Using internet and mobile phone technology to deliver an automated physical activity program: randomized controlled trial

BACKGROUND

The Internet has potential as a medium for health behavior change programs, but no controlled studies have yet evaluated the impact of a fully automated physical activity intervention over several months with real-time objective feedback from a monitor.

OBJECTIVE

The aim was to evaluate the impact of a physical activity program based on the Internet and mobile phone technology provided to individuals for 9 weeks.

METHODS

A single-center, randomized, stratified controlled trial was conducted from September to December 2005 in Bedfordshire, United Kingdom, with 77 healthy adults whose mean age was 40.4 years (SD = 7.6) and mean body mass index was 26.3 (SD = 3.4). Participants were randomized to a test group that had access to an Internet and mobile phone-based physical activity program (n = 47) or to a control group (n = 30) that received no support. The test group received tailored solutions for perceived barriers, a schedule to plan weekly exercise sessions with mobile phone and email reminders, a message board to share their experiences with others, and feedback on their level of physical activity. Both groups were issued a wrist-worn accelerometer to monitor their level of physical activity; only the test group received real-time feedback via the Internet. The main outcome measures were accelerometer data and self-report of physical activity.

RESULTS

At the end of the study period, the test group reported a significantly greater increase over baseline than did the control group for perceived control (P < .001) and intention/expectation to exercise (P < .001). Intent-to-treat analyses of both the accelerometer data (P = .02) and leisure time self-report data (P = .03) found a higher level of moderate physical activity in the test group. The average increase (over the control group) in accelerometer-measured moderate physical activity was 2 h 18 min per week. The test group also lost more percent body fat than the control group (test group: -2.18, SD = 0.59; control group: -0.17, SD = 0.81; P = .04).

CONCLUSIONS

A fully automated Internet and mobile phone-based motivation and action support system can significantly increase and maintain the level of physical activity in healthy adults.

Digital technology for treating and preventing mental disorders in low-income and middle-income countries: a narrative review of the literature

Few individuals living with mental disorders around the globe have access to mental health care, yet most have access to a mobile phone. Digital technology holds promise for improving access to, and quality of, mental health care. We reviewed evidence on the use of mobile, online, and other remote technologies for treatment and prevention of mental disorders in low-income and middle-income countries. Of the 49 studies identified, most were preliminary evaluations of feasibility and acceptability. The findings were promising, showing the potential effectiveness of online, text-messaging, and telephone support interventions. We summarised the evaluations as: technology for supporting clinical care and educating health workers, mobile tools for facilitating diagnosis and detection of mental disorders, technologies for promoting treatment adherence and supporting recovery, online self-help programmes for individuals with mental disorders, and programmes for substance misuse prevention and treatment. Continued research is needed to rigorously evaluate effectiveness, assess costs, and carefully consider potential risks of digital technology interventions for mental disorders, while determining how emerging technologies might support the scale-up of mental health treatment and prevention efforts across low-resource settings.

Integrated rapid-diagnostic-test reader platform on a cellphone

We demonstrate a cellphone-based rapid-diagnostic-test (RDT) reader platform that can work with various lateral flow immuno-chromatographic assays and similar tests to sense the presence of a target analyte in a sample. This compact and cost-effective digital RDT reader, weighing only ~65 g, mechanically attaches to the existing camera unit of a cellphone, where various types of RDTs can be inserted to be imaged in reflection or transmission modes under light-emitting diode (LED)-based illumination. Captured raw images of these tests are then digitally processed (within less than 0.2 s per image) through a smart application running on the cellphone for validation of the RDT, as well as for automated reading of its diagnostic result. The same smart application then transmits the resulting data, together with the RDT images and other related information (e.g., demographic data), to a central server, which presents the diagnostic results on a world map through geo-tagging. This dynamic spatio-temporal map of various RDT results can then be viewed and shared using internet browsers or through the same cellphone application. We tested this platform using malaria, tuberculosis (TB) and HIV RDTs by installing it on both Android-based smartphones and an iPhone. Providing real-time spatio-temporal statistics for the prevalence of various infectious diseases, this smart RDT reader platform running on cellphones might assist healthcare professionals and policymakers to track emerging epidemics worldwide and help epidemic preparedness.

Cellphone-Based Hand-Held Microplate Reader for Point-of-Care Testing of Enzyme-Linked Immunosorbent Assays

Standard microplate based enzyme-linked immunosorbent assays (ELISA) are widely utilized for various nanomedicine, molecular sensing, and disease screening applications, and this multiwell plate batched analysis dramatically reduces diagnosis costs per patient compared to nonbatched or nonstandard tests. However, their use in resource-limited and field-settings is inhibited by the necessity for relatively large and expensive readout instruments. To mitigate this problem, we created a hand-held and cost-effective cellphone-based colorimetric microplate reader, which uses a 3D-printed opto-mechanical attachment to hold and illuminate a 96-well plate using a light-emitting-diode (LED) array. This LED light is transmitted through each well, and is then collected via 96 individual optical fibers. Captured images of this fiber-bundle are transmitted to our servers through a custom-designed app for processing using a machine learning algorithm, yielding diagnostic results, which are delivered to the user within ∼1 min per 96-well plate, and are visualized using the same app. We successfully tested this mobile platform in a clinical microbiology laboratory using FDA-approved mumps IgG, measles IgG, and herpes simplex virus IgG (HSV-1 and HSV-2) ELISA tests using a total of 567 and 571 patient samples for training and blind testing, respectively, and achieved an accuracy of 99.6%, 98.6%, 99.4%, and 99.4% for mumps, measles, HSV-1, and HSV-2 tests, respectively. This cost-effective and hand-held platform could assist health-care professionals to perform high-throughput disease screening or tracking of vaccination campaigns at the point-of-care, even in resource-poor and field-settings. Also, its intrinsic wireless connectivity can serve epidemiological studies, generating spatiotemporal maps of disease prevalence and immunity.

Cost-effective and compact wide-field fluorescent imaging on a cell-phone

We demonstrate wide-field fluorescent and darkfield imaging on a cell-phone with compact, light-weight and cost-effective optical components that are mechanically attached to the existing camera unit of the cell-phone. For this purpose, we used battery powered light-emitting diodes (LEDs) to pump the sample of interest from the side using butt-coupling, where the pump light was guided within the sample cuvette to uniformly excite the specimen. The fluorescent emission from the sample was then imaged using an additional lens that was positioned right in front of the existing lens of the cell-phone camera. Because the excitation occurs through guided waves that propagate perpendicular to our detection path, an inexpensive plastic colour filter was sufficient to create the dark-field background required for fluorescent imaging, without the need for a thin-film interference filter. We validate the performance of this platform by imaging various fluorescent micro-objects in 2 colours (i.e., red and green) over a large field-of-view (FOV) of ∼81 mm(2) with a raw spatial resolution of ∼20 μm. With additional digital processing of the captured cell-phone images, through the use of compressive sampling theory, we demonstrate ∼2 fold improvement in our resolving power, achieving ∼10 μm resolution without a trade-off in our FOV. Further, we also demonstrate darkfield imaging of non-fluorescent specimen using the same interface, where this time the scattered light from the objects is detected without the use of any filters. The capability of imaging a wide FOV would be exceedingly important to probe large sample volumes (e.g., >0.1 mL) of e.g., blood, urine, sputum or water, and for this end we also demonstrate fluorescent imaging of labeled white-blood cells from whole blood samples, as well as water-borne pathogenic protozoan parasites such as Giardia Lamblia cysts. Weighing only ∼28 g (∼1 ounce), this compact and cost-effective fluorescent imaging platform attached to a cell-phone could be quite useful especially for resource-limited settings, and might provide an important tool for wide-field imaging and quantification of various lab-on-a-chip assays developed for global health applications, such as monitoring of HIV+ patients for CD4 counts or viral load measurements.

Validity of the Remote Food Photography Method (RFPM) for estimating energy and nutrient intake in near real-time

Two studies are reported; a pilot study to demonstrate feasibility followed by a larger validity study. Study 1's objective was to test the effect of two ecological momentary assessment (EMA) approaches that varied in intensity on the validity/accuracy of estimating energy intake (EI) with the Remote Food Photography Method (RFPM) over 6 days in free-living conditions. When using the RFPM, Smartphones are used to capture images of food selection and plate waste and to send the images to a server for food intake estimation. Consistent with EMA, prompts are sent to the Smartphones reminding participants to capture food images. During Study 1, EI estimated with the RFPM and the gold standard, doubly labeled water (DLW), were compared. Participants were assigned to receive Standard EMA Prompts (n = 24) or Customized Prompts (n = 16) (the latter received more reminders delivered at personalized meal times). The RFPM differed significantly from DLW at estimating EI when Standard (mean ± s.d. = -895 ± 770 kcal/day, P < 0.0001), but not Customized Prompts (-270 ± 748 kcal/day, P = 0.22) were used. Error (EI from the RFPM minus that from DLW) was significantly smaller with Customized vs. Standard Prompts. The objectives of Study 2 included testing the RFPM's ability to accurately estimate EI in free-living adults (N = 50) over 6 days, and energy and nutrient intake in laboratory-based meals. The RFPM did not differ significantly from DLW at estimating free-living EI (-152 ± 694 kcal/day, P = 0.16). During laboratory-based meals, estimating energy and macronutrient intake with the RFPM did not differ significantly compared to directly weighed intake.

Cell-phone-based platform for biomedical device development and education applications

In this paper we report the development of two attachments to a commercial cell phone that transform the phone's integrated lens and image sensor into a 350x microscope and visible-light spectrometer. The microscope is capable of transmission and polarized microscopy modes and is shown to have 1.5 micron resolution and a usable field-of-view of 150 x 50 with no image processing, and approximately 350 x 350 when post-processing is applied. The spectrometer has a 300 nm bandwidth with a limiting spectral resolution of close to 5 nm. We show applications of the devices to medically relevant problems. In the case of the microscope, we image both stained and unstained blood-smears showing the ability to acquire images of similar quality to commercial microscope platforms, thus allowing diagnosis of clinical pathologies. With the spectrometer we demonstrate acquisition of a white-light transmission spectrum through diffuse tissue as well as the acquisition of a fluorescence spectrum. We also envision the devices to have immediate relevance in the educational field.

Mechanism of short-term ERK activation by electromagnetic fields at mobile phone frequencies

The exposure to non-thermal microwave electromagnetic fields generated by mobile phones affects the expression of many proteins. This effect on transcription and protein stability can be mediated by the MAPK (mitogen-activated protein kinase) cascades, which serve as central signalling pathways and govern essentially all stimulated cellular processes. Indeed, long-term exposure of cells to mobile phone irradiation results in the activation of p38 as well as the ERK (extracellular-signal-regulated kinase) MAPKs. In the present study, we have studied the immediate effect of irradiation on the MAPK cascades, and found that ERKs, but not stress-related MAPKs, are rapidly activated in response to various frequencies and intensities. Using signalling inhibitors, we delineated the mechanism that is involved in this activation. We found that the first step is mediated in the plasma membrane by NADH oxidase, which rapidly generates ROS (reactive oxygen species). These ROS then directly stimulate MMPs (matrix metalloproteinases) and allow them to cleave and release Hb-EGF [heparin-binding EGF (epidermal growth factor)]. This secreted factor activates the EGF receptor, which in turn further activates the ERK cascade. Thus this study demonstrates for the first time a detailed molecular mechanism by which electromagnetic irradiation from mobile phones induces the activation of the ERK cascade and thereby induces transcription and other cellular processes.

Implementation of a WAP-based telemedicine system for patient monitoring

Many parties have already demonstrated telemedicine applications that use cellular phones and the Internet. A current trend in telecommunication is the convergence of wireless communication and computer network technologies, and the emergence of wireless application protocol (WAP) devices is an example. Since WAP will also be a common feature found in future mobile communication devices, it is worthwhile to investigate its use in telemedicine. This paper describes the implementation and experiences with a WAP-based telemedicine system for patient-monitoring that has been developed in our laboratory. It utilizes WAP devices as mobile access terminals for general inquiry and patient-monitoring services. Authorized users can browse the patients' general data, monitored blood pressure (BP), and electrocardiogram (ECG) on WAP devices in store-and-forward mode. The applications, written in wireless markup language (WML), WMLScript, and Perl, resided in a content server. A MySQL relational database system was set up to store the BP readings, ECG data, patient records, clinic and hospital information, and doctors' appointments with patients. A wireless ECG subsystem was built for recording ambulatory ECG in an indoor environment and for storing ECG data into the database. For testing, a WAP phone compliant with WAP 1.1 was used at GSM 1800 MHz by circuit-switched data (CSD) to connect to the content server through a WAP gateway, which was provided by a mobile phone service provider in Hong Kong. Data were successfully retrieved from the database and displayed on the WAP phone. The system shows how WAP can be feasible in remote patient-monitoring and patient data retrieval.

The Stroop smartphone application is a short and valid method to screen for minimal hepatic encephalopathy

Minimal hepatic encephalopathy (MHE) detection is difficult because of the unavailability of short screening tools. Therefore, MHE patients can remain undiagnosed and untreated. The aim of this study was to use a Stroop smartphone application (app) (EncephalApp_Stroop) to screen for MHE. The app and standard psychometric tests (SPTs; 2 of 4 abnormal is MHE, gold standard), psychometric hepatic encephalopathy score (PHES), and inhibitory control tests (ICTs) were administered to patients with cirrhosis (with or without previous overt hepatic encephalopathy; OHE) and age-matched controls from two centers; a subset underwent retesting. A separate validation cohort was also recruited. Stroop has an "off" state with neutral stimuli and an "on" state with incongruent stimuli. Outcomes included time to complete five correct runs as well as number of trials needed in on (Ontime) and off (Offtime) states. Stroop results were compared between controls and patients with cirrhosis with or without OHE and those with or without MHE (using SPTs, ICTs, and PHES). Receiver operating characteristic analysis was performed to diagnose MHE in patients with cirrhosis with or without previous OHE. One hundred and twenty-five patients with cirrhosis (43 previous OHE) and 134 controls were included in the original cohort. App times were correlated with Model for End-Stage Liver Disease (Offtime: r = 0.57; Ontime: r = 0.61; P < 0.0001) and were worst in previous OHE patients, compared to the rest and controls. Stroop performance was also significantly impaired in those with MHE, compared to those without MHE, according to SPTs, ICTs, and PHES (all P < 0.0001). A cutoff of >274.9 seconds (Ontime plus Offtime) had an area under the curve of 0.89 in all patients and 0.84 in patients without previous OHE for MHE diagnosis using SPT as the gold standard. The validation cohort showed 78% sensitivity and 90% specificity with the >274.9-seconds Ontime plus Offtime cutoff. App result patterns were similar between the centers. Test-retest reliability in controls and those without previous OHE was good; a learning effect on Ontime in patients with cirrhosis without previous OHE was noted.

CONCLUSION

The Stroop smartphone app is a short, valid, and reliable tool for screening of MHE.

A personalized food allergen testing platform on a cellphone

We demonstrate a personalized food allergen testing platform, termed iTube, running on a cellphone that images and automatically analyses colorimetric assays performed in test tubes toward sensitive and specific detection of allergens in food samples. This cost-effective and compact iTube attachment, weighing approximately 40 grams, is mechanically installed on the existing camera unit of a cellphone, where the test and control tubes are inserted from the side and are vertically illuminated by two separate light-emitting-diodes. The illumination light is absorbed by the allergen assay, which is activated within the tubes, causing an intensity change in the acquired images by the cellphone camera. These transmission images of the sample and control tubes are digitally processed within 1 s using a smart application running on the same cellphone for detection and quantification of allergen contamination in food products. We evaluated the performance of this cellphone-based iTube platform using different types of commercially available cookies, where the existence of peanuts was accurately quantified after a sample preparation and incubation time of ~20 min per test. This automated and cost-effective personalized food allergen testing tool running on cellphones can also permit uploading of test results to secure servers to create personal and/or public spatio-temporal allergen maps, which can be useful for public health in various settings.

Use of SMS text messaging to improve outpatient attendance

OBJECTIVE

To evaluate the effect of appointment reminders sent as short message service (SMS) text messages to patients' mobile telephones on attendance at outpatient clinics.

DESIGN

Cohort study with historical control.

SETTING

Royal Children's Hospital, Melbourne, Victoria.

PATIENTS

Patients who gave a mobile telephone contact number and were scheduled to attend any of five outpatient clinics (dermatology, gastroenterology, general medicine, paediatric dentistry and plastic surgery) in September (trial group) or August (control group), 2004.

MAIN OUTCOME MEASURES

Failure to attend (FTA) rate compared between the group sent a reminder and those who were not.

RESULTS

2151 patients were scheduled to attend a clinic in September; 1382 of these (64.2%) gave a mobile telephone contact number and were sent an SMS reminder (trial group). Corresponding numbers in the control group were 2276 scheduled to attend and 1482 (65.1%) who gave a mobile telephone number. The FTA rate for individual clinics was 12%-16% for the trial group, and 19%-39% for the control group. Overall FTA rate was significantly lower in the trial group than in the control group (14.2% v 23.4%; P < 0.001).

CONCLUSIONS

The observed reduction in failure to attend rate was in line with that found using traditional reminder methods. The ease with which large numbers of messages can be customised and sent by SMS text messaging, along with its availability and comparatively low cost, suggest it may be a suitable means of improving patient attendance.

Identifying Objective Physiological Markers and Modifiable Behaviors for Self-Reported Stress and Mental Health Status Using Wearable Sensors and Mobile Phones: Observational Study

BACKGROUND

Wearable and mobile devices that capture multimodal data have the potential to identify risk factors for high stress and poor mental health and to provide information to improve health and well-being.

OBJECTIVE

We developed new tools that provide objective physiological and behavioral measures using wearable sensors and mobile phones, together with methods that improve their data integrity. The aim of this study was to examine, using machine learning, how accurately these measures could identify conditions of self-reported high stress and poor mental health and which of the underlying modalities and measures were most accurate in identifying those conditions.

METHODS

We designed and conducted the 1-month SNAPSHOT study that investigated how daily behaviors and social networks influence self-reported stress, mood, and other health or well-being-related factors. We collected over 145,000 hours of data from 201 college students (age: 18-25 years, male:female=1.8:1) at one university, all recruited within self-identified social groups. Each student filled out standardized pre- and postquestionnaires on stress and mental health; during the month, each student completed twice-daily electronic diaries (e-diaries), wore two wrist-based sensors that recorded continuous physical activity and autonomic physiology, and installed an app on their mobile phone that recorded phone usage and geolocation patterns. We developed tools to make data collection more efficient, including data-check systems for sensor and mobile phone data and an e-diary administrative module for study investigators to locate possible errors in the e-diaries and communicate with participants to correct their entries promptly, which reduced the time taken to clean e-diary data by 69%. We constructed features and applied machine learning to the multimodal data to identify factors associated with self-reported poststudy stress and mental health, including behaviors that can be possibly modified by the individual to improve these measures.

RESULTS

We identified the physiological sensor, phone, mobility, and modifiable behavior features that were best predictors for stress and mental health classification. In general, wearable sensor features showed better classification performance than mobile phone or modifiable behavior features. Wearable sensor features, including skin conductance and temperature, reached 78.3% (148/189) accuracy for classifying students into high or low stress groups and 87% (41/47) accuracy for classifying high or low mental health groups. Modifiable behavior features, including number of naps, studying duration, calls, mobility patterns, and phone-screen-on time, reached 73.5% (139/189) accuracy for stress classification and 79% (37/47) accuracy for mental health classification.

CONCLUSIONS

New semiautomated tools improved the efficiency of long-term ambulatory data collection from wearable and mobile devices. Applying machine learning to the resulting data revealed a set of both objective features and modifiable behavioral features that could classify self-reported high or low stress and mental health groups in a college student population better than previous studies and showed new insights into digital phenotyping.

Gene-Z: a device for point of care genetic testing using a smartphone

By 2012, point of care (POC) testing will constitute roughly one third of the $59 billion in vitro diagnostics market. The ability to carry out multiplexed genetic testing and wireless connectivity are emerging as key attributes of future POC devices. In this study, an inexpensive, user-friendly and compact device (termed Gene-Z) is presented for rapid quantitative detection of multiple genetic markers with high sensitivity and specificity. Using a disposable valve-less polymer microfluidic chip containing four arrays of 15 reaction wells each with dehydrated primers for isothermal amplification, the Gene-Z enables simultaneous analysis of four samples, each for multiple genetic markers in parallel, requiring only a single pipetting step per sample for dispensing. To drastically reduce the cost and size of the real-time detector necessary for quantification, loop-mediated isothermal amplification (LAMP) was performed with a high concentration of SYTO-81, a non-inhibiting fluorescent DNA binding dye. The Gene-Z is operated using an iPod Touch, which also receives data and carries out automated analysis and reporting via a WiFi interface. This study presents data pertaining to performance of the device including sensitivity and reproducibility using genomic DNA from Escherichia coli and Staphylococcus aureus. Overall, the Gene-Z represents a significant step toward truly inexpensive and compact tools for POC genetic testing.

Albumin testing in urine using a smart-phone

We demonstrate a digital sensing platform, termed Albumin Tester, running on a smart-phone that images and automatically analyses fluorescent assays confined within disposable test tubes for sensitive and specific detection of albumin in urine. This light-weight and compact Albumin Tester attachment, weighing approximately 148 grams, is mechanically installed on the existing camera unit of a smart-phone, where test and control tubes are inserted from the side and are excited by a battery powered laser diode. This excitation beam, after probing the sample of interest located within the test tube, interacts with the control tube, and the resulting fluorescent emission is collected perpendicular to the direction of the excitation, where the cellphone camera captures the images of the fluorescent tubes through the use of an external plastic lens that is inserted between the sample and the camera lens. The acquired fluorescent images of the sample and control tubes are digitally processed within one second through an Android application running on the same cellphone for quantification of albumin concentration in the urine specimen of interest. Using a simple sample preparation approach which takes ~5 min per test (including the incubation time), we experimentally confirmed the detection limit of our sensing platform as 5-10 μg mL(-1) (which is more than 3 times lower than the clinically accepted normal range) in buffer as well as urine samples. This automated albumin testing tool running on a smart-phone could be useful for early diagnosis of kidney disease or for monitoring of chronic patients, especially those suffering from diabetes, hypertension, and/or cardiovascular diseases.

Recovery of lithium and cobalt from waste lithium ion batteries of mobile phone

In view of the stringent environmental regulations, availability of limited natural resources and ever increasing need of alternative energy critical elements, an environmental eco-friendly leaching process is reported for the recovery of lithium and cobalt from the cathode active materials of spent lithium-ion batteries of mobile phones. The experiments were carried out to optimize the process parameters for the recovery of lithium and cobalt by varying the concentration of leachant, pulp density, reductant volume and temperature. Leaching with 2M sulfuric acid with the addition of 5% H(2)O(2) (v/v) at a pulp density of 100 g/L and 75°C resulted in the recovery of 99.1% lithium and 70.0% cobalt in 60 min. H(2)O(2) in sulfuric acid solution acts as an effective reducing agent, which enhance the percentage leaching of metals. Leaching kinetics of lithium in sulfuric acid fitted well to the chemical controlled reaction model i.e. 1-(1-X)(1/3)=k(c)t. Leaching kinetics of cobalt fitted well to the model 'ash diffusion control dense constant sizes spherical particles' i.e. 1-3(1-X)(2/3)+2(1-X)=k(c)t. Metals could subsequently be separated selectively from the leach liquor by solvent extraction process to produce their salts by crystallization process from the purified solution.

Low-cost mobile phone microscopy with a reversed mobile phone camera lens

The increasing capabilities and ubiquity of mobile phones and their associated digital cameras offer the possibility of extending low-cost, portable diagnostic microscopy to underserved and low-resource areas. However, mobile phone microscopes created by adding magnifying optics to the phone's camera module have been unable to make use of the full image sensor due to the specialized design of the embedded camera lens, exacerbating the tradeoff between resolution and field of view inherent to optical systems. This tradeoff is acutely felt for diagnostic applications, where the speed and cost of image-based diagnosis is related to the area of the sample that can be viewed at sufficient resolution. Here we present a simple and low-cost approach to mobile phone microscopy that uses a reversed mobile phone camera lens added to an intact mobile phone to enable high quality imaging over a significantly larger field of view than standard microscopy. We demonstrate use of the reversed lens mobile phone microscope to identify red and white blood cells in blood smears and soil-transmitted helminth eggs in stool samples.

An ethical framework for automated, wearable cameras in health behavior research

Technologic advances mean automated, wearable cameras are now feasible for investigating health behaviors in a public health context. This paper attempts to identify and discuss the ethical implications of such research, in relation to existing guidelines for ethical research in traditional visual methodologies. Research using automated, wearable cameras can be very intrusive, generating unprecedented levels of image data, some of it potentially unflattering or unwanted. Participants and third parties they encounter may feel uncomfortable or that their privacy has been affected negatively. This paper attempts to formalize the protection of all according to best ethical principles through the development of an ethical framework. Respect for autonomy, through appropriate approaches to informed consent and adequate privacy and confidentiality controls, allows for ethical research, which has the potential to confer substantial benefits on the field of health behavior research.

Rapid electrochemical detection on a mobile phone

We present a compact mobile phone platform for rapid, quantitative biomolecular detection. This system consists of an embedded circuit for signal processing and data analysis, and disposable microfluidic chips for fluidic handling and biosensing. Capillary flow is employed for sample loading, processing, and pumping to enhance operational portability and simplicity. Graphical step-by-step instructions displayed on the phone assists the operator through the detection process. After the completion of each measurement, the results are displayed on the screen for immediate assessment and the data is automatically saved to the phone's memory for future analysis and transmission. Validation of this device was carried out by detecting Plasmodium falciparum histidine-rich protein 2 (PfHRP2), an important biomarker for malaria, with a lower limit of detection of 16 ng mL(-1) in human serum. The simple detection process can be carried out with two loading steps and takes 15 min to complete each measurement. Due to its compact size and high performance, this device offers immense potential as a widely accessible, point-of-care diagnostic platform, especially in remote and rural areas. In addition to its impact on global healthcare, this technology is relevant to other important applications including food safety, environmental monitoring and biosecurity.

Mobile health applications to assist patients with diabetes: lessons learned and design implications

Self-management is critical to achieving diabetes treatment goals. Mobile phones and Bluetooth® can supportself-management and lifestyle changes for chronic diseases such as diabetes. A mobile health (mHealth) research platform--the Few Touch Application (FTA)--is a tool designed to support the self-management of diabetes. The FTA consists of a mobile phone-based diabetes diary, which can be updated both manually from user input and automatically by wireless data transfer, and which provides personalized decision support for the achievement of personal health goals. Studies and applications (apps) based on FTAs have included: (1) automatic transfer of blood glucose (BG) data; (2) short message service (SMS)-based education for type 1diabetes (T1DM); (3) a diabetes diary for type 2 diabetes (T2DM); (4) integrating a patient diabetes diary with health care (HC) providers; (5) a diabetes diary for T1DM; (6) a food picture diary for T1DM; (7) physical activity monitoring for T2DM; (8) nutrition information for T2DM; (9) context sensitivity in mobile self-help tools; and (10) modeling of BG using mobile phones. We have analyzed the performance of these 10 FTA-based apps to identify lessons for designing the most effective mHealth apps. From each of the 10 apps of FTA, respectively, we conclude: (1) automatic BG data transfer is easy to use and provides reassurance; (2) SMS-based education facilitates parent-child communication in T1DM; (3) the T2DM mobile phone diary encourages reflection; (4) the mobile phone diary enhances discussion between patients and HC professionals; (5) the T1DM mobile phone diary is useful and motivational; (6) the T1DM mobile phone picture diary is useful in identifying treatment obstacles; (7) the step counter with automatic data transfer promotes motivation and increases physical activity in T2DM; (8) food information on a phone for T2DM should not be at a detailed level; (9) context sensitivity has good prospects and is possible to implement on today's phones; and (10) BG modeling on mobile phones is promising for motivated T1DM users. We expect that the following elements will be important in future FTA designs: (A) automatic data transfer when possible; (B) motivational and visual user interfaces; (C) apps with considerable health benefits in relation to the effort required; (D) dynamic usage, e.g., both personal and together with HC personnel, long-/short-term perspective; and (E) inclusion of context sensitivity in apps. We conclude that mHealth apps will empower patients to take a more active role in managing their own health.

Desired features of smartphone applications promoting physical activity

Approximately one-third of adults in the United States are physically inactive. This is a significant public health concern as physical activity (PA) can influence the risk of cardiovascular disease, diabetes, and certain forms of cancer. To minimize these health risks, effective PA interventions must be developed and disseminated to the vast number of individuals who remain sedentary. Smartphone technology presents an exciting opportunity for delivering PA interventions remotely. Although a number of PA applications are currently available for smartphones, these "apps" are not based on established theories of health behavior change and most do not include evidence-based features (e.g., reinforcement and goal setting). Our aim was to collect formative data to develop a smartphone PA app that is empirically and theoretically-based and incorporates user preferences. We recruited 15 sedentary adults to test three currently available PA smartphone apps and provide qualitative and quantitative feedback. Findings indicate that users have a number of specific preferences with regard to PA app features, including that apps provide automatic tracking of PA (e.g., steps taken and calories burned), track progress toward PA goals, and integrate a music feature. Participants also preferred that PA apps be flexible enough to be used with several types of PA, and have well-documented features and user-friendly interfaces (e.g., a one-click main page). When queried by the researcher, most participants endorsed including goal-setting and problem-solving features. These findings provide a blue print for developing a smartphone PA app that incorporates evidence-based components and user preferences.

Whole body exposure of rats to microwaves emitted from a cell phone does not affect the testes

The objective of this study was to investigate the effects of radiofrequency radiation emitted from cellular phones on the lipid composition, malondialdehyde concentration, p53 immune reactivity, sperm count, morphology, histological structure of testes, and on rectal temperature of rats exposed to microwave radiation emitted from cellular phones. Sixteen Spraque-Dawley rats were separated into two groups of eight, sham exposed (control) and experimental. The rats were confined in plexiglas cages specially designed for this study, and cellular phones were placed 0.5 cm under the cages. For the experimental group, cellular phones were activated 20 min per day (7 days a week) for 1 month. For the control group, the cellular phones were placed beneath the cages for 20 min a day, but the phones were turned off. Rectal temperatures were measured weekly. For 250 mW radiated power, the whole body average SAR (rms) is 0.52 W/kg and 1 g averaged peak SAR (rms) is 3.13 W/kg. The Mann-Whitney U-test was used for statistical comparisons of groups. No statistically significant alteration in any of the endpoints was noted. This study found no evidence suggesting an adverse effect of cell phone exposure on measures of testicular function or structure.

The SmartCAT: an m-health platform for ecological momentary intervention in child anxiety treatment

INTRODUCTION

Cognitive behavioral therapy (CBT) for child anxiety, although efficacious, typically requires 16-20 weekly sessions with a therapist. Brief CBT (BCBT; eight sessions) for child anxiety is promising but may have less favorable outcomes owing to reduced session time. Mobile health (m-health) has the potential to improve BCBT efficacy by delivering ecological momentary intervention to engage youth in learning and practicing CBT skills in their everyday lives (in vivo).

MATERIALS AND METHODS

We developed an m-health platform entitled SmartCAT (Smartphone-enhanced Child Anxiety Treatment). SmartCAT consists of (1) a smartphone application (app) that cues youth to use the CBT skills taught in sessions, (2) an online portal that allows therapists to monitor skill use, to send cues and treatment-related materials, to engage youth in real-time via secure messages, and to manage rewards, and (3) a communication protocol that allows real-time bidirectional exchange between the app and the portal. A pilot study with nine youth (9-14 years old) examined the platform's feasibility as an adjunct to BCBT.

RESULTS

SmartCAT was found to be capable of supporting BCBT for child anxiety and received positive feedback from both therapists and youth patients. Patients rated the app as highly usable (mean=1.7 on a 1-7 scale, with 1="easy"). Patients completed 5.36 skills coach entries per session (standard deviation=1.95) and took an average of 3.14 min (standard deviation=0.98 min) to complete the entries.

CONCLUSIONS

A smartphone app is feasible within CBT for child anxiety. Users found SmartCAT both acceptable and easy to use. Integrating an m-health platform within BCBT for anxious children may facilitate involvement in treatment and dissemination of effective procedures.

Application of mobile teledermatology for skin cancer screening

BACKGROUND

With advancements in mobile technology, cellular phone-based store-and-forward teledermatology may be applied to skin cancer screening.

OBJECTIVE

We sought to determine diagnostic and management concordance between in-person and teledermatology evaluations for patients at skin cancer screening whose clinical images and history were transmitted through mobile phones.

METHODS

A total of 86 patients with 137 skin lesions presented to a skin cancer screening event in California. These patients' clinical history and skin images were captured by a software-enabled mobile phone. Patients were assessed separately by an in-person dermatologist and a teledermatologist, who evaluated the mobile phone-transmitted history and images. Diagnostic and management concordance was determined between the in-person and teledermatology evaluations.

RESULTS

The primary categorical diagnostic concordance was 82% between the in-person dermatologist and the teledermatologist (95% confidence interval 0.73-0.89), with a Kappa coefficient of 0.62 indicating good agreement. The aggregated diagnostic concordance between the in-person dermatologist and the teledermatologist was 62% (95% confidence interval 0.51-0.71), with Kappa coefficient of 0.60 indicating good agreement. Management concordance between the in-person dermatologist and the teledermatologist was 81% (95% confidence interval 0.72-0.88), with a Kappa coefficient of 0.57, which indicates moderate agreement between the dermatologists. Multivariate analysis showed that older age and presentation of atypical nevus were significantly associated with disagreement in diagnosis between the teledermatologist and in-person dermatologist, after adjusting for other factors.

LIMITATIONS

Dermatoscopic images were not captured via mobile phones, which might improve diagnostic accuracy.

CONCLUSION

Mobile teledermatology using cellular phones is an innovative and convenient modality of providing dermatologic consultations for skin cancer screening.

Variability in and agreement between modeled and personal continuously measured black carbon levels using novel smartphone and sensor technologies

Novel technologies, such as smartphones and small personal continuous air pollution sensors, can now facilitate better personal estimates of air pollution in relation to location. Such information can provide us with a better understanding about whether and how personal exposures relate to residential air pollution estimates, which are normally used in epidemiological studies. The aims of this study were to examine (1) the variability in personal air pollution levels during the day and (2) the relationship between modeled home and school estimates and continuously measured personal air pollution exposure levels in different microenvironments (e.g., home, school, and commute). We focused on black carbon as an indicator of traffic-related air pollution. We recruited 54 school children (aged 7-11) from 29 different schools around Barcelona as part of the BREATHE study, an epidemiological study of the relation between air pollution and brain development. For 2 typical week days during 2012-2013, the children were given a smartphone with CalFit software to obtain information on their location and physical activity level and a small sensor, the micro-aethalometer model AE51, to measure their black carbon levels simultaneously and continuously. We estimated their home and school exposure to PM2.5 filter absorbance, which is well-correlated with black carbon, using a temporally adjusted PM2.5 absorbance land use regression (LUR) model. We found considerable variation in the black carbon levels during the day, with the highest levels measured during commuting periods (geometric mean = 2.8 μg/m(3)) and the lowest levels at home (geometric mean = 1.3 μg/m(3)). Hourly temporally adjusted LUR model estimates for the home and school showed moderate to good correlation with measured personal black carbon levels at home and school (r = 0.59 and 0.68, respectively) and lower correlation with commuting trips (r = 0.32 and 0.21, respectively). The correlation between modeled home estimates and overall personal black carbon levels was 0.62. Personal black carbon levels vary substantially during the day. The correlation between modeled and measured black carbon levels was generally good, with the exception of commuting times. In conclusion, novel technologies, such as smartphones and sensors, provide insights in personal exposure to air pollution.