Protection‐adjusted UV dose estimated for body areas: Daily self‐reported sun protection modification of wearable UV sensor dose

Robinson, June K.; Durst, Dalya A.; Gray, Elizabeth; Kwasny, Mary J.

doi:10.1111/phpp.12557

Cited by 9 publications

(10 citation statements)

References 35 publications

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“…The most dominant study design was observational (n=28, 60.9%) [ 17 , 20 , 21 , 23 - 25 , 27 , 28 , 31 , 32 , 34 , 36 - 40 , 42 - 47 , 49 - 51 , 57 , 58 , 60 ], followed by randomized trials (n=10, 21.7%) [ 19 , 22 , 26 , 30 , 35 , 41 , 52 - 55 ], post hoc analyses of RCTs (n=5, 10.9%) [ 18 , 29 , 56 , 59 , 61 ], and post hoc analyses of observational studies (n=3, 6.5%) [ 16 , 33 , 48 ].…”

Section: Resultsmentioning

confidence: 99%

“…A total of 7 (15.2%) studies focused on cardiovascular diseases, which included hypertension [ 19 , 21 , 45 ], hypercholesterolemia [ 56 ], heart failure [ 24 ], and general cardiovascular health [ 32 , 47 ]. Five studies (10.9%) focused on cancer, including skin cancer [ 28 ], melanoma [ 34 , 35 ], breast cancer [ 55 ], and monitoring patients undergoing chemotherapy [ 27 ]. Moreover, 3 (6.5%) focused on diabetes [ 30 , 38 , 52 ], and 7 (15.2%) focused on participants who were overweight or obese [ 16 , 18 , 30 , 33 , 36 , 43 , 59 ].…”

Section: Resultsmentioning

confidence: 99%

“…The categories used to map how active and passive data were collected in the included studies were as follows: wearable device, mobile app, wearable device + mobile app, wearable device + other, and other. Most (n=25, 54.3%) studies fell under the wearable device category [ 16 - 20 , 22 , 24 , 25 , 32 - 34 , 36 , 38 , 43 , 44 , 46 , 47 , 49 - 51 , 55 - 58 , 61 ]. Many (n=14, 30.4%) studies also collected data using a combination of wearable devices and a mobile app and thus fell under the wearable device + mobile app category [ 21 , 23 , 26 - 30 , 35 , 39 , 45 , 48 , 53 , 54 , 60 ].…”

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

Digital Phenotyping in Health Using Machine Learning Approaches: Scoping Review

Dlima¹,

Shevade²,

Menezes³

et al. 2022

JMIR Bioinform Biotech

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Background Digital phenotyping is the real-time collection of individual-level active and passive data from users in naturalistic and free-living settings via personal digital devices, such as mobile phones and wearable devices. Given the novelty of research in this field, there is heterogeneity in the clinical use cases, types of data collected, modes of data collection, data analysis methods, and outcomes measured. Objective The primary aim of this scoping review was to map the published research on digital phenotyping and to outline study characteristics, data collection and analysis methods, machine learning approaches, and future implications. Methods We utilized an a priori approach for the literature search and data extraction and charting process, guided by the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-analyses Extension for Scoping Reviews). We identified relevant studies published in 2020, 2021, and 2022 on PubMed and Google Scholar using search terms related to digital phenotyping. The titles, abstracts, and keywords were screened during the first stage of the screening process, and the second stage involved screening the full texts of the shortlisted articles. We extracted and charted the descriptive characteristics of the final studies, which were countries of origin, study design, clinical areas, active and/or passive data collected, modes of data collection, data analysis approaches, and limitations. Results A total of 454 articles on PubMed and Google Scholar were identified through search terms associated with digital phenotyping, and 46 articles were deemed eligible for inclusion in this scoping review. Most studies evaluated wearable data and originated from North America. The most dominant study design was observational, followed by randomized trials, and most studies focused on psychiatric disorders, mental health disorders, and neurological diseases. A total of 7 studies used machine learning approaches for data analysis, with random forest, logistic regression, and support vector machines being the most common. Conclusions Our review provides foundational as well as application-oriented approaches toward digital phenotyping in health. Future work should focus on more prospective, longitudinal studies that include larger data sets from diverse populations, address privacy and ethical concerns around data collection from consumer technologies, and build “digital phenotypes” to personalize digital health interventions and treatment plans.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Digital Phenotyping in Health Using Machine Learning Approaches: Scoping Review

Dlima¹,

Shevade²,

Menezes³

et al. 2022

JMIR Bioinform Biotech

View full text Add to dashboard Cite

show abstract

“…Thus, sunburn may be expected in body areas not protected by clothing or the application of sunscreen. Defining sunburn in the recruitment materials was an important initial step in improving awareness and reporting of sunburn [ 10 ]. The reduction in facial sunburns during the study compared with those during the period preceding the intervention was attributed to improved sunscreen usage, reduced scalp sunburn to wearing a baseball cap, and reduced shoulder sunburn to wearing a T-shirt that covered the shoulders.…”

Section: Discussionmentioning

confidence: 99%

Real-Time UV Measurement With a Sun Protection System for Warning Young Adults About Sunburn: Prospective Cohort Study

Robinson¹,

Patel²,

Heo³

et al. 2021

JMIR Mhealth Uhealth

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Background Melanoma is attributable to predisposing phenotypical factors, such as skin that easily sunburns and unprotected exposure to carcinogenic UV radiation. Reducing the proportion of young adults who get sunburned may reduce the incidence of melanoma, a deadly form of skin cancer. Advances in technology have enabled the delivery of real-time UV light exposure and content-relevant health interventions. Objective This study aims to examine the feasibility of young adults performing the following tasks daily: wearing a UV dosimeter, receiving text messages and real-time UV-B doses on their smartphone, and responding to daily web-based surveys about sunburn and sun protection. Methods Young adults aged 18-39 years (n=42) were recruited in the United States in June 2020 via social media. Participants received the UV Guard sun protection system, which consisted of a UV dosimeter and a smartphone app. During 3 consecutive periods, intervention intensity increased as follows: real-time UV-B dose; UV-B dose and daily behavioral facilitation text messages; and UV-B dose, goal setting, and daily text messages to support self-efficacy and self-regulation. Data were self-reported through daily web-based surveys for 28 days, and UV-B doses were transmitted to cloud-based storage. Results Patients’ median age was 22 years (IQR 20, 29), and all patients had sun-sensitive skin. Sunburns were experienced during the study by fewer subjects (n=18) than those in the preceding 28 days (n=30). In July and August, the face was the most commonly sunburned area among 13 body locations; 52% (22/42) of sunburns occurred before the study and 45% (19/42) occurred during the study. The mean daily UV-B dose decreased during the 3 periods; however, this was not statistically significant. Young adults were most often exercising outdoors from 2 to 6 PM, walking from 10 AM to 6 PM, and relaxing from noon to 2 PM. Sunburn was most often experienced during exercise (odds ratio [OR] 5.65, 95% CI 1.60-6.10) and relaxation (OR 3.69, 95% CI 1.03-4.67) relative to those that did not exercise or relax in each category. The self-reported exit survey indicated that participants felt that they spent less time outdoors this summer compared to the last summer because of the COVID-19 pandemic and work. In addition, 38% (16/42) of the participants changed their use of sun protection based on their app-reported UV exposure, and 48% (20/42) shifted the time they went outside to periods with less-intense UV exposure. A total of 79% (33/42) of the participants were willing to continue using the UV Guard system outside of a research setting. Conclusions In this proof-of-concept research, young adults demonstrated that they used the UV Guard system; however, optimization was needed. Although some sun protection behaviors changed, sunburn was not prevented in all participants, especially during outdoor exercise. Trial Registration ClinicalTrials.gov NCT03344796; http://clinicaltrials.gov/ct2/show/NCT03344796

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“…While the devices can sensitively detect UV and convey some message of associated risk to the wearer, they have had contradictory results on improving sun safe behaviors. [27,28] Factors that could be reducing the efficacy of these devices are the desirability and everyday wearability of their designs. Poor aesthetics, limited customization, complexity, and incompatibility with personal identity are found to be under-addressed factors for disengagement with wearable technology.…”

Section: D-printed Wearable and Reusable Uv Sensorsmentioning

confidence: 99%

Diarylethene Photoswitches and 3D Printing to Fabricate Rewearable Colorimetric UV Sensors for Sun Protection

Wiedbrauk

McKinnon

Swann

et al. 2023

Adv Materials Technologies

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damage has been done. The association between a range of skin and eye diseases and exposure to UV light is well established. [1] Despite this knowledge leading to public health education campaigns, the improvement and increased use of broad spectrum sunscreens, sun-related skin cancers continue to be a major health concern. [2,3] Clearly, prevention is better than a cure, and so new innovations are needed to improve people's awareness of their risk when enjoying the sun.Solar UV radiation is typically classified into three classes: UV-A (315-400 nm), UV-B (280-315 nm), and UV-C (100-280 nm). UV-C radiation (and high energy UV-B <300 nm), while being the highest in energy, is of little concern in a sun protection setting on the Earth's surface, as radiation in this spectrum is effectively filtered by the ozone layer (Figure 1). Typically it is the UV-B range that is considered the highest risk for disease, as light in this spectral range can affect direct damage to DNA. [4,5] UV-A is typically regarded as capable of damaging connective tissue and blood vessels in deeper dermal layers and is therefore responsible for ageing, but there is a growing body of evidence for the causal link between UV-A radiation and cancer through indirect damage by reactive oxygen species (ROS). [1,4,5] As such, protection from light across the UV spectrum with broad spectrum sunscreens and UV protective clothing has become increasingly important.Although the link between sun exposure and cancer risk has been established, the role of human behavior in mitigating this risk is critical. [3] Broad spectrum sunscreen is capable of protecting from UV radiation, however, appropriate application is often lacking, and can lead to increased exposure time (and overall dose) in sun-seeking individuals. [7] Conversely, while the deleterious link between UV light and disease is well communicated in the community, there is also a need for UV-B light for the metabolism of the essential vitamin D 3 . [8] Vitamin D deficiency can lead to a range of medical conditions, and so a small, sub-damaging dose of UV exposure is necessary for a healthy life. It is clear there are significant challenges in measuring a person's exposure to UV light, providing an estimation of their level of risk, to enable educated decisions about their sun-seeking behavior.A wide range of laboratory prototypes and commercial wearable UV sensors have been developed that aim to improve sun protection. [9,10] They can be broadly divided into two classes, Despite education campaigns linking sun overexposure and skin cancer, it remains one of the leading preventable cancer diagnoses. Skin cancer risk is correlated with overexposure to UV light in sunlight and can be prevented by avoiding exposure. While sun protection can be achieved using sunscreen and clothing, people must be made aware of their risk to facilitate behavior change. Herein, new rewearable UV sensors which overcome the single-use limitations of other products are presented. These sensors utilize diarylethene photoswitch...

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Protection‐adjusted UV dose estimated for body areas: Daily self‐reported sun protection modification of wearable UV sensor dose

Cited by 9 publications

References 35 publications

Digital Phenotyping in Health Using Machine Learning Approaches: Scoping Review

Digital Phenotyping in Health Using Machine Learning Approaches: Scoping Review

Real-Time UV Measurement With a Sun Protection System for Warning Young Adults About Sunburn: Prospective Cohort Study

Diarylethene Photoswitches and 3D Printing to Fabricate Rewearable Colorimetric UV Sensors for Sun Protection

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