A step towards mobile arsenic measurement for surface waters.

Surface modified quantum dots (QDs) are studied using a bio-inspired cysteine rich ligand (glutathione, GSH) and their quenching response and selectivity to arsenic examined. As predicted from As(3+) binding with highly crosslinked phytochelatin-(PCn)-like molecules, better arsenic selectivity is obtained for a thicker more 3-dimensional GSH surface layer, with exposed sulfhydryl groups. A detection limit of at least 10 μM can be achieved using CdSe/ZnS core-shell QDs capped with this GSH structure. The system is also demonstrated using a mobile phone camera to record the measurement, producing a detection limit of 5 μM. However, copper remains the main interferent of concern. Water-soluble CdTe QDs show little sensitivity to As(3+) even with a GSH surface, but they remain sensitive to Cu(2+), allowing a copper baseline to be established from the CdTe measurement. Despite anticipating that spectrally non overlapping fluorescence would be required from the two types of QDs to achieve this, a method is demonstrated using RGB channels from a mobile phone and processing the raw data for CdTe QDs, with an emission wavelength of 600 nm, and CdSe/ZnS QDs, with emission maximum of 630 nm. It is shown that As(3+) measurement remains feasible at the WHO guideline value of 10 μg L(-1) up to a copper concentration of around 0.3 μM Cu(2+), which corresponds to the highest recorded level in a selection of large rivers world-wide.This is the author accepted manuscript. The final version is available via RSC at http://pubs.rsc.org/en/Content/ArticleLanding/2015/AN/c4an02368d#!divAbstract

A user-centred approach to developing bWell, a mobile app for arm and shoulder exercises after breast cancer treatment

Purpose: The study aim was to develop a mobile application (app) supported by user preferences to optimise self-management of arm and shoulder exercises for upper-limb dysfunction (ULD) after breast cancer treatment. Methods: Focus groups with breast cancer patients were held to identify user needs and requirements. Behaviour change techniques were explored by researchers and discussed during the focus groups. Concepts for content were identified by thematic analysis. A rapid review was conducted to inform the exercise programme. Preliminary testing was carried out to obtain user feedback from breast cancer patients who used the app for 8 weeks post-surgery. Results: Breast cancer patients’ experiences with ULD and exercise advice and routines varied widely. They identified and prioritised several app features: tailored information, video demonstrations of the exercises, push notifications, and tracking and progress features. An evidence-based programme was developed with a physiotherapist with progressive exercises for passive and active mobilisation, stretching and strengthening. The exercise demonstration videos were filmed with a breast cancer patient. Early user testing demonstrated ease of use, and clear and motivating app content. Conclusions: bWell, a novel app for arm and shoulder exercises was developed by breast cancer patients, health care professionals and academics. Further research is warranted to confirm its clinical effectiveness. Implications for Cancer Survivors: Mobile health has great potential to provide patients with information specific to their needs. bWell is a promising way to support breast cancer patients with exercise routines after treatment and may improve future self-management of clinical care

Smoking cessation opportunities in severe mental illness (tobacco intensive motivational and estimate risk — TIMER—): study protocol for a randomized controlled trial

There is an increased risk of premature death in people with severe mental illness (SMI). Respiratory disorders and cardiovascular disease are leading causes of increased mortality rates in these patients, and tobacco consumption remains the most preventable risk factor involved. Developing new tools to motivate patients towards cessation of smoking is a high priority. Information on the motivational value of giving the lung age and prevention opportunities is unknown in this high-risk population. In the context of community care, screening and early detection of lung damage could potentially be used, together with mobile technology, in order to produce a prevention message, which may provide patients with SMI with a better chance of quitting smoking.This study receives funding by the Spanish Ministry of Economy, Industry and Competitiveness, Instituto Carlos III (FIS PI16/00802)

What is the economic evidence for mHealth? A systematic review of economic evaluations of mHealth solutions

Background Mobile health (mHealth) is often reputed to be cost-effective or cost-saving. Despite optimism, the strength of the evidence supporting this assertion has been limited. In this systematic review the body of evidence related to economic evaluations of mHealth interventions is assessed and summarized. Methods Seven electronic bibliographic databases, grey literature, and relevant references were searched. Eligibility criteria included original articles, comparison of costs and consequences of interventions (one categorized as a primary mHealth intervention or mHealth intervention as a component of other interventions), health and economic outcomes and published in English. Full economic evaluations were appraised using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist and The PRISMA guidelines were followed. Results Searches identified 5902 results, of which 318 were examined at full text, and 39 were included in this review. The 39 studies spanned 19 countries, most of which were conducted in upper and upper-middle income countries (34, 87.2%). Primary mHealth interventions (35, 89.7%), behavior change communication type interventions (e.g., improve attendance rates, medication adherence) (27, 69.2%), and short messaging system (SMS) as the mHealth function (e.g., used to send reminders, information, provide support, conduct surveys or collect data) (22, 56.4%) were most frequent; the most frequent disease or condition focuses were outpatient clinic attendance, cardiovascular disease, and diabetes. The average percent of CHEERS checklist items reported was 79.6% (range 47.62–100, STD 14.18) and the top quartile reported 91.3–100%. In 29 studies (74.3%), researchers reported that the mHealth intervention was cost-effective, economically beneficial, or cost saving at base case. Conclusions Findings highlight a growing body of economic evidence for mHealth interventions. Although all studies included a comparison of intervention effectiveness of a health-related outcome and reported economic data, many did not report all recommended economic outcome items and were lacking in comprehensive analysis. The identified economic evaluations varied by disease or condition focus, economic outcome measurements, perspectives, and were distributed unevenly geographically, limiting formal meta-analysis. Further research is needed in low and low-middle income countries and to understand the impact of different mHealth types. Following established economic reporting guidelines will improve this body of research