Assessing recall of personal sun exposure by integrating UV dosimeter and self-reported data with a network flow framework
Autoři:
Nabil Alshurafa aff001; Jayalakshmi Jain aff001; Tammy K. Stump aff001; Bonnie Spring aff001; June K. Robinson aff004
Působiště autorů:
Department of Preventive Medicine, Northwestern University, Chicago, Illinois, United States of America
aff001; Department of Computer Science, Northwestern University, Evanston, Illinois, United States of America
aff002; Department of Electrical and Computer Engineering, Northwestern University, Evanston, Illinois, United States of America
aff003; Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, Illinois, United States of America
aff004; Department of Dermatology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
aff005
Vyšlo v časopise:
PLoS ONE 14(12)
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pone.0225371
Souhrn
Background
Melanoma survivors often do not engage in adequate sun protection, leading to sunburn and increasing their risk of future melanomas. Melanoma survivors do not accurately recall the extent of sun exposure they have received, thus, they may be unaware of their personal UV exposure, and this lack of awareness may contribute towards failure to change behavior. As a means of determining behavioral accuracy of recall of sun exposure, this study compared subjective self-reports of time outdoors to an objective wearable sensor. Analysis of the meaningful discrepancies between the self-report and sensor measures of time outdoors was made possible by using a network flow algorithm to align sun exposure events recorded by both measures. Aligning the two measures provides the opportunity to more accurately evaluate false positive and false negative self-reports of behavior and understand participant tendencies to over- and under-report behavior.
Methods
39 melanoma survivors wore an ultraviolet light (UV) sensor on their chest while outdoors for 10 consecutive summer days and provided an end-of-day subjective self-report of their behavior while outdoors. A Network Flow Alignment framework was used to align self-report and objective UV sensor data to correct misalignment. The frequency and time of day of under- and over-reporting were identified.
Findings
For the 269 days assessed, the proposed framework showed a significant increase in the Jaccard coefficient (i.e. a measure of similarity between self-report and UV sensor data) by 63.64% (p < .001), and significant reduction in false negative minutes by 34.43% (p < .001). Following alignment of the measures, under-reporting of sun exposure time occurred on 51% of the days analyzed and more participants tended to under-report than to over-report sun exposure time. Rates of under-reporting of sun exposure were highest for events that began from 12-1pm, and second-highest from 5-6pm.
Conclusion
These discrepancies may reflect lack of accurate recall of sun exposure during times of peak sun intensity (10am–2pm) that could ultimately increase the risk of developing melanoma. This research provides technical contributions to the field of wearable computing, activity recognition, and identifies actionable times to improve participants’ perception of their sun exposure.
Klíčová slova:
Algorithms – Behavior – Ultraviolet radiation – Cell phones – Memory recall – Melanomas – Overexposure to sun – Cluster analysis
Zdroje
1. Titus-Ernstoff L, Perry AE, Spencer SK, Gibson J, Ding J, Cole B, et al. Multiple primary melanoma: two-year results from a population-based study. Arch Dermatol. 2006;142(4):433–438. doi: 10.1001/archderm.142.4.433 16618861
2. Kricker A, Armstrong BK, Goumas C, Litchfield M, Begg CB, Hummer AJ, et al. Ambient UV, personal sun exposure and risk of multiple primary melanomas. Cancer Causes Control. 2007;18(3):295–304. doi: 10.1007/s10552-006-0091-x 17206532
3. Green AC, Williams GM, Logan V, Strutton GM. Reduced melanoma after regular sunscreen use: randomized trial follow-up. J Clin Oncol. 2011;29(3):257–263. doi: 10.1200/JCO.2010.28.7078 21135266
4. Vogel RI, Strayer LG, Engelman L, Nelson HH, Blaes AH, Anderson KE, et al. Sun exposure and protection behaviors among long-term melanoma survivors and population controls. Cancer Epidemiology and Prevention Biomarkers. 2017;26(4):607–613. doi: 10.1158/1055-9965.EPI-16-0854
5. Italia N, Rehfuess EA. Is the Global Solar UV Index an effective instrument for promoting sun protection? A systematic review. Health education research. 2011;27(2):200–213. doi: 10.1093/her/cyr050 21730253
6. Idorn LW, Datta P, Heydenreich J, Philipsen PA, Wulf HC. A 3-year follow-up of sun behavior in patients with cutaneous malignant melanoma. JAMA Dermatol. 2014;150(2):163–168. doi: 10.1001/jamadermatol.2013.5098 24080851
7. Lee TK, Brazier AS, Shoveller JA, Gallagher RP. Sun-related behavior after a diagnosis of cutaneous malignant melanoma. Melanoma Res. 2007;17(1):51–55. doi: 10.1097/CMR.0b013e3280112b98 17235242
8. Freiman A, Yu J, Loutfi A, Wang B. Impact of melanoma diagnosis on sun-awareness and protection: efficacy of education campaigns in a high-risk population. J Cutan Med Surg. 2004;8(5):303–309. doi: 10.1007/s10227-005-0009-3 15868284
9. Carver CS, Scheier M. Principles of self-regulation: Action and emotion. Guilford Press; 1990.
10. Carver CS, Scheier MF. On the self-regulation of behavior. Cambridge University Press; 2001.
11. Higgins ET. Beyond pleasure and pain. American psychologist. 1997;52(12):1280. doi: 10.1037//0003-066x.52.12.1280 9414606
12. Locke EA, Latham GP. A theory of goal setting & task performance. Prentice-Hall, Inc; 1990.
13. Locke EA, Latham GP. Building a practically useful theory of goal setting and task motivation: A 35-year odyssey. American psychologist. 2002;57(9):705. doi: 10.1037//0003-066x.57.9.705 12237980
14. Bandura A. Self-efficacy: The exercise of control. Macmillan; 1997.
15. Shade UV sensor. Shade UV sensor—Funded by the National Cancer Institute; 2017. Available from: https://www.wearshade.com.
16. Stump TK, Aspinwall LG, Gray EL, Xu S, Maganti N, Leachmean SA, et al. Daily Minutes of Unprotected Sun Exposure (MUSE) Inventory: Measure description and comparisons to UVR sensor and sun protection survey data. Preventive medicine reports. 2018;11:305–311. doi: 10.1016/j.pmedr.2018.07.010 30116702
17. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. Journal of biomedical informatics. 2009;42(2):377–381. doi: 10.1016/j.jbi.2008.08.010 18929686
18. Banerjee S, Hoch EG, Kaplan PD, Dumont EL. A comparative study of wearable ultraviolet radiometers. In: Life Sciences Conference (LSC). IEEE; 2017. p. 9–12.
19. United States Environmental Protection Agency. UV Index | Sun Safety; 2017. Available from: https://www.epa.gov/sunsafety/uv-index-1.
20. Ford LR, Fulkerson DR. Maximal flow through a network. Canadian journal of Mathematics. 1956;8(3):399–404. doi: 10.4153/CJM-1956-045-5
21. Henriksen M, Na R, Aagren M, Wulf H. Minimal erythema dose after multiple UV exposures depends on pre-exposure skin pigmentation. Photodermatology, photoimmunology & photomedicine. 2004;20(4):163–169. doi: 10.1111/j.1600-0781.2004.00104.x
22. Glanz K, McCarty F, Nehl EJ, O’Riordan DL, Gies P, Bundy L, Locke AE, Hall DM. Validity of self-reported sunscreen use by parents, children and lifeguards. Am J Prev Med. 2009;36:63–69. doi: 10.1016/j.amepre.2008.09.012 18945582
23. Hillhouse J, Turrisi R, Jaccard J, Robinson J. Accuracy of self-reported sun exposure and sun protection behavior. Prevention Science. 2012;13(5):519–531. doi: 10.1007/s11121-012-0278-1 22855253
24. Thieden E, Philipsen PA, Wulf HC. Compliance and data reliability in sun exposure studies with diaries and personal, electronic UV dosimeters. Photodermatology, photoimmunology & photomedicine. 2006;22(2):93–99. doi: 10.1111/j.1600-0781.2006.00207.x
25. Alharbi R, Stump T, Vafaie N, Pfammatter A, Spring B, Alshurafa N. I Can’t Be Myself: Effects of Wearable Cameras on the Capture of Authentic Behavior in the Wild. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. 2018;2(3):90. doi: 10.1145/3264900
26. Ross GT, Soland RM. A branch and bound algorithm for the generalized assignment problem. Mathematical programming. 1975;8(1):91–103. doi: 10.1007/BF01580430
Článok vyšiel v časopise
PLOS One
2019 Číslo 12
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
- Masturbační chování žen v ČR − dotazníková studie
- Nejasný stín na plicích – kazuistika
- Těžké menstruační krvácení může značit poruchu krevní srážlivosti. Jaký management vyšetření a léčby je v takovém případě vhodný?
- Somatizace stresu – typické projevy a možnosti řešení
Najčítanejšie v tomto čísle
- Methylsulfonylmethane increases osteogenesis and regulates the mineralization of the matrix by transglutaminase 2 in SHED cells
- Oregano powder reduces Streptococcus and increases SCFA concentration in a mixed bacterial culture assay
- The characteristic of patulous eustachian tube patients diagnosed by the JOS diagnostic criteria
- Parametric CAD modeling for open source scientific hardware: Comparing OpenSCAD and FreeCAD Python scripts