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Table 1.  
Demographic Characteristics of Study Participants
Demographic Characteristics of Study Participants
Table 2.  
Participants Reporting an Intention to Be Treated for Actinic Keratosis Based on Information Presentationa
Participants Reporting an Intention to Be Treated for Actinic Keratosis Based on Information Presentationa
Table 3.  
Patient Choice of AK Treatment Rather Than No Treatment
Patient Choice of AK Treatment Rather Than No Treatment
1.
Parkinson  L, Rainbird  K, Kerridge  I,  et al.  Cancer patients’ attitudes toward euthanasia and physician-assisted suicide: the influence of question wording and patients’ own definitions on responses.  J Bioeth Inq. 2005;2(2):82-89.PubMedGoogle ScholarCrossref
2.
Magelssen  M, Supphellen  M, Nortvedt  P, Materstvedt  LJ.  Attitudes towards assisted dying are influenced by question wording and order: a survey experiment.  BMC Med Ethics. 2016;17(1):24.PubMedGoogle ScholarCrossref
3.
Büchter  RB, Fechtelpeter  D, Knelangen  M, Ehrlich  M, Waltering  A.  Words or numbers? communicating risk of adverse effects in written consumer health information: a systematic review and meta-analysis.  BMC Med Inform Decis Mak. 2014;14:76.PubMedGoogle ScholarCrossref
4.
Heritage  J, Robinson  JD, Elliott  MN, Beckett  M, Wilkes  M.  Reducing patients’ unmet concerns in primary care: the difference one word can make.  J Gen Intern Med. 2007;22(10):1429-1433.PubMedGoogle ScholarCrossref
5.
Leader  AE, Weiner  JL, Kelly  BJ, Hornik  RC, Cappella  JN.  Effects of information framing on human papillomavirus vaccination.  J Womens Health (Larchmt). 2009;18(2):225-233.PubMedGoogle ScholarCrossref
6.
Gurm  HS, Litaker  DG.  Framing procedural risks to patients: is 99% safe the same as a risk of 1 in 100?  Acad Med. 2000;75(8):840-842.PubMedGoogle ScholarCrossref
7.
Heaphy  MR  Jr, Ackerman  AB.  The nature of solar keratosis: a critical review in historical perspective.  J Am Acad Dermatol. 2000;43(1, pt 1):138-150.PubMedGoogle ScholarCrossref
8.
Werner  RN, Sammain  A, Erdmann  R, Hartmann  V, Stockfleth  E, Nast  A.  The natural history of actinic keratosis: a systematic review.  Br J Dermatol. 2013;169(3):502-518.PubMedGoogle ScholarCrossref
9.
Engel  A, Johnson  M-L, Haynes  SG.  Health effects of sunlight exposure in the United States: results from the first National Health and Nutrition Examination Survey, 1971-1974.  Arch Dermatol. 1988;124(1):72-79.PubMedGoogle ScholarCrossref
10.
Harvey  I, Frankel  S, Marks  R, Shalom  D, Nolan-Farrell  M.  Non-melanoma skin cancer and solar keratoses; I: methods and descriptive results of the South Wales Skin Cancer Study.  Br J Cancer. 1996;74(8):1302-1307.PubMedGoogle ScholarCrossref
11.
Frost  C, Williams  G, Green  A.  High incidence and regression rates of solar keratoses in a Queensland community.  J Invest Dermatol. 2000;115(2):273-277.PubMedGoogle ScholarCrossref
12.
Naldi  L, Chatenoud  L, Piccitto  R, Colombo  P, Placchesi  EB, La Vecchia  C; Prevalence of Actinic Keratoses Italian Study (PraKtis) Group.  Prevalence of actinic keratoses and associated factors in a representative sample of the Italian adult population: results from the Prevalence of Actinic Keratoses Italian Study, 2003-2004.  Arch Dermatol. 2006;142(6):722-726.PubMedGoogle ScholarCrossref
13.
Peris  K, Calzavara-Pinton  PG, Neri  L,  et al.  Italian expert consensus for the management of actinic keratosis in immunocompetent patients.  J Eur Acad Dermatol Venereol. 2016;30(7):1077-1084.PubMedGoogle ScholarCrossref
14.
Anwar  J, Wrone  DA, Kimyai-Asadi  A, Alam  M.  The development of actinic keratosis into invasive squamous cell carcinoma: evidence and evolving classification schemes.  Clin Dermatol. 2004;22(3):189-196.PubMedGoogle ScholarCrossref
15.
Stockfleth  E, Ferrandiz  C, Grob  JJ, Leigh  I, Pehamberger  H, Kerl  H; European Skin Academy.  Development of a treatment algorithm for actinic keratoses: a European consensus.  Eur J Dermatol. 2008;18(6):651-659.PubMedGoogle Scholar
16.
Peserico  A, Neri  L, Calzavara Pinton  P,  et al.  Key Opinion Leader (KOL) consensus for actinic keratosis management in Italy: the AKTUAL Workshop.  G Ital Dermatol Venereol. 2013;148(5):515-524.PubMedGoogle Scholar
17.
De Berker  D, McGregor  JM, Hughes  BR; British Association of Dermatologists Therapy Guidelines and Audit Subcommittee.  Guidelines for the management of actinic keratoses.  Br J Dermatol. 2007;156(2):222-230.PubMedGoogle ScholarCrossref
18.
Criscione  VD, Weinstock  MA, Naylor  MF, Luque  C, Eide  MJ, Bingham  SF; Department of Veterans Affairs Topical Tretinoin Chemoprevention Trial Group.  Actinic keratoses: natural history and risk of malignant transformation in the Veterans Affairs Topical Tretinoin Chemoprevention Trial.  Cancer. 2009;115(11):2523-2530.PubMedGoogle ScholarCrossref
19.
Werner  RN, Stockfleth  E, Connolly  SM,  et al; International League of Dermatological Societies; European Dermatology Forum.  Evidence- and consensus-based (S3) guidelines for the treatment of actinic keratosis: International League of Dermatological Societies in cooperation with the European Dermatology Forum—short version.  J Eur Acad Dermatol Venereol. 2015;29(11):2069-2079.PubMedGoogle ScholarCrossref
20.
Marks  R, Foley  P, Goodman  G, Hage  BH, Selwood  TS.  Spontaneous remission of solar keratoses: the case for conservative management.  Br J Dermatol. 1986;115(6):649-655.PubMedGoogle ScholarCrossref
21.
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.  J Biomed Inform. 2009;42(2):377-381.PubMedGoogle ScholarCrossref
22.
Marks  R, Rennie  G, Selwood  TS.  Malignant transformation of solar keratoses to squamous cell carcinoma.  Lancet. 1988;1(8589):795-797.PubMedGoogle ScholarCrossref
23.
Buhrmester  M, Kwang  T, Gosling  SD.  Amazon’s Mechanical Turk: a new source of inexpensive, yet high-quality, data?  Perspect Psychol Sci. 2011;6(1):3-5.PubMedGoogle ScholarCrossref
24.
Ross  J, Irani  L, Silberman  MS, Zaldivar  A, Tomlinson  B. Who are the crowdworkers? In: Proceedings of the 28th ACM Conference on Human Factors in Computing Systems. Extended Abstracts on Human Factors in Computing Systems—CHI EA ’10. New York, NY: ACM Press; 2010:2863.
25.
Ipeirotis  P. Demographics of Mechanical Turk. http://www.ipeirotis.com/wp-content/uploads/2012/02/CeDER-10-01.pdf. Published February 2012. Accessed August 11, 2016.
26.
Charles  C, Whelan  T, Gafni  A.  What do we mean by partnership in making decisions about treatment?  BMJ. 1999;319(7212):780-782.PubMedGoogle ScholarCrossref
27.
Fischer  GS, Tulsky  JA, Rose  MR, Siminoff  LA, Arnold  RM.  Patient knowledge and physician predictions of treatment preferences after discussion of advance directives.  J Gen Intern Med. 1998;13(7):447-454.PubMedGoogle ScholarCrossref
Original Investigation
May 2017

Influence of Information Framing on Patient Decisions to Treat Actinic Keratosis

Author Affiliations
  • 1Student, Penn State College of Medicine, Hershey, Pennsylvania
  • 2Department of Dermatology, Penn State Milton S. Hershey Medical Center, Hershey, Pennsylvania
JAMA Dermatol. 2017;153(5):421-426. doi:10.1001/jamadermatol.2016.5245
Key Points

Question  How does framing the presentation of information about actinic keratosis influence patient decisions to receive treatment for actinic keratosis?

Findings  In this survey study of 539 dermatology clinic patients, there were significant differences in the proportions of patients who would decide to receive treatment for actinic keratosis when statements about the disease were framed differently. When actinic keratosis was described as precancer, the highest proportion of participants preferred treatment; when discussed as a disease that could possibly go away without treatment and not turn into life-threatening skin cancer, the lowest proportion of participants chose treatment.

Meaning  Patients’ decisions to receive treatment for actinic keratosis are significantly influenced by how physicians present information, especially regarding the risk of transformation to cancer.

Abstract

Importance  Actinic keratosis (AK) is a skin growth induced by UV light exposure that requires long-term management because a small proportion of the disease can progress to squamous cell carcinoma. The influence of how clinicians frame or present information to patients may affect decision making about AK.

Objective  To evaluate the differences in patients’ decisions on whether to receive treatment for AK related to information presentation or choice framing.

Design, Setting, and Participants  A prospective survey study was performed from June 1 to July 31, 2016, in participants who were able to read English. Participants were recruited through the Penn State Milton S. Hershey Dermatology Clinic and an online survey site. The survey was conducted through an online portal. A total of 571 individuals were recruited. Regression analysis, correlation coefficient analysis, and test-retest validation were conducted.

Main Outcomes and Measures  The proportions of patients choosing to receive treatment for AK. Analyses were performed to adjust for age, sex, educational level, history of skin cancer, and history of AK.

Results  Of the 571 recruited participants, 539 (94.4%) returned completed surveys. The mean (SD) age of respondents was 42.9 (17.8) years; 306 (56.8%) were women. The decision to receive treatment for AK varied from 57.7% (n = 311) to 92.2% (n = 497) for the 5 scenarios presented in the questions (P < .001). The question that presented AK as a “precancer” had the highest proportion of participants who preferred treatment (497 [92.2%]). Two questions that presented the risk of AK as not progressing to cancer had the lowest proportion of individuals who chose treatment (311 [57.7%] and 328 [60.9%]). Participants from the clinic and from the online portal were significantly different in age (mean [SD] age, 56.1 [17.6] vs 33.3 [10.0] years), sex (145 [63.6%] vs 161 [51.8%] were females), educational level (40 [17.5%] vs 80 [25.7%] had completed some graduate school), history of AK (46 [20.2%] vs 19 [6.1%] answered yes), and history of skin cancer (76 [33.3%] vs 15 [4.8%] answered yes) (all P ≤ .001). Based on a regression analysis, age, sex, and previous diagnosis of skin cancer were not significantly associated with the participants’ responses.

Conclusions and Relevance  This study found that patients’ decisions on whether to receive treatment for AK is significantly affected by physician wording, especially with alterations in the presentation of risk of malignant transformation.

Introduction

Previous studies have demonstrated that the manner in which a physician presents medical information (ie, choice framing) is a critical factor in a patient’s treatment decision and has a significant effect on patients’ choices regarding their care.1-3 Even the modification of 1 word in a statement about medical management can alter the patient’s treatment decision significantly.4 Studies on physician information presentation have been conducted related to physician-assisted suicide, vaccinations, and procedural risk, but, to our knowledge, none have been performed regarding treatment options for skin conditions.1,2,5,6

Actinic keratoses (AKs) have the potential to progress to squamous cell carcinoma.7,8 Actinic keratoses are the most common skin disease in the adult population, with a current estimated prevalence ranging from 1% to 44%.9-13 There are several therapeutic options, and multiple guidelines have been created for this disease.13-17 Actinic keratoses have been described as precancerous; however, the rate of transformation to squamous cell carcinoma is estimated to be 0.1% to 0.6% per lesion per year.18,19 In addition, spontaneous regression may also occur; Marks et al20 found that 25.9% of AKs present at baseline were not present 1 year later. In addition, studies of sunscreen application have demonstrated up to a 53% reduction in AKs.8 Thus, the management of AK is complex, which makes the discussion between clinicians and patients even more important.

Our study is a novel and important area of research since patient autonomy is a major factor in modern medicine. We aimed to examine the influence of information presentation on patients’ decisions to receive treatment for AK, enabling us to better understand clinicians’ discussions with their patients about treatment options.

Methods

The study was conducted from June 1 to July 31, 2016. Study data were collected and managed using Research Electronic Data Capture (REDCap) tools hosted at Penn State Hershey. REDCap is a secure web-based application designed to support data capture for research studies.21 A 10-question survey with a multiple-choice format was developed (eAppendix in the Supplement). Questions were based on extant AK studies.6,8,22 A pilot survey was evaluated for content, wording, and completion time by staff and patients of the Penn State Milton S. Hershey Medical Center Department of Dermatology, Hershey, Pennsylvania. The first 5 items collected demographic information, including age, sex, educational level, history of skin cancer, and history of AK. The last 5 items presented various scenarios and measured intention to be treated (Box). Patients were given the information presented in the Box and no additional information about AK. The survey software did not allow participants to review or change items previously completed.

Box Section Ref ID
Box.

Survey Questions on Information Presentation Influencing Actinic Keratoses Treatment

Question 1
  • Actinic keratoses are spots of sun damage. About 0.5% of actinic keratoses turn into a non–life-threatening skin cancer and 25% go away without treatment. Based on this statement, how likely are you to want treatment?

Question 2
  • Actinic keratoses are spots of sun damage. About 0.5% of actinic keratoses turn into a non–life-threatening skin cancer and 75% stay unchanged on your skin. Based on this statement, how likely are you to want treatment?

Question 3
  • Actinic keratoses are spots of sun damage. About 99.5% of actinic keratoses will not turn into skin cancer and 25% will go away without treatment. Based on this statement, how likely are you to want treatment?

Question 4
  • Actinic keratoses are spots of sun damage. About 99.5% of actinic keratoses will not turn into skin cancer and 75% stay unchanged on your skin. Based on this statement, how likely are you to want treatment?

Question 5
  • Actinic keratoses are precancers. Based on this statement, how likely are you to want treatment?

Response options for each question were definitely treat, very likely to treat, somewhat likely to treat, somewhat likely to not treat, very likely to not treat, or definitely not treat.

Participants were recruited from the Penn State Milton S. Hershey Dermatology Clinic and through the Amazon Mechanical Turk (mTurk) platform (https://www.mturk.com/mturk/welcome). Once mTurk users decided to participate, a hyperlink took them directly to the survey in REDCap. Inclusion criteria for all participants included being (1) able to read English, (2) 18 years or older, and (3) either a patient in the Penn State Milton S. Hershey Dermatology Clinic or a participant in Amazon’s mTurk platform. Participants were not required to have a history of AK, skin cancer, or any other skin condition. Participants were excluded if they did not meet inclusion criteria or did not consent to participate. Participants recruited from the dermatology clinic were not compensated. However, because Amazon requires some amount of compensation, those enrolled through the mTurk platform received $0.02. The study was approved by the Penn State College of Medicine Institutional Review Board, and all participants provided written informed consent.

Statistical Analysis

Descriptive statistical analyses were performed on all variables. Frequencies of different answers to each question on the survey were calculated. Comparisons were made by using a 2-tailed, unpaired t test for continuous variables (eg, age) and the χ2 test for categorical variables, with the Fisher exact test used when necessary. Regression analysis was conducted on the questions that were asked to determine whether the demographic variables played a significant role in the way that individuals answered. Multivariate logistic regression analysis was performed on the decision to receive treatment related to the effects of group, including dermatology clinic or mTurk platform, age, sex, educational level, history of AK, and former diagnosis of skin cancer as covariates. For these analyses, answers on the ordinal scale were condensed into binary responses. Instances in which the participants responded “decline to answer” for sex or “not sure” for previous diagnosis of skin cancer or AK were excluded from the analysis since these instances were rare. Correlation coefficients were also determined to evaluate whether there was any pattern in the ways that participants answered the questions using the full 6-point scale.

Test-retest validation was conducted using a subset of respondents. An electronic invitation was sent to an independent sample of individuals who were asked to answer the 5 questions and provide an email address to retake the survey 24 to 48 hours later. The initial invitation yielded 112 completed surveys. The questions were then reordered using a random number generator and sent to the participants approximately 48 hours after the initial survey. A weighted Cohen κ test for each of the questions was used to evaluate agreement between the initial and second surveys. All questions showed moderate to substantial agreement based on the weighted κ coefficient. For questions 1 through 5, the coefficients were 0.53, 0.68, 0.68, 0.60, and 0.65, respectively (all P < .0001). Data analysis was performed using SAS, version 9.4 for Windows (SAS Institute Inc).

Results
Characteristics of Participants

In all, 571 participants were recruited: 322 through mTurk and 249 through the dermatology clinic. There were 539 complete surveys (94.4%); the proportion of incomplete surveys was 8.4% (n = 21) and 3.4% (n = 11) for the clinic and online groups, respectively. The response rate for participants recruited through the clinic was 91.6% (n = 249). The response rate for the online survey—an unrestricted, self-selected survey—could not be calculated because the number of people who viewed and decided not to complete the survey is unknown. The mTurk and clinic respondents differed significantly in demographics related to age, sex, educational level, history of AK, and history of skin cancer (Table 1). Such differences were expected since previous studies found that mTurk users are younger than the general population.23-25

Patterns of Treatment

Table 2 presents the frequencies of participants’ intention to receive treatment for AK based on the presentation of the information. Participants were most likely to endorse treatment for question 5 (497 [92.2%]); questions 3 and 4 had the lowest number of participants (311 [57.7%] and 328 [60.9%], respectively) responding that they would want treatment. For all questions, most respondents chose treatment, and the differences among all questions were significantly different.

Based on the regression analysis, age, sex, and previous diagnosis of skin cancer were not significantly associated with participants’ responses (Table 3). Group identity, defined as participants being either a dermatology clinic patient or an online respondent, was significant in questions 1 and 5. Having some college education had significance compared with graduate-level education for the decision to receive treatment in questions 2 and 4. Overall, there were few strong and clinically significant findings for the covariates and patients’ decisions regarding treatment.

We conducted a simple correlation test to investigate patterns in responses to questions. For this analysis, the full 6-point answer scale was used. Question 5 had only a mild positive correlation with all other questions (Pearson correlation coefficient, 0.39-0.55); questions 1 and 2 and questions 3 and 4 had moderately strong correlations (0.77 and 0.80, respectively). The first statement was identical in these question pairs. Questions 1 and 3 and questions 2 and 4 had slightly lower correlations, with coefficients of 0.67 and 0.75, respectively. The second statement was identical for these question pairs; therefore, the analyses were not run.

Discussion

This study shows that, for AK, the format of information presentation has an important effect on a patient’s intention to be treated. A growing body of evidence supports this finding for other health-related decisions.1-6 In the present study, the highest proportion of participants chose treatment when AK behavior was presented as precancerous. In our experience, this statement is frequently used by clinicians to describe AK to patients. Questions 1 through 4 included specific rates of malignant transformation and risk of spontaneous resolution, with reversals of the numbers related to the progression to cancer. The lowest proportion of participants intended to receive treatment when statements were worded with an optimistic outlook related to the proportion of AK that may not progress to cancer. Statements with cautionary wording regarding the risk of AK progressing to cancer had an intermediate rate of participants who intended to receive treatment for AK. The difference in responses based on the phrasing of the statement highlights the importance of clinicians thoughtfully considering how to phrase information for patients since information phrasing may influence patients’ decision making.26

The strong positive correlations between questions 1 and 2 and questions 3 and 4 and lesser correlations between questions 1 and 3 and questions 2 and 4 suggest that the first half of the question had a larger effect on patients’ treatment decision than the second half of the question. This finding may be attributable to the word cancer in the first half of the statement and the risk of this outcome. This correlation between the wording of the question and patient treatment decision further supports our conclusion that wording affects patients’ treatment choice.

In most cases, patient demographics did not appear to have a significant association with patients’ treatment decisions. If participants were making choices based on personal history, these variables would be expected to have a significant effect. However, only educational level had any significant effect on treatment. It could be hypothesized that those with more education would be expected to make more rational decisions or to have similar answers for questions that have the same meaning (eg, 99.5% of lesions do not turn into skin cancer and 0.5% of lesions turn into a non–life-threatening skin cancer). However, educational level was found to have a significant effect on participants’ decision to receive treatment in only 2 of the 20 permutations. Group was statistically significant for questions 1 and 5, with a higher percentage of clinic patients choosing treatment in both cases. This finding may be attributable to clinic selection for patients who are more likely to receive treatment. Overall, this study shows that wording of information about AK is more significant in patient decision making than his or her age, sex, history of skin cancer, or history of AK.

This study found that, regardless of the way information is presented, most individuals would choose treatment for AK. However, there are a significant number of patients whose treatment preferences changed based on minor modifications or reversals in the wording. It is essential that physicians discuss treatment options thoroughly. A study by Fischer et al27 found that, in 18 of 20 scenarios, physicians were no better able to determine their patients’ treatment preferences than by chance alone. Although AK is not considered life-threatening, it is still essential that patients are able to make informed decisions that are then executed and that clinicians understand the impact of how they deliver information on patient’s decision making.

Limitations

The interpretation of these findings requires consideration of some potential limitations to survey research. There is little information known about individuals who considered vs those who did not consider participating. Thus, the true response rate cannot be calculated or the differences between those populations quantified, and there may also be a difference in participants who chose to take the survey vs those who declined. However, this project did not seek to accurately infer population estimates. The results are based only on survey data from hypothetical physician statements and so may not match actual practice. These hypothetical physician statements do not consider complicated situations, such as the number and location of AKs; desired and available treatment modalities; and the patient’s general health. This survey did not ask for participants to explain their responses, and participant choices were restricted to close-ended, multiple-choice answers. Our survey questions demonstrated moderate intrarater agreement; thus, some of the differences may be due to error. However, we believe the responses are valid for investigating attitudes toward AK.

Conclusions

This study found that patients’ decisions to receive treatment for AK are significantly affected by physician wording of the information provided, especially with alterations in the presentation of risk of malignant transformation. Based on this observation, we suggest that physicians offer a more thorough explanation of the risk associated with AK and be cognizant of the influence of statements on patient’s decision making.

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Article Information

Corresponding Author: Joslyn S. Kirby, MD, MS, MEd, Department of Dermatology, Penn State Milton S. Hershey Medical Center, 500 University Ave, HU 14, Hershey, PA 17033 (jkirby1@hmc.psu.edu).

Accepted for Publication: November 8, 2016.

Correction: This article was corrected on May 10, 2017, for an error in the description of participant compensation in the Methods section.

Published Online: January 18, 2017. doi:10.1001/jamadermatol.2016.5245

Author Contributions: Mss Berry and Butt had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Kirby.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Berry, Butt.

Critical revision of the manuscript for important intellectual content: Kirby.

Statistical analysis: Berry, Butt.

Administrative, technical, or material support: Butt.

Study supervision: Kirby.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was supported in part by the Penn State Clinical & Translational Research Institute, Pennsylvania State University Clinical and Translational Science Award, National Institutes of Health (NIH)/National Center for Advancing Translational Sciences (NCATS) grant UL1 TR000127.

Role of the Funder/Sponsor: The funding organization had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The contents of this article are solely the responsibility of the authors and do not necessarily represent the official views of the NIH or NCATS.

References
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2.
Magelssen  M, Supphellen  M, Nortvedt  P, Materstvedt  LJ.  Attitudes towards assisted dying are influenced by question wording and order: a survey experiment.  BMC Med Ethics. 2016;17(1):24.PubMedGoogle ScholarCrossref
3.
Büchter  RB, Fechtelpeter  D, Knelangen  M, Ehrlich  M, Waltering  A.  Words or numbers? communicating risk of adverse effects in written consumer health information: a systematic review and meta-analysis.  BMC Med Inform Decis Mak. 2014;14:76.PubMedGoogle ScholarCrossref
4.
Heritage  J, Robinson  JD, Elliott  MN, Beckett  M, Wilkes  M.  Reducing patients’ unmet concerns in primary care: the difference one word can make.  J Gen Intern Med. 2007;22(10):1429-1433.PubMedGoogle ScholarCrossref
5.
Leader  AE, Weiner  JL, Kelly  BJ, Hornik  RC, Cappella  JN.  Effects of information framing on human papillomavirus vaccination.  J Womens Health (Larchmt). 2009;18(2):225-233.PubMedGoogle ScholarCrossref
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Gurm  HS, Litaker  DG.  Framing procedural risks to patients: is 99% safe the same as a risk of 1 in 100?  Acad Med. 2000;75(8):840-842.PubMedGoogle ScholarCrossref
7.
Heaphy  MR  Jr, Ackerman  AB.  The nature of solar keratosis: a critical review in historical perspective.  J Am Acad Dermatol. 2000;43(1, pt 1):138-150.PubMedGoogle ScholarCrossref
8.
Werner  RN, Sammain  A, Erdmann  R, Hartmann  V, Stockfleth  E, Nast  A.  The natural history of actinic keratosis: a systematic review.  Br J Dermatol. 2013;169(3):502-518.PubMedGoogle ScholarCrossref
9.
Engel  A, Johnson  M-L, Haynes  SG.  Health effects of sunlight exposure in the United States: results from the first National Health and Nutrition Examination Survey, 1971-1974.  Arch Dermatol. 1988;124(1):72-79.PubMedGoogle ScholarCrossref
10.
Harvey  I, Frankel  S, Marks  R, Shalom  D, Nolan-Farrell  M.  Non-melanoma skin cancer and solar keratoses; I: methods and descriptive results of the South Wales Skin Cancer Study.  Br J Cancer. 1996;74(8):1302-1307.PubMedGoogle ScholarCrossref
11.
Frost  C, Williams  G, Green  A.  High incidence and regression rates of solar keratoses in a Queensland community.  J Invest Dermatol. 2000;115(2):273-277.PubMedGoogle ScholarCrossref
12.
Naldi  L, Chatenoud  L, Piccitto  R, Colombo  P, Placchesi  EB, La Vecchia  C; Prevalence of Actinic Keratoses Italian Study (PraKtis) Group.  Prevalence of actinic keratoses and associated factors in a representative sample of the Italian adult population: results from the Prevalence of Actinic Keratoses Italian Study, 2003-2004.  Arch Dermatol. 2006;142(6):722-726.PubMedGoogle ScholarCrossref
13.
Peris  K, Calzavara-Pinton  PG, Neri  L,  et al.  Italian expert consensus for the management of actinic keratosis in immunocompetent patients.  J Eur Acad Dermatol Venereol. 2016;30(7):1077-1084.PubMedGoogle ScholarCrossref
14.
Anwar  J, Wrone  DA, Kimyai-Asadi  A, Alam  M.  The development of actinic keratosis into invasive squamous cell carcinoma: evidence and evolving classification schemes.  Clin Dermatol. 2004;22(3):189-196.PubMedGoogle ScholarCrossref
15.
Stockfleth  E, Ferrandiz  C, Grob  JJ, Leigh  I, Pehamberger  H, Kerl  H; European Skin Academy.  Development of a treatment algorithm for actinic keratoses: a European consensus.  Eur J Dermatol. 2008;18(6):651-659.PubMedGoogle Scholar
16.
Peserico  A, Neri  L, Calzavara Pinton  P,  et al.  Key Opinion Leader (KOL) consensus for actinic keratosis management in Italy: the AKTUAL Workshop.  G Ital Dermatol Venereol. 2013;148(5):515-524.PubMedGoogle Scholar
17.
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