Dataset Information

Improving Dengue Diagnostics and Management Through Innovative Technology.

ABSTRACT:

Purpose of review

Dengue continues to be a major global public health threat. Symptomatic infections can cause a spectrum of disease ranging from a mild febrile illness to severe and potentially life-threatening manifestations. Management relies on supportive treatment with careful fluid replacement. The purpose of this review is to define the unmet needs and challenges in current dengue diagnostics and patient monitoring and outline potential novel technologies to address these needs.

Recent findings

There have been recent advances in molecular and point-of-care (POC) diagnostics as well as technologies including wireless communication, low-power microelectronics, and wearable sensors that have opened up new possibilities for management, clinical monitoring, and real-time surveillance of dengue. Novel platforms utilizing innovative technologies for POC dengue diagnostics and wearable patient monitors have the potential to revolutionize dengue surveillance, outbreak response, and management at population and individual levels. Validation studies of these technologies are urgently required in dengue-endemic areas.

SUBMITTER: Rodriguez-Manzano J

PROVIDER: S-EPMC5992235 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Publications

Improving Dengue Diagnostics and Management Through Innovative Technology.

Rodriguez-Manzano Jesus J Chia Po Ying PY Yeo Tsin Wen TW Holmes Alison A Georgiou Pantelis P Yacoub Sophie S

Current infectious disease reports 20180607 8

<h4>Purpose of review</h4>Dengue continues to be a major global public health threat. Symptomatic infections can cause a spectrum of disease ranging from a mild febrile illness to severe and potentially life-threatening manifestations. Management relies on supportive treatment with careful fluid replacement. The purpose of this review is to define the unmet needs and challenges in current dengue diagnostics and patient monitoring and outline potential novel technologies to address these needs.<h ...[more]

PMID: 29882167

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Project description:BackgroundAnxiety and mood disorders are the most common mental illnesses, peaking during adolescence and affecting approximately 25% of Canadians aged 14-17 years. If not successfully treated at this age, they often persist into adulthood, exerting a great social and economic toll. Given the long-term impact, finding ways to increase the success and cost-effectiveness of mental health care is a pressing need. Cognitive behavior therapy (CBT) is an evidence-based treatment for mood and anxiety disorders throughout the lifespan. Mental health technologies can be used to make such treatments more successful by delivering them in a format that increases utilization. Young people embrace technologies, and many want to actively manage their mental health. Mobile software apps have the potential to improve youth adherence to CBT and, in turn, improve outcomes of treatment.ObjectiveThe purpose of this project is to improve homework adherence in CBT for youth anxiety and/or depression. The objectives are to (1) design and optimize the usability of a mobile app for delivering the homework component of CBT for youth with anxiety and/or depression, (2) assess the app's impact on homework completion, and (3) implement the app in CBT programs. We hypothesize that homework adherence will be greater in the app group than in the no-app group.MethodsPhase 1: exploratory interviews will be conducted with adolescents and therapists familiar with CBT to obtain views and perspectives on the requirements and features of a usable app and the challenges involved in implementation. The information obtained will guide the design of a prototype. The prototype will be optimized via think-aloud procedures involving an iterative process of evaluation, modification, and re-evaluation, culminating in a fully functional version of the prototype that is ready for optimization in a clinical context. Phase 2: a usability study will be conducted to optimize the prototype in the context of treatment at clinics that provide CBT treatment for youth with anxiety and/or depression. This phase will result in a usable app that is ready to be tested for its effectiveness in increasing homework adherence. Phase 3: a pragmatic clinical trial will be conducted at several clinics to evaluate the impact of the app on homework adherence. Participants in the app group are expected to show greater homework completion than those in the no-app group.ResultsPhase 3 will be completed by September 2019.ConclusionsThe app will be a unique adjunct to treatment for adolescents in CBT, focusing on both anxiety and depression, developed in partnership with end users at every stage from design to implementation, customizable for different cognitive profiles, and designed with depression symptom tracking measures for youth made interoperable with electronic medical records.

Project description:BackgroundSkin cancer diagnostics is challenging, and mastery requires extended periods of dedicated practice.ObjectiveThe aim of the study was to determine if self-paced pattern recognition training in skin cancer diagnostics with clinical and dermoscopic images of skin lesions using a large-scale interactive image repository (LIIR) with patient cases improves primary care physicians' (PCPs') diagnostic skills and confidence.MethodsA total of 115 PCPs were randomized (allocation ratio 3:1) to receive or not receive self-paced pattern recognition training in skin cancer diagnostics using an LIIR with patient cases through a quiz-based smartphone app during an 8-day period. The participants' ability to diagnose skin cancer was evaluated using a 12-item multiple-choice questionnaire prior to and 8 days after the educational intervention period. Their thoughts on the use of dermoscopy were assessed using a study-specific questionnaire. A learning curve was calculated through the analysis of data from the mobile app.ResultsOn average, participants in the intervention group spent 2 hours 26 minutes quizzing digital patient cases and 41 minutes reading the educational material. They had an average preintervention multiple choice questionnaire score of 52.0% of correct answers, which increased to 66.4% on the postintervention test; a statistically significant improvement of 14.3 percentage points (P<.001; 95% CI 9.8-18.9) with intention-to-treat analysis. Analysis of participants who received the intervention as per protocol (500 patient cases in 8 days) showed an average increase of 16.7 percentage points (P<.001; 95% CI 11.3-22.0) from 53.9% to 70.5%. Their overall ability to correctly recognize malignant lesions in the LIIR patient cases improved over the intervention period by 6.6 percentage points from 67.1% (95% CI 65.2-69.3) to 73.7% (95% CI 72.5-75.0) and their ability to set the correct diagnosis improved by 10.5 percentage points from 42.5% (95% CI 40.2%-44.8%) to 53.0% (95% CI 51.3-54.9). The diagnostic confidence of participants in the intervention group increased on a scale from 1 to 4 by 32.9% from 1.6 to 2.1 (P<.001). Participants in the control group did not increase their postintervention score or their diagnostic confidence during the same period.ConclusionsSelf-paced pattern recognition training in skin cancer diagnostics through the use of a digital LIIR with patient cases delivered by a quiz-based mobile app improves the diagnostic accuracy of PCPs.Trial registrationClinicalTrials.gov NCT05661370; https://classic.clinicaltrials.gov/ct2/show/NCT05661370.

Dataset Information

Improving Dengue Diagnostics and Management Through Innovative Technology.

Purpose of review

Recent findings

Publications

Improving Dengue Diagnostics and Management Through Innovative Technology.

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