Using codesign to develop a culturally tailored, behavior change mHealth intervention for indigenous and other priority communities: A case study in New Zealand.

The obesity rate in New Zealand is one of the highest worldwide (31%), with highest rates among Maori (47%) and Pasifika (67%). Codesign was used to develop a culturally tailored, behavior change mHealth intervention for Maori and Pasifika in New Zealand. The purpose of this article is to provide an overview of the codesign methods and processes and describe how these were used to inform and build a theory-driven approach to the selection of behavioral determinants and change techniques. The codesign approach in this study was based on a partnership between Maori and Pasifika partners and an academic research team. This involved working with communities on opportunity identification, elucidation of needs and desires, knowledge generation, envisaging the mHealth tool, and prototype testing. Models of Maori and Pasifika holistic well-being and health promotion were the basis for identifying key content modules and were applied to relevant determinants of behavior change and theoretically based behavior change techniques from the Theoretical Domains Framework and Behavior Change Taxonomy, respectively. Three key content modules were identified: physical activity, family/whanau [extended family], and healthy eating. Other important themes included mental well-being/stress, connecting, motivation/support, and health literacy. Relevant behavioral determinants were selected, and 17 change techniques were mapped to these determinants. Community partners established that a smartphone app was the optimal vehicle for the intervention. Both Maori and Pasifika versions of the app were developed to ensure features and functionalities were culturally tailored and appealing to users. Codesign enabled and empowered users to tailor the intervention to their cultural needs. By using codesign and applying both ethnic-specific and Western theoretical frameworks of health and behavior change, the mHealth intervention is both evidence based and culturally tailored.

Morphological control of nanoprobe for colorimetric antioxidant detection.

Colloidal metal nanoparticles (NPs) with remarkable localized surface plasmon resonance (LSPR) have found wide use as probes in sensing. The LSPR that employed as the sensing signal is strongly associated with the morphology of nanoprobes. In this work, morphological change of Au nanocage to Au@Ag nanobox and thus the LSPR evolution are well regulated by trace amount of antioxidant, where the mechanism of seed-mediated growth is used as a powerful means in this process. Based on the linear relationship between morphology-induced LSPR evolution and the concentration of antioxidant, a simple, reliable and highly sensitive colorimetric method is developed for antioxidant detection. The detectable range of this method is 0.01-5 µM and 2-20 µM when a UV-vis spectrophotometer and a smartphone are employed as an analyzer, respectively. It has also been successfully applied in the detection of total antioxidants in green tea. This work provides new insights into developing sensitive LSPR-based sensors through precisely manipulating the morphology of nanoprobes.

A smartphone application for treating depressive symptoms: study protocol for a randomised controlled trial.

BACKGROUND: Depression is a commonly occurring disorder linked to diminished role functioning and quality of life. The development of treatments that overcome barriers to accessing treatment remains an important area of clinical research as most people delay or do not receive treatment at an appropriate time. The workplace is an ideal setting to roll-out an intervention, particularly given the substantial psychological benefits associated with remaining in the workforce. Mobile health (mhealth) interventions utilising smartphone applications (apps) offer novel solutions to disseminating evidence based programs, however few apps have undergone rigorous testing. The present study aims to evaluate the effectiveness of a smartphone app designed to treat depressive symptoms in workers. METHODS: The present study is a multicentre randomised controlled trial (RCT), comparing the effectiveness of the intervention to that of an attention control. The primary outcome measured will be reduced depressive symptoms at 3 months. Secondary outcomes such as wellbeing and work performance will also be measured. Employees from a range of industries will be recruited via a mixture of targeted social media advertising and Industry partners. Participants will be included if they present with likely current depression at baseline. Following baseline assessment (administered within the app), participants will be randomised to receive one of two versions of the Headgear application: 1) Intervention (a 30-day mental health intervention focusing on behavioural activation and mindfulness), or 2) attention control app (mood monitoring for 30 days). Participants will be blinded to their allocation. Analyses will be conducted within an intention to treat framework using mixed modelling. DISCUSSION: The results of this trial will provide valuable information about the effectiveness of mhealth interventions in the treatment of depressive symptoms in a workplace context. TRIAL REGISTRATION: The current trial is registered with the Australian and New Zealand Clinical Trials Registry ( ACTRN12617000547347 , Registration date: 19/04/2017).

Smartphone-Driven Low-Power Light-Emitting Device.

Low-level light (laser) therapy (LLLT) has been widely researched in the recent past. Existing LLLT studies were performed based on laser. Recently, studies using LED have increased. This study presents a smartphone-driven low-power light-emitting device for use in colour therapy as an alternative medicine. The device consists of a control unit and a colour probe. The device is powered by and communicates with a smartphone using USB On-The-Go (OTG) technology. The control unit controls emitting time and intensity of illumination with the configuration value of a smartphone application. Intensity is controlled by pulse width modulation (PWM) without feedback. A calibration is performed to resolve a drawback of no feedback. To calibrate, intensity is measured in every 10 percent PWM output. PWM value is linearly calibrated to obtain accurate intensity. The device can control the intensity of illumination, and so, it can find application in varied scenarios.

A smartphone imaging-based label-free and dual-wavelength fluorescent biosensor with high sensitivity and accuracy.

The accuracy of a bioassay based on smartphone-integrated fluorescent biosensors has been limited due to the occurrence of false signals from non-specific reactions as well as a high background and low signal-to-noise ratios for complementary metal oxide semiconductor image sensors. To overcome this problem, we demonstrate dual-wavelength fluorescent detection of biomolecules with high accuracy. Fluorescent intensity can be quantified using dual wavelengths simultaneously, where one decreases and the other increases, as the target analytes bind to the split capture and detection aptamer probes. To do this, we performed smartphone imaging-based fluorescence microscopy using a microarray platform on a substrate with metal-enhanced fluorescence (MEF) using Ag film and Al2O3 nano-spacer. The results showed that the sensitivity and specificity of the dual-wavelength fluorescent quantitative assay for the target biomolecule 17-ß-estradiol in water were significantly increased through the elimination of false signals. The detection limit was 1pg/mL and the area under the receiver operating characteristic curve of the proposed assay (0.922) was comparable to that of an enzyme-linked immunosorbent assay (0.956) from statistical accuracy tests using spiked wastewater samples. This novel method has great potential as an accurate point-of-care testing technology based on mobile platforms for clinical diagnostics and environmental monitoring.

Exploiting NanoLuc luciferase for smartphone-based bioluminescence cell biosensor for (anti)-inflammatory activity and toxicity.

The availability of smartphones with high-performance digital image sensors and processing power has completely reshaped the landscape of point-of-need analysis. Thanks to the high maturity level of reporter gene technology and the availability of several bioluminescent proteins with improved features, we were able to develop a bioluminescence smartphone-based biosensing platform exploiting the highly sensitive NanoLuc luciferase as reporter. A 3D-printed smartphone-integrated cell biosensor based on genetically engineered Hek293T cells was developed. Quantitative assessment of (anti)-inflammatory activity and toxicity of liquid samples was performed with a simple and rapid add-and-measure procedure. White grape pomace extracts, known to contain several bioactive compounds, were analyzed, confirming the suitability of the smartphone biosensing platform for analysis of untreated complex biological matrices. Such approach could meet the needs of small medium enterprises lacking fully equipped laboratories for first-level safety tests and rapid screening of new bioactive products. Graphical abstract Smartphone-based bioluminescence cell biosensor.

Personalized nutrition diagnostics at the point-of-need.

Micronutrient deficiency is widespread and negatively impacts morbidity, mortality, and quality of life globally. On-going advancements in nutritional biomarker discovery are enabling objective and accurate assessment of an individual's micronutrient and broader nutritional status. The vast majority of such assessment however still needs to be conducted in traditional centralized laboratory facilities which are not readily accessible in terms of cost and time in both the developed and developing countries. Lab-on-a-chip (LOC) technologies are enabling an increasing number of biochemical reactions at the point-of-need (PON) settings, and can significantly improve the current predicament in nutrition diagnostics by allowing rapid evaluation of one's nutritional status and providing an easy feedback mechanism for tracking changes in diet or supplementation. We believe that nutrition diagnostics represents a particularly appealing opportunity over other PON applications for two reasons: (1) healthy ranges for many micronutrients are well defined which allows for an unbiased diagnosis, and (2) many deficiencies can be reversed through changes in diet or supplementation before they become severe. In this paper, we provide background on nutritional biomarkers used in nutrition diagnostics and review the emerging technologies that exploit them at the point-of-need.

A Validated Smartphone-Based Assessment of Gait and Gait Variability in Parkinson's Disease.

BACKGROUND: A well-established connection exists between increased gait variability and greater fall likelihood in Parkinson's disease (PD); however, a portable, validated means of quantifying gait variability (and testing the efficacy of any intervention) remains lacking. Furthermore, although rhythmic auditory cueing continues to receive attention as a promising gait therapy for PD, its widespread delivery remains bottlenecked. The present paper describes a smartphone-based mobile application ("SmartMOVE") to address both needs. METHODS: The accuracy of smartphone-based gait analysis (utilizing the smartphone's built-in tri-axial accelerometer and gyroscope to calculate successive step times and step lengths) was validated against two heel contact-based measurement devices: heel-mounted footswitch sensors (to capture step times) and an instrumented pressure sensor mat (to capture step lengths). 12 PD patients and 12 age-matched healthy controls walked along a 26-m path during self-paced and metronome-cued conditions, with all three devices recording simultaneously. RESULTS: Four outcome measures of gait and gait variability were calculated. Mixed-factorial analysis of variance revealed several instances in which between-group differences (e.g., increased gait variability in PD patients relative to healthy controls) yielded medium-to-large effect sizes (eta-squared values), and cueing-mediated changes (e.g., decreased gait variability when PD patients walked with auditory cues) yielded small-to-medium effect sizes-while at the same time, device-related measurement error yielded small-to-negligible effect sizes. CONCLUSION: These findings highlight specific opportunities for smartphone-based gait analysis to serve as an alternative to conventional gait analysis methods (e.g., footswitch systems or sensor-embedded walkways), particularly when those methods are cost-prohibitive, cumbersome, or inconvenient.

Ultrastretchable and flexible copper interconnect-based smart patch for adaptive thermotherapy.

Unprecedented 800% stretchable, non-polymeric, widely used, low-cost, naturally rigid, metallic thin-film copper (Cu)-based flexible and non-invasive, spatially tunable, mobile thermal patch with wireless controllability, adaptability (tunes the amount of heat based on the temperature of the swollen portion), reusability, and affordability due to low-cost complementary metal oxide semiconductor (CMOS) compatible integration.