The Empowering Role of Mobile Apps in Behavior Change Interventions: The Gray Matters Randomized Controlled Trial

BACKGROUND: Health education and behavior change programs targeting specific risk factors have demonstrated their effectiveness in reducing the development of future diseases. Alzheimer disease (AD) shares many of the same risk factors, most of which can be addressed via behavior change. It is therefore theorized that a behavior change intervention targeting these risk factors would likely result in favorable rates of AD prevention. OBJECTIVE: The objective of this study was to reduce the future risk of developing AD, while in the short term promoting vascular health, through behavior change. METHODS: The study was an interventional randomized controlled trial consisting of subjects who were randomly assigned into either treatment (n=102) or control group (n=42). Outcome measures included various blood-based biomarkers, anthropometric measures, and behaviors related to AD risk. The treatment group was provided with a bespoke “Gray Matters” mobile phone app designed to encourage and facilitate behavior change. The app presented evidence-based educational material relating to AD risk and prevention strategies, facilitated self-reporting of behaviors across 6 behavioral domains, and presented feedback on the user’s performance, calculated from reported behaviors against recommended guidelines. RESULTS: This paper explores the rationale for a mobile phone–led intervention and details the app’s effect on behavior change and subsequent clinical outcomes. Via the app, the average participant submitted 7.3 (SD 3.2) behavioral logs/day (n=122,719). Analysis of these logs against primary outcome measures revealed that participants who improved their high-density lipoprotein cholesterol levels during the study duration answered a statistically significant higher number of questions per day (mean 8.30, SD 2.29) than those with no improvement (mean 6.52, SD 3.612), t(97.74)=−3.051, P=.003. Participants who decreased their body mass index (BMI) performed significantly better in attaining their recommended daily goals (mean 56.21 SD 30.4%) than those who increased their BMI (mean 40.12 SD 29.1%), t(80) = −2.449, P=.017. In total, 69.2% (n=18) of those who achieved a mean performance percentage of 60% or higher, across all domains, reduced their BMI during the study, whereas 60.7% (n=34) who did not, increased their BMI. One-way analysis of variance of systolic blood pressure category changes showed a significant correlation between reported efforts to reduce stress and category change as a whole, P=.035. An exit survey highlighted that respondents (n=83) reported that the app motivated them to perform physical activity (85.4%) and make healthier food choices (87.5%). CONCLUSIONS: In this study, the ubiquitous nature of the mobile phone excelled as a delivery platform for the intervention, enabling the dissemination of educational intervention material while simultaneously monitoring and encouraging positive behavior change, resulting in desirable clinical effects. Sustained effort to maintain the achieved behaviors is expected to mitigate future AD risk. TRIAL REGISTRATION: ClinicalTrails.gov NCT02290912; https://clinicaltrials.gov/ct2/show/NCT02290912 (Archived by WebCite at http://www.webcitation.org/6ictUEwnm

Automated identification of diagnostic labelling errors in medicine

Objectives: Identification of diagnostic error is complex and mostly relies on expert ratings, a severely limited procedure. We developed a system that allows to automatically identify diagnostic labelling error from diagnoses coded according to the international classification of diseases (ICD), often available as routine health care data. Methods: The system developed (index test) was validated against rater based classifications taken from three previous studies of diagnostic labeling error (reference standard). The system compares pairs of diagnoses through calculation of their distance within the ICD taxonomy. Calculation is based on four different algorithms. To assess the concordance between index test and reference standard, we calculated the area under the receiver operating characteristics curve (AUROC) and corresponding confidence intervals. Analysis were conducted overall and separately per algorithm and type of available dataset. Results: Diagnoses of 1,127 cases were analyzed. Raters previously classified 24.58% of cases as diagnostic labelling errors (ranging from 12.3 to 87.2% in the three datasets). AUROC ranged between 0.821 and 0.837 overall, depending on the algorithm used to calculate the index test (95% CIs ranging from 0.8 to 0.86). Analyzed per type of dataset separately, the highest AUROC was 0.924 (95% CI 0.887-0.962). Conclusions: The trigger system to automatically identify diagnostic labeling error from routine health care data performs excellent, and is unaffected by the reference standards' limitations. It is however only applicable to cases with pairs of diagnoses, of which one must be more accurate or otherwise superior than the other, reflecting a prevalent definition of a diagnostic labeling error

Radiation dose optimized lateral expansion of the field of view in synchrotron radiation X-ray tomographic microscopy

Increasing the lateral field of view of tomography-based imaging methods greatly increases the acquisition time. This article presents scanning protocols to obtain high-resolution tomographic scans with large lateral field of view at greatly decreased acquisition time and thus reduced radiation dose while resulting in high-quality three-dimensional tomographic datasets

The crossroads of tradition and modern technology: integrative approaches to studying carnivores in low density ecosystems

The study of large carnivores in semi-arid ecosystems presents inherent challenges due to their low densities, extensive home ranges, and elusive nature. We explore the potential for the synthesis of traditional knowledge (i.e. art of tracking) and modern technology to address challenges in conservation and wildlife research in these challenging environments. Our research focuses on the African lion (Panthera leo) in the Central Kalahari region of Botswana as a model system to demonstrate the potential of this integrative approach. Combining GPS tracking and traditional San trackers’ expertise, we present two case studies: (1) the individual identification of lions via a combination of tracking and footprint analysis and (2) the monitoring of territorial behavior through a combination of GPS technology (i.e. GPS collars and handheld GPS devices) and non-invasive tracking. These approaches enhance our understanding of carnivore ecology as well as support conservation efforts by offering a non-invasive, cost-effective, and highly accurate means of monitoring populations. Our findings underscore the value of merging traditional tracking skills with contemporary analytical and technological developments to offer new insights into the ecology of carnivores in challenging environments. This approach not only improves data collection accuracy and efficiency but also fosters a deeper understanding of wildlife, ensuring the conservation and sustainable management of these species. Our work advocates for the inclusion of indigenous knowledge in conservation science, highlighting its relevance and applicability across various disciplines, thereby broadening the methodologies used to study wildlife, monitor populations, and inform conservation strategies

Argonne National Laboratory Reports

This report is part of a series of studies designed to analyze the commercialization potential of various concepts of community-scale energy systems that have been termed Integrated Community Energy Systems (ICES). The study reported here concerns ways that affected individuals and organizations will respond to proposed ICES development projects. The intent is an initial examination of several institutional sectors that will: (1) anticipate responses that could impede ICES proposals and (2) provide an information base from which strategies to address adverse responses can be formulated

Motility-related protein-1 (MRP-1/CD9) expression can predict disease-free survival in patients with squamous cell carcinoma of the head and neck

CD9 is a transmembrane protein that has been implicated in cell adhesion, motility and proliferation, and numerous studies have demonstrated the prognostic value of its expression in different solid tumours. The purpose of this study is to determine the predictive value of CD9 in squamous cell carcinoma (SCC) of the head and neck. A total of 153 cases were examined for CD9 expression using immunohistochemistry applied on formalin-fixed, paraffin-embedded tissue. Cases were stratified in two categories depending on CD9 expression, as positive (>/=50% positive cells) or reduced (<50%). In all, 108 cases were positive for CD9 (85 cases with membranous, and 23 with both membranous and cytoplasmic staining) and 45 reduced expression. Reduced CD9 expression was significantly associated with high grade (P=0.0007) and lower disease-free survival (DFS) (P=0.017). The latter retained its significance in the multivariate analysis. When the 23 cases with both membranous and cytoplasmic patterns were studied as a separate subgroup, there were significant associations between CD9 expression and tumour grade (P=0.025) (95% CI 11-68), tumour stage (P=0.08) (95% CI 3.5-86) and the occurrence of any failure (P=0.083) (95% CI -1.7-57). Immunohistochemical CD9 expression proved to be an independent prognostic factor in SCC of the head and neck, and it may detect patients at a high risk of recurrence. In addition, the cytoplasmic pattern seems to have an even more significant value. However, this finding is limited to the small number of cases with this pattern