Enhanced Melanoma Diagnosis With Multispectral Digital Skin Lesion Analysis

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Enhanced Melanoma Diagnosis With Multispectral Digital Skin Lesion Analysis

Early detection of melanoma, which is known to improve survival rates, remains a challenge for dermatologists. Suspicious pigmented lesions typically are evaluated via clinical examination and dermoscopy; however, new technologies are being developed to provide additional objective information for clinicians to incorporate into their biopsy decisions.

Multispectral digital skin lesion analysis (MSDSLA) uses 10 bands of visible and near-infrared light (430–950 nm) to image and analyze pigmented skin lesions (PSLs) down to 2.5 mm below the skin surface and measures the distribution of melanin using 75 unique algorithms to determine the degree of the morphologic disorder. Using a logical regression model previously validated on a set of 1632 PSLs, the probability of melanoma and probability of being a melanoma/PSL of high-risk malignant potential are then provided to the clinician.1

In this study, we analyzed aggregate data from 7 prior studies2-8 to better determine how MSDSLA impacts the biopsy decisions of dermatologists and nondermatologists following clinical examination and dermoscopic evaluation of PSLs.

Methods

A total of 855 practitioners (657 dermatologists, 126 dermatology residents, 72 nondermatologists [ie, primary care physicians, physician assistants, nurse practitioners]) in 7 prior reader studies (Table)2-8 were shown a total of 62 clinical (distant and close-up) and dermoscopic images of PSLs (13 invasive melanomas, 10 melanomas in situ, 7 high-grade dysplastic nevi, 32 benign skin lesions including low-grade dysplastic nevi) previously analyzed by MSDSLA.2-8 For each lesion evaluated, the practitioners were first asked if they would biopsy based on their review of the clinical and dermoscopic images and were asked again when given the associated MSDSLA information. Data were aggregated across all participants for the individual lesions presented in each reader study. Biopsy decisions were compared overall after evaluation of clinical and dermoscopic findings and then after evaluation of MSDSLA findings. Statistical analyses were performed using t-test and χ2 analysis for proportions where appropriate.

Results

Overall sensitivity for the detection of melanoma or other high-grade PSLs improved from 70% on clinical and dermoscopic evaluation to 88% after MSDSLA information was provided (P<.0001), and specificity increased from 52% to 58% (P<.001). Diagnostic accuracy also improved from 59% on clinical evaluation to 69% after review of MSDSLA findings (P<.0001). The positive predictive value of biopsy decisions was 47% following clinical evaluation, which improved to 56% after evaluation of MSDSLA findings (P<.001), and the negative predictive value increased from 74% to 89% (P<.0001). The overall percentage of lesions selected for biopsy did not significantly change following MSDSLA data integration (57% vs 60%)(Figure). Given that similar numbers of lesions were biopsied with improved sensitivity and specificity, the integration of MSDSLA data into the biopsy decision led to an improved biopsy ratio (ratio of melanomas biopsied to total biopsies) and fewer unnecessary biopsies.

Standard statistical metrics evaluating the impact of multispectral digital skin lesion analysis on pigmented lesion diagnosis. All 5 of the standard metrics for diagnostic tests improved following the provision of multispectral digital skin lesion analysis data to the health care providers (N=855). Asterisk indicates statiscally significant improvement (P< .05).

Comment

Our broad analysis further supported the findings of prior studies that decisions to biopsy clinically suspicious PSLs are more sensitive, specific, and accurate when practitioners are provided MSDSLA information following clinical examination.2-8With no significant increase in the number of biopsies performed, the fact that all 5 of the standard diagnostic evaluation metrics (sensitivity, specificity, diagnostic accuracy, positive predictive value, negative predictive value) were improved after MSDSLA information was provided additionally supported this conclusion.

Given the evolution in health care economics, it is clear that greater emphasis will continue to be placed on superior, evidence-based, effective care. The reported diagnostic sensitivities and specificities of clinical evaluation and dermoscopy for melanoma detection vary widely throughout the literature, with sensitivities ranging from 58% to over 90% and specificities ranging from 77% to 99%.9-11Diagnostic performance generally has been found to be higher among dermatologists than nondermatologists and is highest in specialized pigmented lesion clinics.12

Our study had several limitations. For this analysis to be more representative of lesion biopsy selection in the clinical setting, biopsy sensitivity (correctly identifying lesions appropriate for biopsy) vs melanoma sensitivity (identifying a lesion as melanoma) was used.13 The overall sensitivity found was within the range of prior studies,2-8 but this approach may have potentially led to a lower specificity due to an increased number of lesions biopsied. Additionally, the melanomas selected for these studies were early (malignant melanoma in situ or mean thickness of invasive malignant melanoma of 0.3 mm), and the nonmelanomas (including low-grade dysplastic nevi) were not necessarily diagnostically straightforward. This may have led to the clinical and dermoscopic sensitivity and specificity noted being lower than in some prior studies.9-11

The risk of missing a melanoma with MSDSLA devices has led manufacturers to strive for a high sensitivity for their devices, leading to lower specificity as a consequence. For this reason and other ambiguous practical considerations (eg, device and patient costs, difficulty with insurance reimbursement), the adoption of this technology into routine clinical practice has remained relatively static; however, using enhanced diagnostic technologies such as MSDSLA may help with more accurate identification of high-risk PSLs, thereby leading to earlier detection and overall less expensive, more cost-effective treatment of melanoma.

References
  1. Monheit G, Cognetta AB, Ferris L, et al. The performance of MelaFind: a prospective multicenter study. Arch Dermatol. 2011;147:188-194.
  2. Rigel DS, Roy M, Yoo J, et al. Impact of guidance from a computer-aided multispectral digital skin lesion analysis device on decision to biopsy lesions clinically suggestive of melanoma. Arch Dermatol. 2012;148:541-543.
  3. Yoo J, Rigel DS, Roy M, et al. Impact of guidance from a multispectral digital skin lesion analysis device on dermatology residents decisions to biopsy lesions clinically suggestive of melanoma. J Am Acad Dermatol. 2013;68:AB152.
  4. Winkelmann RR, Yoo J, Tucker N, et al. Impact of guidance provided by a multispectral digital skin lesion analysis device following dermoscopy on decisions to biopsy atypical melanocytic lesions. J Clin Aesthet Dermatol. 2015;8:21-24.
  5. Winkelmann RR, Hauschild A, Tucker N, et al. The impact of multispectral digital skin lesion analysis on German dermatologist decisions to biopsy atypical pigmented lesions with clinical characteristics of melanoma. J Clin Aesthet Dermatol. 2015;8:27-29.
  6. Winkelmann RR, Tucker N, White R, et al. Pigmented skin lesion biopsies after computer-aided multispectral digital skin lesion analysis. J Am Osteopath Assoc. 2015;115:666-669.
  7. Winkelmann RR, Farberg AS, Tucker N, et al. Enhancement of international dermatologists’ pigmented skin lesion biopsy decisions following dermoscopy with subsequent integration of multispectral digital skin lesion analysis [published online July 1, 2016]. J Clin Aesthet Dermatol. 2016;9:53-55.
  8. Farberg AS, Winkelmann RR, Tucker N, et al. The impact of quantitative data provided by a multi-spectral digital skin lesion analysis device on dermatologists’ decisions to biopsy pigmented lesions [published online September 1, 2017]. J Clin Aesthet Dermatol. 2017;10:24-26.
  9. Wolf IH, Smolle J, Soyer HP, et al. Sensitivity in the clinical diagnosis of malignant melanoma. Melanoma Res. 1998;8:425-429.
  10. Kittler H, Pehamberger H, Wolff K, et al. Diagnostic accuracy of dermoscopy. Lancet Oncol. 2002;3:159-165.
  11. Ascierto PA, Palmieri G, Celentano E, et al. Sensitivity and specificity of epiluminescence microscopy: evaluation on a sample of 2731 excised cutaneous pigmented lesions: the Melanoma Cooperative Study. Br J Dermatol. 2000;142:893-898.
  12. Carli P, Nardini P, Crocetti E, et al. Frequency and characteristics of melanomas missed at a pigmented lesion clinic: a registry-based study. Melanoma Res. 2004;14:403-407.
  13. Friedman RJ, Gutkowicz-Krusin D, Farber MJ, et al. The diagnostic performance of expert dermoscopists vs a computer-vision system on small-diameter melanomas. Arch Dermatol. 2008;144:476-482.
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Author and Disclosure Information

Dr. Farberg is from the Department of Dermatology, Icahn School of Medicine at Mount Sinai, New York, New York. Dr. Glazer is from the Division of Dermatology, University of Arizona, Tucson. Dr. Winkelmann is from the Department of Dermatology, OhioHealth, Athens. Ms. Tucker is from STRATA Skin Sciences, Horsham, Pennsylvania. Mr. White is from IRIS Interactive Horizon Inc, Cody, Wyoming. Dr. Rigel is from the Department of Dermatology, New York University School of Medicine, New York.

Drs. Glazer and White report no conflict of interest. Drs. Farberg and Winkelman received research funding from STRATA Skin Sciences. Ms. Tucker is an employee of STRATA Skin Sciences. Dr. Rigel was a consultant for STRATA Skin Sciences.

Correspondence: Darrell S. Rigel, MD, MS, 35 E 35th St, #208, New York, NY, 10016 (dsrigel@prodigy.net).

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Dr. Farberg is from the Department of Dermatology, Icahn School of Medicine at Mount Sinai, New York, New York. Dr. Glazer is from the Division of Dermatology, University of Arizona, Tucson. Dr. Winkelmann is from the Department of Dermatology, OhioHealth, Athens. Ms. Tucker is from STRATA Skin Sciences, Horsham, Pennsylvania. Mr. White is from IRIS Interactive Horizon Inc, Cody, Wyoming. Dr. Rigel is from the Department of Dermatology, New York University School of Medicine, New York.

Drs. Glazer and White report no conflict of interest. Drs. Farberg and Winkelman received research funding from STRATA Skin Sciences. Ms. Tucker is an employee of STRATA Skin Sciences. Dr. Rigel was a consultant for STRATA Skin Sciences.

Correspondence: Darrell S. Rigel, MD, MS, 35 E 35th St, #208, New York, NY, 10016 (dsrigel@prodigy.net).

Author and Disclosure Information

Dr. Farberg is from the Department of Dermatology, Icahn School of Medicine at Mount Sinai, New York, New York. Dr. Glazer is from the Division of Dermatology, University of Arizona, Tucson. Dr. Winkelmann is from the Department of Dermatology, OhioHealth, Athens. Ms. Tucker is from STRATA Skin Sciences, Horsham, Pennsylvania. Mr. White is from IRIS Interactive Horizon Inc, Cody, Wyoming. Dr. Rigel is from the Department of Dermatology, New York University School of Medicine, New York.

Drs. Glazer and White report no conflict of interest. Drs. Farberg and Winkelman received research funding from STRATA Skin Sciences. Ms. Tucker is an employee of STRATA Skin Sciences. Dr. Rigel was a consultant for STRATA Skin Sciences.

Correspondence: Darrell S. Rigel, MD, MS, 35 E 35th St, #208, New York, NY, 10016 (dsrigel@prodigy.net).

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Early detection of melanoma, which is known to improve survival rates, remains a challenge for dermatologists. Suspicious pigmented lesions typically are evaluated via clinical examination and dermoscopy; however, new technologies are being developed to provide additional objective information for clinicians to incorporate into their biopsy decisions.

Multispectral digital skin lesion analysis (MSDSLA) uses 10 bands of visible and near-infrared light (430–950 nm) to image and analyze pigmented skin lesions (PSLs) down to 2.5 mm below the skin surface and measures the distribution of melanin using 75 unique algorithms to determine the degree of the morphologic disorder. Using a logical regression model previously validated on a set of 1632 PSLs, the probability of melanoma and probability of being a melanoma/PSL of high-risk malignant potential are then provided to the clinician.1

In this study, we analyzed aggregate data from 7 prior studies2-8 to better determine how MSDSLA impacts the biopsy decisions of dermatologists and nondermatologists following clinical examination and dermoscopic evaluation of PSLs.

Methods

A total of 855 practitioners (657 dermatologists, 126 dermatology residents, 72 nondermatologists [ie, primary care physicians, physician assistants, nurse practitioners]) in 7 prior reader studies (Table)2-8 were shown a total of 62 clinical (distant and close-up) and dermoscopic images of PSLs (13 invasive melanomas, 10 melanomas in situ, 7 high-grade dysplastic nevi, 32 benign skin lesions including low-grade dysplastic nevi) previously analyzed by MSDSLA.2-8 For each lesion evaluated, the practitioners were first asked if they would biopsy based on their review of the clinical and dermoscopic images and were asked again when given the associated MSDSLA information. Data were aggregated across all participants for the individual lesions presented in each reader study. Biopsy decisions were compared overall after evaluation of clinical and dermoscopic findings and then after evaluation of MSDSLA findings. Statistical analyses were performed using t-test and χ2 analysis for proportions where appropriate.

Results

Overall sensitivity for the detection of melanoma or other high-grade PSLs improved from 70% on clinical and dermoscopic evaluation to 88% after MSDSLA information was provided (P<.0001), and specificity increased from 52% to 58% (P<.001). Diagnostic accuracy also improved from 59% on clinical evaluation to 69% after review of MSDSLA findings (P<.0001). The positive predictive value of biopsy decisions was 47% following clinical evaluation, which improved to 56% after evaluation of MSDSLA findings (P<.001), and the negative predictive value increased from 74% to 89% (P<.0001). The overall percentage of lesions selected for biopsy did not significantly change following MSDSLA data integration (57% vs 60%)(Figure). Given that similar numbers of lesions were biopsied with improved sensitivity and specificity, the integration of MSDSLA data into the biopsy decision led to an improved biopsy ratio (ratio of melanomas biopsied to total biopsies) and fewer unnecessary biopsies.

Standard statistical metrics evaluating the impact of multispectral digital skin lesion analysis on pigmented lesion diagnosis. All 5 of the standard metrics for diagnostic tests improved following the provision of multispectral digital skin lesion analysis data to the health care providers (N=855). Asterisk indicates statiscally significant improvement (P< .05).

Comment

Our broad analysis further supported the findings of prior studies that decisions to biopsy clinically suspicious PSLs are more sensitive, specific, and accurate when practitioners are provided MSDSLA information following clinical examination.2-8With no significant increase in the number of biopsies performed, the fact that all 5 of the standard diagnostic evaluation metrics (sensitivity, specificity, diagnostic accuracy, positive predictive value, negative predictive value) were improved after MSDSLA information was provided additionally supported this conclusion.

Given the evolution in health care economics, it is clear that greater emphasis will continue to be placed on superior, evidence-based, effective care. The reported diagnostic sensitivities and specificities of clinical evaluation and dermoscopy for melanoma detection vary widely throughout the literature, with sensitivities ranging from 58% to over 90% and specificities ranging from 77% to 99%.9-11Diagnostic performance generally has been found to be higher among dermatologists than nondermatologists and is highest in specialized pigmented lesion clinics.12

Our study had several limitations. For this analysis to be more representative of lesion biopsy selection in the clinical setting, biopsy sensitivity (correctly identifying lesions appropriate for biopsy) vs melanoma sensitivity (identifying a lesion as melanoma) was used.13 The overall sensitivity found was within the range of prior studies,2-8 but this approach may have potentially led to a lower specificity due to an increased number of lesions biopsied. Additionally, the melanomas selected for these studies were early (malignant melanoma in situ or mean thickness of invasive malignant melanoma of 0.3 mm), and the nonmelanomas (including low-grade dysplastic nevi) were not necessarily diagnostically straightforward. This may have led to the clinical and dermoscopic sensitivity and specificity noted being lower than in some prior studies.9-11

The risk of missing a melanoma with MSDSLA devices has led manufacturers to strive for a high sensitivity for their devices, leading to lower specificity as a consequence. For this reason and other ambiguous practical considerations (eg, device and patient costs, difficulty with insurance reimbursement), the adoption of this technology into routine clinical practice has remained relatively static; however, using enhanced diagnostic technologies such as MSDSLA may help with more accurate identification of high-risk PSLs, thereby leading to earlier detection and overall less expensive, more cost-effective treatment of melanoma.

Early detection of melanoma, which is known to improve survival rates, remains a challenge for dermatologists. Suspicious pigmented lesions typically are evaluated via clinical examination and dermoscopy; however, new technologies are being developed to provide additional objective information for clinicians to incorporate into their biopsy decisions.

Multispectral digital skin lesion analysis (MSDSLA) uses 10 bands of visible and near-infrared light (430–950 nm) to image and analyze pigmented skin lesions (PSLs) down to 2.5 mm below the skin surface and measures the distribution of melanin using 75 unique algorithms to determine the degree of the morphologic disorder. Using a logical regression model previously validated on a set of 1632 PSLs, the probability of melanoma and probability of being a melanoma/PSL of high-risk malignant potential are then provided to the clinician.1

In this study, we analyzed aggregate data from 7 prior studies2-8 to better determine how MSDSLA impacts the biopsy decisions of dermatologists and nondermatologists following clinical examination and dermoscopic evaluation of PSLs.

Methods

A total of 855 practitioners (657 dermatologists, 126 dermatology residents, 72 nondermatologists [ie, primary care physicians, physician assistants, nurse practitioners]) in 7 prior reader studies (Table)2-8 were shown a total of 62 clinical (distant and close-up) and dermoscopic images of PSLs (13 invasive melanomas, 10 melanomas in situ, 7 high-grade dysplastic nevi, 32 benign skin lesions including low-grade dysplastic nevi) previously analyzed by MSDSLA.2-8 For each lesion evaluated, the practitioners were first asked if they would biopsy based on their review of the clinical and dermoscopic images and were asked again when given the associated MSDSLA information. Data were aggregated across all participants for the individual lesions presented in each reader study. Biopsy decisions were compared overall after evaluation of clinical and dermoscopic findings and then after evaluation of MSDSLA findings. Statistical analyses were performed using t-test and χ2 analysis for proportions where appropriate.

Results

Overall sensitivity for the detection of melanoma or other high-grade PSLs improved from 70% on clinical and dermoscopic evaluation to 88% after MSDSLA information was provided (P<.0001), and specificity increased from 52% to 58% (P<.001). Diagnostic accuracy also improved from 59% on clinical evaluation to 69% after review of MSDSLA findings (P<.0001). The positive predictive value of biopsy decisions was 47% following clinical evaluation, which improved to 56% after evaluation of MSDSLA findings (P<.001), and the negative predictive value increased from 74% to 89% (P<.0001). The overall percentage of lesions selected for biopsy did not significantly change following MSDSLA data integration (57% vs 60%)(Figure). Given that similar numbers of lesions were biopsied with improved sensitivity and specificity, the integration of MSDSLA data into the biopsy decision led to an improved biopsy ratio (ratio of melanomas biopsied to total biopsies) and fewer unnecessary biopsies.

Standard statistical metrics evaluating the impact of multispectral digital skin lesion analysis on pigmented lesion diagnosis. All 5 of the standard metrics for diagnostic tests improved following the provision of multispectral digital skin lesion analysis data to the health care providers (N=855). Asterisk indicates statiscally significant improvement (P< .05).

Comment

Our broad analysis further supported the findings of prior studies that decisions to biopsy clinically suspicious PSLs are more sensitive, specific, and accurate when practitioners are provided MSDSLA information following clinical examination.2-8With no significant increase in the number of biopsies performed, the fact that all 5 of the standard diagnostic evaluation metrics (sensitivity, specificity, diagnostic accuracy, positive predictive value, negative predictive value) were improved after MSDSLA information was provided additionally supported this conclusion.

Given the evolution in health care economics, it is clear that greater emphasis will continue to be placed on superior, evidence-based, effective care. The reported diagnostic sensitivities and specificities of clinical evaluation and dermoscopy for melanoma detection vary widely throughout the literature, with sensitivities ranging from 58% to over 90% and specificities ranging from 77% to 99%.9-11Diagnostic performance generally has been found to be higher among dermatologists than nondermatologists and is highest in specialized pigmented lesion clinics.12

Our study had several limitations. For this analysis to be more representative of lesion biopsy selection in the clinical setting, biopsy sensitivity (correctly identifying lesions appropriate for biopsy) vs melanoma sensitivity (identifying a lesion as melanoma) was used.13 The overall sensitivity found was within the range of prior studies,2-8 but this approach may have potentially led to a lower specificity due to an increased number of lesions biopsied. Additionally, the melanomas selected for these studies were early (malignant melanoma in situ or mean thickness of invasive malignant melanoma of 0.3 mm), and the nonmelanomas (including low-grade dysplastic nevi) were not necessarily diagnostically straightforward. This may have led to the clinical and dermoscopic sensitivity and specificity noted being lower than in some prior studies.9-11

The risk of missing a melanoma with MSDSLA devices has led manufacturers to strive for a high sensitivity for their devices, leading to lower specificity as a consequence. For this reason and other ambiguous practical considerations (eg, device and patient costs, difficulty with insurance reimbursement), the adoption of this technology into routine clinical practice has remained relatively static; however, using enhanced diagnostic technologies such as MSDSLA may help with more accurate identification of high-risk PSLs, thereby leading to earlier detection and overall less expensive, more cost-effective treatment of melanoma.

References
  1. Monheit G, Cognetta AB, Ferris L, et al. The performance of MelaFind: a prospective multicenter study. Arch Dermatol. 2011;147:188-194.
  2. Rigel DS, Roy M, Yoo J, et al. Impact of guidance from a computer-aided multispectral digital skin lesion analysis device on decision to biopsy lesions clinically suggestive of melanoma. Arch Dermatol. 2012;148:541-543.
  3. Yoo J, Rigel DS, Roy M, et al. Impact of guidance from a multispectral digital skin lesion analysis device on dermatology residents decisions to biopsy lesions clinically suggestive of melanoma. J Am Acad Dermatol. 2013;68:AB152.
  4. Winkelmann RR, Yoo J, Tucker N, et al. Impact of guidance provided by a multispectral digital skin lesion analysis device following dermoscopy on decisions to biopsy atypical melanocytic lesions. J Clin Aesthet Dermatol. 2015;8:21-24.
  5. Winkelmann RR, Hauschild A, Tucker N, et al. The impact of multispectral digital skin lesion analysis on German dermatologist decisions to biopsy atypical pigmented lesions with clinical characteristics of melanoma. J Clin Aesthet Dermatol. 2015;8:27-29.
  6. Winkelmann RR, Tucker N, White R, et al. Pigmented skin lesion biopsies after computer-aided multispectral digital skin lesion analysis. J Am Osteopath Assoc. 2015;115:666-669.
  7. Winkelmann RR, Farberg AS, Tucker N, et al. Enhancement of international dermatologists’ pigmented skin lesion biopsy decisions following dermoscopy with subsequent integration of multispectral digital skin lesion analysis [published online July 1, 2016]. J Clin Aesthet Dermatol. 2016;9:53-55.
  8. Farberg AS, Winkelmann RR, Tucker N, et al. The impact of quantitative data provided by a multi-spectral digital skin lesion analysis device on dermatologists’ decisions to biopsy pigmented lesions [published online September 1, 2017]. J Clin Aesthet Dermatol. 2017;10:24-26.
  9. Wolf IH, Smolle J, Soyer HP, et al. Sensitivity in the clinical diagnosis of malignant melanoma. Melanoma Res. 1998;8:425-429.
  10. Kittler H, Pehamberger H, Wolff K, et al. Diagnostic accuracy of dermoscopy. Lancet Oncol. 2002;3:159-165.
  11. Ascierto PA, Palmieri G, Celentano E, et al. Sensitivity and specificity of epiluminescence microscopy: evaluation on a sample of 2731 excised cutaneous pigmented lesions: the Melanoma Cooperative Study. Br J Dermatol. 2000;142:893-898.
  12. Carli P, Nardini P, Crocetti E, et al. Frequency and characteristics of melanomas missed at a pigmented lesion clinic: a registry-based study. Melanoma Res. 2004;14:403-407.
  13. Friedman RJ, Gutkowicz-Krusin D, Farber MJ, et al. The diagnostic performance of expert dermoscopists vs a computer-vision system on small-diameter melanomas. Arch Dermatol. 2008;144:476-482.
References
  1. Monheit G, Cognetta AB, Ferris L, et al. The performance of MelaFind: a prospective multicenter study. Arch Dermatol. 2011;147:188-194.
  2. Rigel DS, Roy M, Yoo J, et al. Impact of guidance from a computer-aided multispectral digital skin lesion analysis device on decision to biopsy lesions clinically suggestive of melanoma. Arch Dermatol. 2012;148:541-543.
  3. Yoo J, Rigel DS, Roy M, et al. Impact of guidance from a multispectral digital skin lesion analysis device on dermatology residents decisions to biopsy lesions clinically suggestive of melanoma. J Am Acad Dermatol. 2013;68:AB152.
  4. Winkelmann RR, Yoo J, Tucker N, et al. Impact of guidance provided by a multispectral digital skin lesion analysis device following dermoscopy on decisions to biopsy atypical melanocytic lesions. J Clin Aesthet Dermatol. 2015;8:21-24.
  5. Winkelmann RR, Hauschild A, Tucker N, et al. The impact of multispectral digital skin lesion analysis on German dermatologist decisions to biopsy atypical pigmented lesions with clinical characteristics of melanoma. J Clin Aesthet Dermatol. 2015;8:27-29.
  6. Winkelmann RR, Tucker N, White R, et al. Pigmented skin lesion biopsies after computer-aided multispectral digital skin lesion analysis. J Am Osteopath Assoc. 2015;115:666-669.
  7. Winkelmann RR, Farberg AS, Tucker N, et al. Enhancement of international dermatologists’ pigmented skin lesion biopsy decisions following dermoscopy with subsequent integration of multispectral digital skin lesion analysis [published online July 1, 2016]. J Clin Aesthet Dermatol. 2016;9:53-55.
  8. Farberg AS, Winkelmann RR, Tucker N, et al. The impact of quantitative data provided by a multi-spectral digital skin lesion analysis device on dermatologists’ decisions to biopsy pigmented lesions [published online September 1, 2017]. J Clin Aesthet Dermatol. 2017;10:24-26.
  9. Wolf IH, Smolle J, Soyer HP, et al. Sensitivity in the clinical diagnosis of malignant melanoma. Melanoma Res. 1998;8:425-429.
  10. Kittler H, Pehamberger H, Wolff K, et al. Diagnostic accuracy of dermoscopy. Lancet Oncol. 2002;3:159-165.
  11. Ascierto PA, Palmieri G, Celentano E, et al. Sensitivity and specificity of epiluminescence microscopy: evaluation on a sample of 2731 excised cutaneous pigmented lesions: the Melanoma Cooperative Study. Br J Dermatol. 2000;142:893-898.
  12. Carli P, Nardini P, Crocetti E, et al. Frequency and characteristics of melanomas missed at a pigmented lesion clinic: a registry-based study. Melanoma Res. 2004;14:403-407.
  13. Friedman RJ, Gutkowicz-Krusin D, Farber MJ, et al. The diagnostic performance of expert dermoscopists vs a computer-vision system on small-diameter melanomas. Arch Dermatol. 2008;144:476-482.
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  • Multispectral digital skin lesion analysis (MSDSLA) can be a valuable tool in the evaluation of pigmented skin lesions (PSLs).
  • MSDSLA may help to better identify high-risk PSLs and improve cost of care.
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Hat-Wearing Patterns in Spectators Attending Baseball Games: A 10-Year Retrospective Comparison

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Hat-Wearing Patterns in Spectators Attending Baseball Games: A 10-Year Retrospective Comparison

Spectators at baseball games may be exposed to excess solar UV radiation (UVR), which has been linked to the development of both melanoma and nonmelanoma skin cancers.1,2 Although baseball hats traditionally are worn to demonstrate team support, they also may provide some sun protection for the head and face where skin cancers are commonly found.

The importance of protecting the skin from solar UVR has led to sun-protection programs and community education as well as efforts to evaluate the impact of these programs. Major League Baseball (MLB) has partnered with the American Academy of Dermatology since 1999 to promote the importance of sun protection and raise skin cancer awareness through its Play Sun Smart program.3 A study conducted 10 years ago (N=2030) evaluated hat use in spectators at MLB games and noted that less than half of all spectators in seating sections exposed to direct sunlight wore hats.4 The purpose of the current study was to evaluate how public education about sun protection has impacted the use of hats by spectators at MLB games in 2015 compared to the prior study in 2006.

Methods

Data were collected during a 3-game series (2 day games, 1 night game) in August 2015 in New York, New York. During one of the day games, 18,000 fans received a free wide-brimmed hat. High-resolution digital photographs of seating sections were obtained using a camera with a 300-mm lens. Using the same methodology as the prior study,4 sunny and shaded seating sections were photographed during all 3 games (Figure). Photographs of each section were analyzed by an independent reviewer using a high-resolution computer screen. Spectators wearing head coverings—baseball hats, visors, or hats with circumferential brims—were defined as using hats. The number of spectators wearing hats versus not wearing hats was recorded for all identical sections of interest. Bleacher seating was analyzed separately, as spectators presumably knew in advance of the continuous direct sun exposure during day games, and a subset of young children in the bleachers (<10 years of age) also was assessed. A continuously sunny section also was evaluated at the second and sixth innings to see if hats were presumably purchased during exposure. Statistical significance was determined using χ2 tests with P<.05 indicating statistical significance.

Representative photographs of spectators at a daytime baseball game sitting in adjacent sunny and shaded sections (A) and spectators sitting in the bleachers during a day game with a free hat giveaway (B).

Results

This analysis consisted of 3539 spectators. In both the sunny and shaded sections of a day game, there were more spectators wearing hats (49% and 37%, respectively)(P<.001) than in the same sections at night games (35% and 29%, respectively)(Table 1). During the day game, more spectators wore hats in the sunny section than in the adjacent shaded section (49% vs 37%; P<.001). Analysis of the same 2 sections during the night game revealed no significant differences.

Spectators sitting in the bleachers during a day game who presumably knew to anticipate direct sun exposure showed no significant differences in hat-wearing patterns versus the sunny section (44% vs 49%) but were more likely to wear hats compared to those sitting in the bleachers at the night game (44% vs 33%)(P<.001)(Table 1). There was no significant difference in the number of hats worn by spectators in the sunny section in the second inning (43%) versus the same section after continuous sun exposure at the sixth inning (44%)(Table 2). Significantly more children seated in the bleachers during the day game wore hats compared to adults in the same section (64% vs 42%; P<.001)(Table 3). During the hat giveaway day, significantly more spectators wore hats (the majority of which were the free giveaway hats) across all sections studied (P<.001)(Table 4).

 

 

Comment

More than 23 million spectators attended daytime MLB games in 2015, with millions more attending minor league and amateur events.5Although sun-protection messages tend to be well understood and received by society, many choose to ignore them.6

In partnership with the American Academy of Dermatology, the MLB’s Play Sun Smart program has promoted UVR risk awareness at sporting events since 1999.3 Those affiliated with MLB teams also receive annual skin cancer screenings in conjunction with a public education effort in May of each season. However, despite the years of sun-protection education, our study found that less than half of attendees wore hats for UVR protection. In fact, there were no significant differences noted across all of the hat-wearing parameters studied (day vs night game, sunny vs shaded section, sunny section over course of game) between the current study compared to the results from 10 years prior4 (Tables 1 and 2). For spectators in the bleacher section, even presumably knowing in advance that seating would be in the sun did not significantly increase hat-wearing behavior. Although skin cancer rates continue to rise, hat-wearing trends remain stable, revealing a concerning trend.

Increased availability of sunscreen has led to improved sun-protective behaviors in many populations.7 In our study, the free hat giveaway had the greatest impact on hat wearing, which suggests that improved availability and access to hats can lead to an important opportunity for sun-protection programs to partner with hat manufacturers to augment their use and protective impact.

Sun avoidance during childhood and adolescence has been shown to decrease the risk for melanoma.1 Young children had the highest rate of hat usage in the current study, possibly due to parental example or dictates. Research has shown the importance of role models in promoting sun safety to young children,8,9 so perhaps use of hats by parents or MLB players contributed to the hat-wearing behavior observed in this subpopulation.

Given the limited change observed in hat-wearing behaviors over the last decade, a knowledge and behavioral gap appears to exist that may be able to be exploited to enhance future sun protection. Also, based on our findings, the MLB and other sun-protection education campaigns may wish to augment their UVR protective messages by offering hat giveaways, which appear to have a notable impact.

Acknowledgment

The authors thank Jessie Skapik, BS (New York, New York), for her independent review of the spectator photographs.

References

References

1. Rigel DS. Cutaneous ultraviolet exposure and its relationship to the development of skin cancer. J Am Acad Dermatol. 2008;58(5, suppl 2):S129-S132.

2. Lim HW, James WD, Rigel DS, et al. Adverse effects of ultraviolet radiation from the use of indoor tanning equipment: time to ban the tan. J Am Acad Dermatol. 2011;64:893-902.

3. Play Sun Smart. American Academy of Dermatology website. https://www.aad.org/public/spot-skin-cancer/programs/play-sun-smart. Accessed August 25, 2016.

4. Rigel AS, Lebwohl MG. Hat-wearing patterns in persons attending baseball games. J Am Acad Dermatol. 2006;54:918-919.

5. MLB attendance report - 2016. ESPN website. www.espn.go.com/mlb/attendance. Accessed May 20, 2016.

6. Turner D, Harrison SL, Buettner P, et al. Does being a “SunSmart School” influence hat-wearing compliance? an ecological study of hat-wearing rates at Australian primary schools in a region of high sun exposure [published online December 29, 2013]. Prev Med. 2014;60:107-114.

7. Dubas LE, Adams BB. Sunscreen use and availability among female collegiate athletes [published online February 3, 2012]. J Am Acad Dermatol. 2012;67:876.e1-876.e6.

8. O’Riodran DL, Geller AC, Brooks DR, et al. Sunburn reduction through parental role modeling and sunscreen vigilance. J Pediatr. 2003;142:67-72.

9. Turrisi R, Hillhouse J, Heavin S, et al. Examination of the short-term efficacy of a parent-based intervention to prevent skin cancer. J Behav Med. 2004;27:393-412.

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Author and Disclosure Information

Dr. Farberg is from the Department of Dermatology, Icahn School of Medicine at Mount Sinai, New York, New York. Mr. Donohue is from the New York Yankees, New York. Dr. Rigel is from the Ronald O. Perelman Department of Dermatology, New York University School of Medicine, New York.

The authors report no conflict of interest.

Correspondence: Darrell S. Rigel, MD, MS, Ronald O. Perelman Department of Dermatology, New York University School of Medicine, 35 E 35th St, Ste 208, New York, NY 10016 (dsrigel@prodigy.net).

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Author and Disclosure Information

Dr. Farberg is from the Department of Dermatology, Icahn School of Medicine at Mount Sinai, New York, New York. Mr. Donohue is from the New York Yankees, New York. Dr. Rigel is from the Ronald O. Perelman Department of Dermatology, New York University School of Medicine, New York.

The authors report no conflict of interest.

Correspondence: Darrell S. Rigel, MD, MS, Ronald O. Perelman Department of Dermatology, New York University School of Medicine, 35 E 35th St, Ste 208, New York, NY 10016 (dsrigel@prodigy.net).

Author and Disclosure Information

Dr. Farberg is from the Department of Dermatology, Icahn School of Medicine at Mount Sinai, New York, New York. Mr. Donohue is from the New York Yankees, New York. Dr. Rigel is from the Ronald O. Perelman Department of Dermatology, New York University School of Medicine, New York.

The authors report no conflict of interest.

Correspondence: Darrell S. Rigel, MD, MS, Ronald O. Perelman Department of Dermatology, New York University School of Medicine, 35 E 35th St, Ste 208, New York, NY 10016 (dsrigel@prodigy.net).

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Spectators at baseball games may be exposed to excess solar UV radiation (UVR), which has been linked to the development of both melanoma and nonmelanoma skin cancers.1,2 Although baseball hats traditionally are worn to demonstrate team support, they also may provide some sun protection for the head and face where skin cancers are commonly found.

The importance of protecting the skin from solar UVR has led to sun-protection programs and community education as well as efforts to evaluate the impact of these programs. Major League Baseball (MLB) has partnered with the American Academy of Dermatology since 1999 to promote the importance of sun protection and raise skin cancer awareness through its Play Sun Smart program.3 A study conducted 10 years ago (N=2030) evaluated hat use in spectators at MLB games and noted that less than half of all spectators in seating sections exposed to direct sunlight wore hats.4 The purpose of the current study was to evaluate how public education about sun protection has impacted the use of hats by spectators at MLB games in 2015 compared to the prior study in 2006.

Methods

Data were collected during a 3-game series (2 day games, 1 night game) in August 2015 in New York, New York. During one of the day games, 18,000 fans received a free wide-brimmed hat. High-resolution digital photographs of seating sections were obtained using a camera with a 300-mm lens. Using the same methodology as the prior study,4 sunny and shaded seating sections were photographed during all 3 games (Figure). Photographs of each section were analyzed by an independent reviewer using a high-resolution computer screen. Spectators wearing head coverings—baseball hats, visors, or hats with circumferential brims—were defined as using hats. The number of spectators wearing hats versus not wearing hats was recorded for all identical sections of interest. Bleacher seating was analyzed separately, as spectators presumably knew in advance of the continuous direct sun exposure during day games, and a subset of young children in the bleachers (<10 years of age) also was assessed. A continuously sunny section also was evaluated at the second and sixth innings to see if hats were presumably purchased during exposure. Statistical significance was determined using χ2 tests with P<.05 indicating statistical significance.

Representative photographs of spectators at a daytime baseball game sitting in adjacent sunny and shaded sections (A) and spectators sitting in the bleachers during a day game with a free hat giveaway (B).

Results

This analysis consisted of 3539 spectators. In both the sunny and shaded sections of a day game, there were more spectators wearing hats (49% and 37%, respectively)(P<.001) than in the same sections at night games (35% and 29%, respectively)(Table 1). During the day game, more spectators wore hats in the sunny section than in the adjacent shaded section (49% vs 37%; P<.001). Analysis of the same 2 sections during the night game revealed no significant differences.

Spectators sitting in the bleachers during a day game who presumably knew to anticipate direct sun exposure showed no significant differences in hat-wearing patterns versus the sunny section (44% vs 49%) but were more likely to wear hats compared to those sitting in the bleachers at the night game (44% vs 33%)(P<.001)(Table 1). There was no significant difference in the number of hats worn by spectators in the sunny section in the second inning (43%) versus the same section after continuous sun exposure at the sixth inning (44%)(Table 2). Significantly more children seated in the bleachers during the day game wore hats compared to adults in the same section (64% vs 42%; P<.001)(Table 3). During the hat giveaway day, significantly more spectators wore hats (the majority of which were the free giveaway hats) across all sections studied (P<.001)(Table 4).

 

 

Comment

More than 23 million spectators attended daytime MLB games in 2015, with millions more attending minor league and amateur events.5Although sun-protection messages tend to be well understood and received by society, many choose to ignore them.6

In partnership with the American Academy of Dermatology, the MLB’s Play Sun Smart program has promoted UVR risk awareness at sporting events since 1999.3 Those affiliated with MLB teams also receive annual skin cancer screenings in conjunction with a public education effort in May of each season. However, despite the years of sun-protection education, our study found that less than half of attendees wore hats for UVR protection. In fact, there were no significant differences noted across all of the hat-wearing parameters studied (day vs night game, sunny vs shaded section, sunny section over course of game) between the current study compared to the results from 10 years prior4 (Tables 1 and 2). For spectators in the bleacher section, even presumably knowing in advance that seating would be in the sun did not significantly increase hat-wearing behavior. Although skin cancer rates continue to rise, hat-wearing trends remain stable, revealing a concerning trend.

Increased availability of sunscreen has led to improved sun-protective behaviors in many populations.7 In our study, the free hat giveaway had the greatest impact on hat wearing, which suggests that improved availability and access to hats can lead to an important opportunity for sun-protection programs to partner with hat manufacturers to augment their use and protective impact.

Sun avoidance during childhood and adolescence has been shown to decrease the risk for melanoma.1 Young children had the highest rate of hat usage in the current study, possibly due to parental example or dictates. Research has shown the importance of role models in promoting sun safety to young children,8,9 so perhaps use of hats by parents or MLB players contributed to the hat-wearing behavior observed in this subpopulation.

Given the limited change observed in hat-wearing behaviors over the last decade, a knowledge and behavioral gap appears to exist that may be able to be exploited to enhance future sun protection. Also, based on our findings, the MLB and other sun-protection education campaigns may wish to augment their UVR protective messages by offering hat giveaways, which appear to have a notable impact.

Acknowledgment

The authors thank Jessie Skapik, BS (New York, New York), for her independent review of the spectator photographs.

Spectators at baseball games may be exposed to excess solar UV radiation (UVR), which has been linked to the development of both melanoma and nonmelanoma skin cancers.1,2 Although baseball hats traditionally are worn to demonstrate team support, they also may provide some sun protection for the head and face where skin cancers are commonly found.

The importance of protecting the skin from solar UVR has led to sun-protection programs and community education as well as efforts to evaluate the impact of these programs. Major League Baseball (MLB) has partnered with the American Academy of Dermatology since 1999 to promote the importance of sun protection and raise skin cancer awareness through its Play Sun Smart program.3 A study conducted 10 years ago (N=2030) evaluated hat use in spectators at MLB games and noted that less than half of all spectators in seating sections exposed to direct sunlight wore hats.4 The purpose of the current study was to evaluate how public education about sun protection has impacted the use of hats by spectators at MLB games in 2015 compared to the prior study in 2006.

Methods

Data were collected during a 3-game series (2 day games, 1 night game) in August 2015 in New York, New York. During one of the day games, 18,000 fans received a free wide-brimmed hat. High-resolution digital photographs of seating sections were obtained using a camera with a 300-mm lens. Using the same methodology as the prior study,4 sunny and shaded seating sections were photographed during all 3 games (Figure). Photographs of each section were analyzed by an independent reviewer using a high-resolution computer screen. Spectators wearing head coverings—baseball hats, visors, or hats with circumferential brims—were defined as using hats. The number of spectators wearing hats versus not wearing hats was recorded for all identical sections of interest. Bleacher seating was analyzed separately, as spectators presumably knew in advance of the continuous direct sun exposure during day games, and a subset of young children in the bleachers (<10 years of age) also was assessed. A continuously sunny section also was evaluated at the second and sixth innings to see if hats were presumably purchased during exposure. Statistical significance was determined using χ2 tests with P<.05 indicating statistical significance.

Representative photographs of spectators at a daytime baseball game sitting in adjacent sunny and shaded sections (A) and spectators sitting in the bleachers during a day game with a free hat giveaway (B).

Results

This analysis consisted of 3539 spectators. In both the sunny and shaded sections of a day game, there were more spectators wearing hats (49% and 37%, respectively)(P<.001) than in the same sections at night games (35% and 29%, respectively)(Table 1). During the day game, more spectators wore hats in the sunny section than in the adjacent shaded section (49% vs 37%; P<.001). Analysis of the same 2 sections during the night game revealed no significant differences.

Spectators sitting in the bleachers during a day game who presumably knew to anticipate direct sun exposure showed no significant differences in hat-wearing patterns versus the sunny section (44% vs 49%) but were more likely to wear hats compared to those sitting in the bleachers at the night game (44% vs 33%)(P<.001)(Table 1). There was no significant difference in the number of hats worn by spectators in the sunny section in the second inning (43%) versus the same section after continuous sun exposure at the sixth inning (44%)(Table 2). Significantly more children seated in the bleachers during the day game wore hats compared to adults in the same section (64% vs 42%; P<.001)(Table 3). During the hat giveaway day, significantly more spectators wore hats (the majority of which were the free giveaway hats) across all sections studied (P<.001)(Table 4).

 

 

Comment

More than 23 million spectators attended daytime MLB games in 2015, with millions more attending minor league and amateur events.5Although sun-protection messages tend to be well understood and received by society, many choose to ignore them.6

In partnership with the American Academy of Dermatology, the MLB’s Play Sun Smart program has promoted UVR risk awareness at sporting events since 1999.3 Those affiliated with MLB teams also receive annual skin cancer screenings in conjunction with a public education effort in May of each season. However, despite the years of sun-protection education, our study found that less than half of attendees wore hats for UVR protection. In fact, there were no significant differences noted across all of the hat-wearing parameters studied (day vs night game, sunny vs shaded section, sunny section over course of game) between the current study compared to the results from 10 years prior4 (Tables 1 and 2). For spectators in the bleacher section, even presumably knowing in advance that seating would be in the sun did not significantly increase hat-wearing behavior. Although skin cancer rates continue to rise, hat-wearing trends remain stable, revealing a concerning trend.

Increased availability of sunscreen has led to improved sun-protective behaviors in many populations.7 In our study, the free hat giveaway had the greatest impact on hat wearing, which suggests that improved availability and access to hats can lead to an important opportunity for sun-protection programs to partner with hat manufacturers to augment their use and protective impact.

Sun avoidance during childhood and adolescence has been shown to decrease the risk for melanoma.1 Young children had the highest rate of hat usage in the current study, possibly due to parental example or dictates. Research has shown the importance of role models in promoting sun safety to young children,8,9 so perhaps use of hats by parents or MLB players contributed to the hat-wearing behavior observed in this subpopulation.

Given the limited change observed in hat-wearing behaviors over the last decade, a knowledge and behavioral gap appears to exist that may be able to be exploited to enhance future sun protection. Also, based on our findings, the MLB and other sun-protection education campaigns may wish to augment their UVR protective messages by offering hat giveaways, which appear to have a notable impact.

Acknowledgment

The authors thank Jessie Skapik, BS (New York, New York), for her independent review of the spectator photographs.

References

References

1. Rigel DS. Cutaneous ultraviolet exposure and its relationship to the development of skin cancer. J Am Acad Dermatol. 2008;58(5, suppl 2):S129-S132.

2. Lim HW, James WD, Rigel DS, et al. Adverse effects of ultraviolet radiation from the use of indoor tanning equipment: time to ban the tan. J Am Acad Dermatol. 2011;64:893-902.

3. Play Sun Smart. American Academy of Dermatology website. https://www.aad.org/public/spot-skin-cancer/programs/play-sun-smart. Accessed August 25, 2016.

4. Rigel AS, Lebwohl MG. Hat-wearing patterns in persons attending baseball games. J Am Acad Dermatol. 2006;54:918-919.

5. MLB attendance report - 2016. ESPN website. www.espn.go.com/mlb/attendance. Accessed May 20, 2016.

6. Turner D, Harrison SL, Buettner P, et al. Does being a “SunSmart School” influence hat-wearing compliance? an ecological study of hat-wearing rates at Australian primary schools in a region of high sun exposure [published online December 29, 2013]. Prev Med. 2014;60:107-114.

7. Dubas LE, Adams BB. Sunscreen use and availability among female collegiate athletes [published online February 3, 2012]. J Am Acad Dermatol. 2012;67:876.e1-876.e6.

8. O’Riodran DL, Geller AC, Brooks DR, et al. Sunburn reduction through parental role modeling and sunscreen vigilance. J Pediatr. 2003;142:67-72.

9. Turrisi R, Hillhouse J, Heavin S, et al. Examination of the short-term efficacy of a parent-based intervention to prevent skin cancer. J Behav Med. 2004;27:393-412.

References

References

1. Rigel DS. Cutaneous ultraviolet exposure and its relationship to the development of skin cancer. J Am Acad Dermatol. 2008;58(5, suppl 2):S129-S132.

2. Lim HW, James WD, Rigel DS, et al. Adverse effects of ultraviolet radiation from the use of indoor tanning equipment: time to ban the tan. J Am Acad Dermatol. 2011;64:893-902.

3. Play Sun Smart. American Academy of Dermatology website. https://www.aad.org/public/spot-skin-cancer/programs/play-sun-smart. Accessed August 25, 2016.

4. Rigel AS, Lebwohl MG. Hat-wearing patterns in persons attending baseball games. J Am Acad Dermatol. 2006;54:918-919.

5. MLB attendance report - 2016. ESPN website. www.espn.go.com/mlb/attendance. Accessed May 20, 2016.

6. Turner D, Harrison SL, Buettner P, et al. Does being a “SunSmart School” influence hat-wearing compliance? an ecological study of hat-wearing rates at Australian primary schools in a region of high sun exposure [published online December 29, 2013]. Prev Med. 2014;60:107-114.

7. Dubas LE, Adams BB. Sunscreen use and availability among female collegiate athletes [published online February 3, 2012]. J Am Acad Dermatol. 2012;67:876.e1-876.e6.

8. O’Riodran DL, Geller AC, Brooks DR, et al. Sunburn reduction through parental role modeling and sunscreen vigilance. J Pediatr. 2003;142:67-72.

9. Turrisi R, Hillhouse J, Heavin S, et al. Examination of the short-term efficacy of a parent-based intervention to prevent skin cancer. J Behav Med. 2004;27:393-412.

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Hat-Wearing Patterns in Spectators Attending Baseball Games: A 10-Year Retrospective Comparison
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Practice Points

  • With less than half of attendees wearing hats to Major League Baseball games, there has been limited change in hat-wearing behavior over the last decade, possibly due to a knowledge or behavioral gap.
  • Improved availability and access to hats can lead to improved sun-protective behaviors.
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