volume of distribution was 416 L/70 kg and the apparent clearance was 22.1 L/h/70 kg. Allometric scaling was used to correct for differences in bodyweight. The model was successfully externally validated. The median [25th–75th percentile] measured pipamperone trough concentrations were numerically higher in responders (98.0 µg/L [56.0–180.5 µg/L]) than in non-responders (58.0 µg/L [14.9–105.5 µg/L]), although non-significant (p = 0.14). A twice-daily 0.6-mg/kg dosage was better than a fixed dosage to attain the concentration range observed in responders.

Conclusions

Our findings suggest that pipamperone therapeutic reference ranges may be lower for children with behavioral problems than recommended for adults with psychotic symptoms (100–400 µg/L). When dosing pipamperone in children and adolescents, bodyweight should be taken into account.

Electronic supplementary material

The online version of this article (10.1007/s40262-020-00894-y) contains supplementary material, which is available to authorized users.

Persistence as a Robust Indicator of Medication Adherence-Related Quality and Performance

Medication adherence is a priority for health systems worldwide and is widely recognised as a key component of quality of care for disease management. Adherence-related indicators were rarely explicitly included in national health policy agendas. One barrier is the lack of standardised adherence terminology and of routine measures of adherence in clinical practice. This paper discusses the possibility of developing adherence-related performance indicators highlighting the value of measuring persistence as a robust indicator of quality of care. To standardise adherence and persistence-related terminology allowing for benchmarking of adherence strategies, the European Ascertaining Barriers for Compliance (ABC) project proposed a Taxonomy of Adherence in 2012 consisting of three components: initiation, implementation, discontinuation. Persistence, which immediately precedes discontinuation, is a key element of taxonomy, which could capture adherence chronology allowing the examination of patterns of medication-taking behaviour. Advances in eHealth and Information Communication Technology (ICT) could play a major role in providing necessary structures to develop persistence indicators. We propose measuring persistence as an informative and pragmatic measure of medication-taking behaviour. Our view is to develop quality and performance indicators of persistence, which requires investing in ICT solutions enabling healthcare providers to review complete information on patients’ medication-taking patterns, as well as clinical and health outcomes.

Digital Health Around Clinical High Risk and First-Episode Psychosis

PURPOSE OF REVIEW

This review aims to examine relapse definitions and risk factors in psychosis as well as the role of technology in relapse predictions and risk modeling.

RECENT FINDINGS

There is currently no standard definition for relapse. Therefore, there is a need for data models that can account for the variety of factors involved in defining relapse. Smartphones have the ability to capture real-time, moment-to-moment assessment symptomology and behaviors via their variety of sensors and have high potential to be used to create prediction and risk modeling. While there is still a need for further research on how technology can predict and model relapse, there are simple ways to begin incorporating technology for relapse prediction in clinical care.