0
We're unable to sign you in at this time. Please try again in a few minutes.
Retry
We were able to sign you in, but your subscription(s) could not be found. Please try again in a few minutes.
Retry
There may be a problem with your account. Please contact the AMA Service Center to resolve this issue.
Contact the AMA Service Center:
Telephone: 1 (800) 262-2350 or 1 (312) 670-7827  *   Email: subscriptions@jamanetwork.com
Error Message ......
Study | ONLINE FIRST

Improvement in Patient Performance of Skin Self-examinations After Intervention With Interactive Education and Telecommunication Reminders A Randomized Controlled Study FREE

Savina Aneja, MD; Angela K. Brimhall, DO, MS; Douglas R. Kast, DO; Sanjay Aneja, BS; Diana Carlson, DO; Kevin D. Cooper, MD; Jeremy S. Bordeaux, MD, MPH
[+] Author Affiliations

Author Affiliations School of Medicine, Case Western Reserve University (Drs Aneja, Cooper, and Bordeaux), Cleveland, Ohio; Department of Dermatology (Drs Brimhall, Kast, Carlson, Cooper, and Bordeaux), Case Comprehensive Cancer Center (Drs Cooper and Bordeaux), and Skin Diseases Research Center (Drs Cooper and Bordeaux), University Hospitals Case Medical Center, Cleveland; and Yale School of Medicine, New Haven, Connecticut (Mr Aneja).


Arch Dermatol. 2012;148(11):1266-1272. doi:10.1001/archdermatol.2012.2480.
Text Size: A A A
Published online

Objective To determine if interactive computerized patient education, skin self-examination (SSE) tutorials, and telecommunication reminders could be combined to increase patient performance of SSEs, increase confidence in ability to identify melanoma, and influence individual melanoma risk perception.

Design A total of 132 adult participants from our dermatology clinics were enrolled in an interventional study and randomized to a control group or an intervention group. Survey data were collected from all participants on the day of enrollment and 3 months after enrollment.

Setting University Hospitals Case Medical Center outpatient dermatology clinics.

Participants English speakers older than 18 years.

Interventions The intervention group (1) participated in a computer-assisted learning tutorial, (2) took part in a hands-on SSE tutorial, (3) received monthly telecommunication reminders to perform SSEs for 12 weeks, and (4) received a brochure on melanoma detection. The control group received only the brochure on melanoma detection.

Main Outcome Measures Self-report of performance of SSEs. Melanoma risk perception and confidence in ability to identify melanoma were secondary considerations. Logistic regressions, controlling for race, age, sex, education, and family history of melanoma, were used to assess the effectiveness of the intervention.

Results At the 3-month follow-up, those in the intervention group were more likely to perform SSEs (odds ratio [OR], 2.36; P ≤ .05). In addition, those who participated in the intervention were more likely to report being confident in their ability to identify melanoma during an SSE (OR, 2.72; P ≤ .05).

Conclusion Computer-assisted patient education used in conjunction with a hands-on SSE tutorial and telecommunication reminders can increase patient performance of SSEs and confidence in the ability to identify melanoma.

Figures in this Article

The rate of malignant melanoma (MM) continues to increase, with current estimates that 1 in 53 adults in the United States will be diagnosed as having MM of the skin during their lifetime.1 The most common subtypes of MM demonstrate early radial growth and only later enter a vertical or invasive growth phase.2 Mortality is largely dependent on a Breslow depth at time of diagnosis.3 Early detection of MM has been associated with thinner lesions and improved survival.4 Stage I disease exhibits a 5-year survival of 97%, whereas stage IV metastatic disease is associated with a 1-year survival rate of 33% to 62%.3 Early detection remains the primary strategy for reducing the morbidity and mortality of MM.

Patients and their partners are integral to the diagnosis of MM and detect anywhere from 57% to 72%3,5,6 of primary MM and 62%7 of recurrent MM. Consequently, patient education of MM symptoms, including change or irregularity in symmetry, border, color, or diameter (“ABCDs” of MM), and implementing preventive behaviors, such as skin self-examinations (SSEs) and UV protection, has the potential to improve patient survival.810 Furthermore, a lack of understanding of MM symptoms has been associated with delayed diagnosis and poorer prognosis.11,12

Early detection and prevention of melanoma can be facilitated by regular SSEs. A large case-control study (N = 1199) demonstrated a 63% decrease in mortality from primary and secondary MM in patients who performed SSEs compared with those who did not.13 A retrospective review of Italian patients diagnosed as having MM reported an association between MM detection by SSEs and thinner lesion at time of diagnosis.14 Despite the potential for decreased mortality, many barriers to the performance of SSEs still exist, and few prospective trials regarding interventions to increase the regular use of SSEs have been performed.15

Exploring methods for patient behavior modification is an evolving area of research. Interactive computer-assisted learning (CAL) has been used successfully to increase knowledge and patient protective behavior relating to breast cancer screening,16,17 asthma control,18 and sun safety.19,20 More recently, interactive CAL has also been applied to melanoma prevention and early detection. An intervention known as Skinsafe, an interactive computer-based educational module, was developed to increase patient awareness of melanoma symptoms, melanoma risks, sun protective behaviors, and the importance of SSEs.

Telecommunication reminders have been used successfully to modify the behavior of patients with type 2 diabetes mellitus,21 raise awareness of breast health,22 manage pain for sickle cell patients,23 and aid in weight loss techniques.24 Text, e-mail, phone, and letter reminders deliver timely information to the patient in their home. Previous observations have concluded that this increases the likelihood of patient compliance.25 We propose that a multifactorial approach including interactive CAL, hands-on SSEs tutorials, and telecommunication reminders can be combined to increase patient performance of SSEs. We sought to determine if interactive computer-assisted patient education, hands-on SSE tutorials, and telecommunication reminders could be combined to effectively increase patient performance of SSEs. Secondarily, we considered if these interventions influenced confidence in patients' ability to identity melanoma during an SSE and individual perceived risk for melanoma.

After receiving institutional review board approval, an interventional study was conducted at University Hospital Case Medical Center outpatient dermatology clinics (Cleveland, Ohio) from June 2010 to September 2010. Patients, accompanying family members, caregivers, or friends seen at the dermatology clinic who were at least 18 years old and spoke English were eligible.

INTERVENTION

Participants were randomized into the control or intervention arm using permutated block randomization. The intervention group was involved as follows:

1. They participated in the Skinsafe (CAL) tutorial. This tool contained educational interactive modules on MM risk, MM symptoms, SSEs, and preventive measures. The program was developed in 1998 in the United Kingdom by a multidisciplinary team comprised of dermatologists and health psychologists. The participants were asked to complete 8 modules in a single setting on a laptop computer. These modules included a combination of animation cartoons, photographs, and text. Some modules asked the participants to correctly identify lesions that may be suspicious for melanoma in a quiz format, whereas other modules simply presented information on sun protection and melanoma risk factors that the participants could read on the screen. In addition, the CAL program calculated the participant's risk for melanoma (“higher than average,” “average,” or “less average than”), which we compared with the participant's self-perceived risk for melanoma. The computerized risk was based on the participant's response to 10 standardized questions that asked participants about family history of melanoma, history of sunburns and sun exposure, skin and eye color, freckles, and number of moles on the skin. Completion of the CAL tutorial took 5 to 30 minutes.

2. The intervention group participated in a kinesthetic, hands-on, SSE tutorial, while clothed. The role-play SSE was led by the research assistant and demonstrated how to examine different angles of one's body, including difficult-to-evaluate areas, such as the scalp, nails, and between fingers and toes.

3. They received a selected telecommunication reminder to perform SSEs, which the participant would receive throughout the study. The reminders contained a brief message, which contained a salutation from the principal investigator (A.K.B.) and a single statement reminding the participant to perform monthly SSEs. Participants could elect to receive a text message, e-mail, phone call, or letter reminder. Participants also indicated a desired day of week and time to receive the reminder. Reminders were sent to the participants once a month at the indicated time throughout the study period.

4. They received a melanoma education brochure, published by the American Academy of Dermatology,26 containing information on melanoma risk, warning signs, and SSEs.

Participants in the control group received only the melanoma education brochure, a common form of patient education distributed in dermatology clinics. The control group did not receive telecommunication reminders, Skinsafe tutorial, or hands-on SSE tutorial.

MAIN OUTCOME MEASURES

On enrollment, each participant completed a baseline questionnaire (eFigure 1) that collected demographic data, assessed participants' current performance of SSEs, their confidence in indentifying melanoma, self-perceived risk for melanoma, use of sunscreen, use of sun protective clothing, and knowledge of the ABCDs of melanoma. Other data collected from the baseline questionnaire were used to allocate participants into a high-risk group or low-risk group for developing melanoma to ensure that similar numbers of participants in the control and treatment groups were at high risk for melanoma. Allocation into the high-risk group was based on participant report of at least 1 of the following: a personal history of MM, a personal history of nonmelanoma skin cancer, a first-degree relative with history of MM, and/or 2 or more independent risk factors for melanoma: red or blonde hair, a personal history of blistering sunburns as a child, a personal history of “atypical” or “dysplastic” mole, more than 100 moles, green or blue eyes, or a history of burning instead of tanning after sun exposure.2732 Those who did not meet these criteria of high risk were placed in the low-risk group. All participants were contacted for follow-up phone surveys to collect information on self-reported behavior 3 months after enrollment (eFigure 2). Every effort was made to collect follow-up data, as participants were called a minimum of 5 times before they were removed from the final analysis because follow-up data could not be collected. If the participant was not contacted, a message was left when possible with the principal investigator's contact information so that participant could contact the study team to complete the follow-up questionnaire.

STATISTICAL ANALYSIS

The target sample size was 200 participants. With equal numbers in the treatment and control groups, a total of 200 individuals is needed to achieve at least 80% power, at a .05 level of significance, to observe a standardized effect size of 0.4.

A logistic regression was used to analyze the data because it is nonparametric and the distribution of our data set was not normal. We constructed 2 models to evaluate the effectiveness of our intervention on the outcomes of interest, controlling for sex, age, race, education, and family history to adjust for variations between the groups.

CHARACTERISTICS OF PARTICIPANTS

A total of 390 clinic visitors were offered study participation (Figure 1); 112 participants were randomized to the control group, of whom 14 did not complete the survey, and 115 were randomized to the intervention group, of whom 3 did not complete the survey. Enrollment was completed for 98 in the control group and 112 in the intervention group. The overall response rate for the 3-month follow-up was 62.9% (132 of 210). There was no significant difference in response rate in the intervention and control groups (P = .77). At baseline, participants in the control and intervention groups were similar in terms of sex, age, race, and education level (Table 1).

Place holder to copy figure label and caption
Graphic Jump Location

Figure 1. Flowchart illustrating progression of participants through the trial.

Table Graphic Jump LocationTable 1. Demographics of Study Population
TELECOMMUNICATION REMINDER SELECTION

Most individuals in the intervention group selected to receive e-mail telecommunication reminders (50%). Of the remaining participants in the intervention group, 18% selected letters, 17% selected phone calls, and 15% selected text messages.

PERFORMANCE OF SSEs

At baseline, 43.3% reported performing SSEs (Table 2). At the 3-month follow-up, a greater percentage in the intervention group reported performing SSEs, compared with the control group (78.9% vs 60.7%; P ≤ .05) (Figure 2). Those in the intervention group were 2.36 times more likely to do SSEs at the end of the study (P ≤ .05) (Table 3). The subgroup that received text message reminders had greatest improvement in performance in SSEs from 31.3% at baseline to 76.9% at follow-up (Table 4).

Place holder to copy figure label and caption
Graphic Jump Location

Figure 2. Reported performance of self-skin examinations (SSEs) by participants in the control and intervention groups at the baseline and the 3-month follow-up. δ Indicates change.

Table Graphic Jump LocationTable 3. Logistic Regression Follow-up Assessment
Table Graphic Jump LocationTable 4. Reminder Type and Performance of SSEs in the Intervention Group
RISK ASSESSMENT FOR DEVELOPING MELANOMA

Prior to the intervention, approximately one-third (34.5%) of participants in the intervention group perceived their risk for melanoma to be “higher than average,” another third in this cohort perceived their risk to be “average,” and the remaining third perceived their risk to be “less than average” (Figure 3). At the time of enrollment, the Skinsafe program calculated the risk for these same participants based on responses to 10 standardized questions (addressing history of sun exposure and blistering sunburns, family history, skin type, etc) and found that 56.7% were at a higher than average risk for melanoma, 37.1% had an average risk, and only 6.2% had a less than average risk. At the 3-month follow-up, 47% of participants reported perceiving their risk for melanoma to be higher than average, 30% reported their perceived risk to be average, and 22% reported less than average perceived risk. Of the patients who reported performing SSEs at the end of the study, 47% of those perceived their risk for melanoma to be higher than average, and only 18% perceived their risk to be less than average.

Place holder to copy figure label and caption
Graphic Jump Location

Figure 3. Risk assessment for melanoma as perceived by participants in the intervention group compared with the risk calculated by the Skinsafe software program.

CONFIDENCE IN IDENTIFYING MELANOMA DURING AN SSE

At baseline, more individuals in the intervention group reported being “not very confident” or “not at all confident” in their ability to identify melanoma compared with the control group (44.6% vs 20.4%; P < .001). At the 3-month follow-up, more in the control group reported being not very confident or not at all confident about their ability to identify melanoma compared with the intervention group (32.8% vs 14%; P = .01). In addition, those in the intervention group were 2.72 times more likely to feel “very confident” or “somewhat confident” in their ability to identify melanoma during an SSE at the end of the study (Table 3). Age was inversely correlated with confidence in ability to identify melanoma (odds ratio [OR], 0.97; P ≤ .05) (Table 3).

The combination of CAL Skinsafe education, hands-on SSE tutorial, and telecommunication reminders was successful at increasing the performance of SSEs. We hypothesize that this is due to the complex interplay of psychosocial factors involved in modifying patient behavior. Patients often exhibit distinctive learning styles that may be restricted to visual, aural, reading/writing, kinesthetic styles, or a multimodal combination of these patterns.33 As such, each patient possesses a unique learning fingerprint that is most likely to be accessed through multiple and often diverse mechanisms. A unique aspect of our intervention involved kinesthetic teaching, which gives the patient an opportunity to gain “hands-on” experience that builds confidence, an important motivator in performing health protective behavior. This has been used successfully for patients with diabetes mellitus who must perform precise health protective behaviors to control their disease.33,34

Glazebrook et al19 studied the efficacy of Skinsafe software to educate high-risk patients in a primary care setting and found that those who participated in the intervention were 1.67 times more likely to perform SSEs or “mole checks” after the intervention. In our study, those in the intervention group were 2.36 times more likely to perform SSEs after the intervention. We hypothesize that our greater success rate is due to the multimodal approach used in our intervention, whereas the previous work conducted by Glazebrook et al19 used only the Skinsafe program. Furthermore, we hypothesize that our greater success may be partial attributable to setting—the participants in our study were recruited at dermatology outpatient clinics and may have ben more interested in sun protective behavior and SSEs than patients recruited from primary care offices. The success of multiple interventions is well established in trials of smoking cessation and coronary risk minimization that routinely demonstrate higher efficacy for patients receiving multimodal interventions.3537

Notable increases in the performance of SSEs were observed in the subset of participants in the intervention group that elected to receive text message telecommunication reminders. In recent studies, text message reminders linked to local weather information were used successfully to increase the use of sunscreen in patients presenting to the dermatology clinic.38 We hypothesize that telecommunication reminders, such as text message and e-mail, are more closely associated with behavior modification because of greater personalization. In our study participants were able to select a day and time that would be most convenient to receive the reminder, which likely made our reminders most effective. In addition, these methods of contact are usually directed specifically at the participant, whereas it is more difficult to ensure that letters and phone calls reach the intended recipient.

As demonstrated in a prior study, the participants in our study tended to underestimate their risk for developing MM prior to the intervention.19 Those in our intervention group were given a “computer-calculated” risk—and most perceived their risk to be lower than what was calculated by the software program, despite reporting well-known risk factors, such as history of melanoma in a first-degree relative or a personal history of atypical or dysplastic moles. At the end of the study, more participants reported perceiving their risk for melanoma to be higher than average, which is more consistent with the computer-generated risk assessment. Yet, 22% perceived their risk to be less than average, despite having received a computer-generated risk profile during the intervention on the day of enrollment, which indicated that only 6.2% of this population had a less than average risk. These data suggest that informing patients that they are at a greater risk for melanoma does not always change self-perceived risk. Of note, only 18% of participants who perceived their risk to be less than average reported performing SSEs at the end of the study, a rate that is well below the baseline performance of SSEs—perhaps an indication that perceived risk is a motivator for adapting new behaviors.

Improved self-reported confidence in ability to identify melanoma was observed in the intervention group. We hypothesize that the tutorial within the Skinsafe program that allows participants to identify suspicious lesions in a “quiz format” was helpful in raising confidence. In addition, because more participants in the intervention group reported performing SSEs, confidence may have increased as individuals became more acclimatized to closely examining their skin. Of note, our logistic regression suggested that age is inversely correlated with confidence in an ability to identify melanoma, which suggests that perhaps additional interventions are needed to improve confidence in self-detection in elderly populations. There are a variety of mechanisms that could account for this finding, and we hypothesize that perhaps older patients may have more benign skin changes (seborrheic keratosis and pigmented macules) appearing at a faster rate and therefore may have greater difficulty keeping track of changes. Furthermore, older patients may have comorbidities, such as impaired vision, that could compromise their ability to detect subtle changes in color or border pattern.

There are several limitations to this analysis. For example, neither the researchers nor the participants were blinded in this study. The slightly lower recruitment and follow-up rates in the control group may be a source of selection bias. However, the control and intervention groups were well matched at enrollment, and there were fair response rates in both groups. A further limitation was that change in performance in SSEs and all other variables measured in our analysis relied entirely on self-reported behavior, and it was not possible to reach all of the participants for follow-up data at the end of the study period. Every effort was made to contact all the participants via a minimum of 5 phone calls, and consequently, most participants (62.9%) provided follow-up data. Because nearly half of the participants in our analysis held a college or advanced degree, it is not clear if our findings could be generalized by the level of education In our analysis, all of the participants followed in the intervention group received all 3 aspects of the intervention (CAL, SSE tutorial, and telecommunication reminder), but it is not clear if our findings are attributable to synergism or if 1 modality was primarily responsible for the changes we observed. Future research could be aimed at determining the efficacy of other combinations of multimodal interventions that can modify patient behavior.

Dermatologists may use these findings to implement multiple modalities for teaching and reminding patients to perform SSE to increase patient autonomy and ultimately reduce the morbidity and mortality of MM.

Correspondence: Jeremy S. Bordeaux, MD, MPH, Department of Dermatology, University Hospitals Case Medical Center, Case Western Reserve University, 11100 Euclid Ave, 3500 Lakeside, Cleveland, OH 44106 (jeremy.bordeaux@uhhospital.org).

Accepted for Publication: May 24, 2012.

Published Online: August 20, 2012. doi:10.1001/archdermatol.2012.2480

Author Contributions: Drs Aneja and Brimhall contributed equally to this study. Drs Aneja, Brimhall, Kast, Carlson, Cooper, and Bordeaux had full access to all of 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: Brimhall, Cooper, and Bordeaux. Acquisition of data: Savina Aneja, Brimhall, Kast, and Carlson. Analysis and interpretation of data: Savina Aneja, Brimhall, Kast, Sanjay Aneja, Cooper, and Bordeaux. Drafting of the manuscript: Savina Aneja, Brimhall, and Kast. Critical revision of the manuscript for important intellectual content: Savina Aneja, Brimhall, Kast, Sanjay Aneja, Carlson, Cooper, and Bordeaux. Statistical analysis: Savina Aneja and Sanjay Aneja. Obtained funding: Cooper. Administrative, technical, and material support: Savina Aneja, Brimhall, Kast, Cooper, and Bordeaux. Study supervision: Cooper and Bordeaux.

Financial Disclosure: None reported.

Funding/Support: This study was made possible by the Case Western Reserve University Skin Diseases Research Center grant No. P30AR039750 from National Institute of Arthritis and Musculoskeletal and Skin Diseases. In addition, Dr Bordeaux is supported by the Dermatology Foundation Clinical Career Development Award in Dermatologic Surgery.

Additional Information: This is study case No.1610. The trial protocol is available through Case Western Reserve Cancer Center institutional review board office

 Cancer Statistics Review SEER, 1975-2006. Bethesda, MD: National Cancer Institute. http://seer.cancer.gov/statfacts/html/melan.html. Based on November 2008 SEER data submission, posted to the SEER web site, 2009. Accessed July 30, 2012
Herlyn M, Clark WH, Rodeck U, Mancianti ML, Jambrosic J, Koprowski H. Biology of tumor progression in human melanocytes.  Lab Invest. 1987;56(5):461-474
PubMed
Balch CM, Gershenwald JE, Soong SJ,  et al.  Final version of 2009 AJCC melanoma staging and classification.  J Clin Oncol. 2009;27(36):6199-6206
PubMed   |  Link to Article
Lens MB, Dawes M. Global perspectives of contemporary epidemiological trends of cutaneous malignant melanoma.  Br J Dermatol. 2004;150(2):179-185
PubMed   |  Link to Article
Brady MS, Oliveria SA, Christos PJ,  et al.  Patterns of detection in patients with cutaneous melanoma.  Cancer. 2000;89(2):342-347
PubMed   |  Link to Article
Francken AB, Shaw HM, Accortt NA, Soong SJ, Hoekstra HJ, Thompson JF. Detection of first relapse in cutaneous melanoma patients: implications for the formulation of evidence-based follow-up guidelines.  Ann Surg Oncol. 2007;14(6):1924-1933
PubMed   |  Link to Article
Francken AB, Bastiaannet E, Hoekstra HJ. Follow-up in patients with localised primary cutaneous melanoma.  Lancet Oncol. 2005;6(8):608-621
PubMed   |  Link to Article
Nieweg OE, Kroon BB. The conundrum of follow-up: should it be abandoned?  Surg Oncol Clin N Am. 2006;15(2):319-330
PubMed   |  Link to Article
Francken AB, Hoekstra HJ. Follow-up of melanoma patients: the need for evidence-based protocols.  Ann Surg Oncol. 2009;16(4):804-805
PubMed   |  Link to Article
Kiebert GM, Welvaart K, Kievit J. Psychological effects of routine follow up on cancer patients after surgery.  Eur J Surg. 1993;159(11-12):601-607
PubMed
Krige JE, Isaacs S, Hudson DA, King HS, Strover RM, Johnson CA. Delay in the diagnosis of cutaneous malignant melanoma: a prospective study in 250 patients.  Cancer. 1991;68(9):2064-2068
PubMed   |  Link to Article
Schmid-Wendtner MH, Baumert J, Stange J, Volkenandt M. Delay in the diagnosis of cutaneous melanoma: an analysis of 233 patients.  Melanoma Res. 2002;12(4):389-394
PubMed   |  Link to Article
Berwick M, Begg CB, Fine JA, Roush GC, Barnhill RL. Screening for cutaneous melanoma by skin self-examination.  J Natl Cancer Inst. 1996;88(1):17-23
PubMed   |  Link to Article
Carli P, De Giorgi V, Palli D,  et al; Italian Multidisciplinary Group on Melanoma.  Dermatologist detection and skin self-examination are associated with thinner melanomas: results from a survey of the Italian Multidisciplinary Group on Melanoma.  Arch Dermatol. 2003;139(5):607-612
PubMed   |  Link to Article
Hamidi R, Cockburn MG, Peng DH. Prevalence and predictors of skin self-examination: prospects for melanoma prevention and early detection.  Int J Dermatol. 2008;47(10):993-1003
PubMed   |  Link to Article
Champion VL, Springston JK, Zollinger TW,  et al.  Comparison of three interventions to increase mammography screening in low income African American women.  Cancer Detect Prev. 2006;30(6):535-544
PubMed   |  Link to Article
Dabney MK, Huelsman K.University of Wisconsin–Madison, Department of Medicine and the Program in Medical Ethics.  Counseling by computer: breast cancer risk and genetic testing.  Genet Test. 2000;4(1):43-44
PubMed   |  Link to Article
Coffman JM, Cabana MD, Halpin HA, Yelin EH. Effects of asthma education on children's use of acute care services: a meta-analysis.  Pediatrics. 2008;121(3):575-586
PubMed   |  Link to Article
Glazebrook C, Garrud P, Avery A, Coupland C, Williams H. Impact of a multimedia intervention “Skinsafe” on patients' knowledge and protective behaviors.  Prev Med. 2006;42(6):449-454
PubMed   |  Link to Article
Buller MK, Kane IL, Martin RC,  et al.  Randomized trial evaluating computer-based sun safety education for children in elementary school.  J Cancer Educ. 2008;23(2):74-79
PubMed   |  Link to Article
Faridi Z, Liberti L, Shuval K, Northrup V, Ali A, Katz DL. Evaluating the impact of mobile telephone technology on type 2 diabetic patients' self-management: the NICHE Pilot Study.  J Eval Clin Pract. 2008;14(3):465-469
PubMed   |  Link to Article
Khokhar A. Short text messages (SMS) as a reminder system for making working women from Delhi Breast Aware.  Asian Pac J Cancer Prev. 2009;10(2):319-322
PubMed
McClellan CB, Schatz JC, Puffer E, Sanchez CE, Stancil MT, Roberts CW. Use of handheld wireless technology for a home-based sickle cell pain management protocol.  J Pediatr Psychol. 2009;34(5):564-573
PubMed   |  Link to Article
Patrick K, Raab F, Adams MA,  et al.  A text message-based intervention for weight loss: randomized controlled trial.  J Med Internet Res. 2009;11(1):e1
PubMed   |  Link to Article
Flocke SA, Stange KC. Direct observation and patient recall of health behavior advice.  Prev Med. 2004;38(3):343-349
PubMed   |  Link to Article
 Skin Cancer (patient education pamphlet published by the American Academy of Dermatology, 2010). https://www.aad.org/store/search/default.aspx?catid=5. Accessed July 30, 2012
Bain C, Colditz GA, Willett WC,  et al.  Self-reports of mole counts and cutaneous malignant melanoma in women: methodological issues and risk of disease.  Am J Epidemiol. 1988;127(4):703-712
PubMed
White E, Kirkpatrick CS, Lee JA. Case-control study of malignant melanoma in Washington State; I: constitutional factors and sun exposure.  Am J Epidemiol. 1994;139(9):857-868
PubMed
Bliss JM, Ford D, Swerdlow AJ,  et al; International Melanoma Analysis Group (IMAGE).  Risk of cutaneous melanoma associated with pigmentation characteristics and freckling: systematic overview of 10 case-control studies.  Int J Cancer. 1995;62(4):367-376
PubMed   |  Link to Article
Udayakumar D, Mahato B, Gabree M, Tsao H. Genetic determinants of cutaneous melanoma predisposition.  Semin Cutan Med Surg. 2010;29(3):190-195
PubMed   |  Link to Article
Garibyan L, Fisher DE. How sunlight causes melanoma.  Curr Oncol Rep. 2010;12(5):319-326
PubMed   |  Link to Article
Psaty EL, Scope A, Halpern AC, Marghoob AA. Defining the patient at high risk for melanoma.  Int J Dermatol. 2010;49(4):362-376
PubMed   |  Link to Article
Dinakar C, Adams C, Brimer A, Silva MD. Learning preferences of caregivers of asthmatic children.  J Asthma. 2005;42(8):683-687
PubMed   |  Link to Article
Wolpert H, Block J. Hands-on demonstration and discussion of new pump software/hardware.  Diabetes Technol Ther. 2005;7(5):840-844
PubMed   |  Link to Article
Stead LF, Bergson G, Lancaster T. Physician advice for smoking cessation [update of Cochrane Database Syst Rev. 2004;(4):CD000165].  Cochrane Database Syst Rev. 2008;(2):000165
PubMed
Welton NJ, Caldwell DM, Adamopoulos E, Vedhara K. Mixed treatment comparison meta-analysis of complex interventions: psychological interventions in coronary heart disease.  Am J Epidemiol. 2009;169(9):1158-1165
PubMed   |  Link to Article
Solomon DH, Hashimoto H, Daltroy L, Liang MH. Techniques to improve physicians' use of diagnostic tests: a new conceptual framework.  JAMA. 1998;280(23):2020-2027
PubMed   |  Link to Article
Armstrong AW, Watson AJ, Makredes M, Frangos JE, Kimball AB, Kvedar JC. Text-message reminders to improve sunscreen use: a randomized, controlled trial using electronic monitoring.  Arch Dermatol. 2009;145(11):1230-1236
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Graphic Jump Location

Figure 2. Reported performance of self-skin examinations (SSEs) by participants in the control and intervention groups at the baseline and the 3-month follow-up. δ Indicates change.

Place holder to copy figure label and caption
Graphic Jump Location

Figure 1. Flowchart illustrating progression of participants through the trial.

Place holder to copy figure label and caption
Graphic Jump Location

Figure 3. Risk assessment for melanoma as perceived by participants in the intervention group compared with the risk calculated by the Skinsafe software program.

Tables

Table Graphic Jump LocationTable 1. Demographics of Study Population
Table Graphic Jump LocationTable 3. Logistic Regression Follow-up Assessment
Table Graphic Jump LocationTable 4. Reminder Type and Performance of SSEs in the Intervention Group

References

 Cancer Statistics Review SEER, 1975-2006. Bethesda, MD: National Cancer Institute. http://seer.cancer.gov/statfacts/html/melan.html. Based on November 2008 SEER data submission, posted to the SEER web site, 2009. Accessed July 30, 2012
Herlyn M, Clark WH, Rodeck U, Mancianti ML, Jambrosic J, Koprowski H. Biology of tumor progression in human melanocytes.  Lab Invest. 1987;56(5):461-474
PubMed
Balch CM, Gershenwald JE, Soong SJ,  et al.  Final version of 2009 AJCC melanoma staging and classification.  J Clin Oncol. 2009;27(36):6199-6206
PubMed   |  Link to Article
Lens MB, Dawes M. Global perspectives of contemporary epidemiological trends of cutaneous malignant melanoma.  Br J Dermatol. 2004;150(2):179-185
PubMed   |  Link to Article
Brady MS, Oliveria SA, Christos PJ,  et al.  Patterns of detection in patients with cutaneous melanoma.  Cancer. 2000;89(2):342-347
PubMed   |  Link to Article
Francken AB, Shaw HM, Accortt NA, Soong SJ, Hoekstra HJ, Thompson JF. Detection of first relapse in cutaneous melanoma patients: implications for the formulation of evidence-based follow-up guidelines.  Ann Surg Oncol. 2007;14(6):1924-1933
PubMed   |  Link to Article
Francken AB, Bastiaannet E, Hoekstra HJ. Follow-up in patients with localised primary cutaneous melanoma.  Lancet Oncol. 2005;6(8):608-621
PubMed   |  Link to Article
Nieweg OE, Kroon BB. The conundrum of follow-up: should it be abandoned?  Surg Oncol Clin N Am. 2006;15(2):319-330
PubMed   |  Link to Article
Francken AB, Hoekstra HJ. Follow-up of melanoma patients: the need for evidence-based protocols.  Ann Surg Oncol. 2009;16(4):804-805
PubMed   |  Link to Article
Kiebert GM, Welvaart K, Kievit J. Psychological effects of routine follow up on cancer patients after surgery.  Eur J Surg. 1993;159(11-12):601-607
PubMed
Krige JE, Isaacs S, Hudson DA, King HS, Strover RM, Johnson CA. Delay in the diagnosis of cutaneous malignant melanoma: a prospective study in 250 patients.  Cancer. 1991;68(9):2064-2068
PubMed   |  Link to Article
Schmid-Wendtner MH, Baumert J, Stange J, Volkenandt M. Delay in the diagnosis of cutaneous melanoma: an analysis of 233 patients.  Melanoma Res. 2002;12(4):389-394
PubMed   |  Link to Article
Berwick M, Begg CB, Fine JA, Roush GC, Barnhill RL. Screening for cutaneous melanoma by skin self-examination.  J Natl Cancer Inst. 1996;88(1):17-23
PubMed   |  Link to Article
Carli P, De Giorgi V, Palli D,  et al; Italian Multidisciplinary Group on Melanoma.  Dermatologist detection and skin self-examination are associated with thinner melanomas: results from a survey of the Italian Multidisciplinary Group on Melanoma.  Arch Dermatol. 2003;139(5):607-612
PubMed   |  Link to Article
Hamidi R, Cockburn MG, Peng DH. Prevalence and predictors of skin self-examination: prospects for melanoma prevention and early detection.  Int J Dermatol. 2008;47(10):993-1003
PubMed   |  Link to Article
Champion VL, Springston JK, Zollinger TW,  et al.  Comparison of three interventions to increase mammography screening in low income African American women.  Cancer Detect Prev. 2006;30(6):535-544
PubMed   |  Link to Article
Dabney MK, Huelsman K.University of Wisconsin–Madison, Department of Medicine and the Program in Medical Ethics.  Counseling by computer: breast cancer risk and genetic testing.  Genet Test. 2000;4(1):43-44
PubMed   |  Link to Article
Coffman JM, Cabana MD, Halpin HA, Yelin EH. Effects of asthma education on children's use of acute care services: a meta-analysis.  Pediatrics. 2008;121(3):575-586
PubMed   |  Link to Article
Glazebrook C, Garrud P, Avery A, Coupland C, Williams H. Impact of a multimedia intervention “Skinsafe” on patients' knowledge and protective behaviors.  Prev Med. 2006;42(6):449-454
PubMed   |  Link to Article
Buller MK, Kane IL, Martin RC,  et al.  Randomized trial evaluating computer-based sun safety education for children in elementary school.  J Cancer Educ. 2008;23(2):74-79
PubMed   |  Link to Article
Faridi Z, Liberti L, Shuval K, Northrup V, Ali A, Katz DL. Evaluating the impact of mobile telephone technology on type 2 diabetic patients' self-management: the NICHE Pilot Study.  J Eval Clin Pract. 2008;14(3):465-469
PubMed   |  Link to Article
Khokhar A. Short text messages (SMS) as a reminder system for making working women from Delhi Breast Aware.  Asian Pac J Cancer Prev. 2009;10(2):319-322
PubMed
McClellan CB, Schatz JC, Puffer E, Sanchez CE, Stancil MT, Roberts CW. Use of handheld wireless technology for a home-based sickle cell pain management protocol.  J Pediatr Psychol. 2009;34(5):564-573
PubMed   |  Link to Article
Patrick K, Raab F, Adams MA,  et al.  A text message-based intervention for weight loss: randomized controlled trial.  J Med Internet Res. 2009;11(1):e1
PubMed   |  Link to Article
Flocke SA, Stange KC. Direct observation and patient recall of health behavior advice.  Prev Med. 2004;38(3):343-349
PubMed   |  Link to Article
 Skin Cancer (patient education pamphlet published by the American Academy of Dermatology, 2010). https://www.aad.org/store/search/default.aspx?catid=5. Accessed July 30, 2012
Bain C, Colditz GA, Willett WC,  et al.  Self-reports of mole counts and cutaneous malignant melanoma in women: methodological issues and risk of disease.  Am J Epidemiol. 1988;127(4):703-712
PubMed
White E, Kirkpatrick CS, Lee JA. Case-control study of malignant melanoma in Washington State; I: constitutional factors and sun exposure.  Am J Epidemiol. 1994;139(9):857-868
PubMed
Bliss JM, Ford D, Swerdlow AJ,  et al; International Melanoma Analysis Group (IMAGE).  Risk of cutaneous melanoma associated with pigmentation characteristics and freckling: systematic overview of 10 case-control studies.  Int J Cancer. 1995;62(4):367-376
PubMed   |  Link to Article
Udayakumar D, Mahato B, Gabree M, Tsao H. Genetic determinants of cutaneous melanoma predisposition.  Semin Cutan Med Surg. 2010;29(3):190-195
PubMed   |  Link to Article
Garibyan L, Fisher DE. How sunlight causes melanoma.  Curr Oncol Rep. 2010;12(5):319-326
PubMed   |  Link to Article
Psaty EL, Scope A, Halpern AC, Marghoob AA. Defining the patient at high risk for melanoma.  Int J Dermatol. 2010;49(4):362-376
PubMed   |  Link to Article
Dinakar C, Adams C, Brimer A, Silva MD. Learning preferences of caregivers of asthmatic children.  J Asthma. 2005;42(8):683-687
PubMed   |  Link to Article
Wolpert H, Block J. Hands-on demonstration and discussion of new pump software/hardware.  Diabetes Technol Ther. 2005;7(5):840-844
PubMed   |  Link to Article
Stead LF, Bergson G, Lancaster T. Physician advice for smoking cessation [update of Cochrane Database Syst Rev. 2004;(4):CD000165].  Cochrane Database Syst Rev. 2008;(2):000165
PubMed
Welton NJ, Caldwell DM, Adamopoulos E, Vedhara K. Mixed treatment comparison meta-analysis of complex interventions: psychological interventions in coronary heart disease.  Am J Epidemiol. 2009;169(9):1158-1165
PubMed   |  Link to Article
Solomon DH, Hashimoto H, Daltroy L, Liang MH. Techniques to improve physicians' use of diagnostic tests: a new conceptual framework.  JAMA. 1998;280(23):2020-2027
PubMed   |  Link to Article
Armstrong AW, Watson AJ, Makredes M, Frangos JE, Kimball AB, Kvedar JC. Text-message reminders to improve sunscreen use: a randomized, controlled trial using electronic monitoring.  Arch Dermatol. 2009;145(11):1230-1236
PubMed   |  Link to Article

Correspondence

CME
Also Meets CME requirements for:
Browse CME for all U.S. States
Accreditation Information
The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
Note: You must get at least of the answers correct to pass this quiz.
Please click the checkbox indicating that you have read the full article in order to submit your answers.
Your answers have been saved for later.
You have not filled in all the answers to complete this quiz
The following questions were not answered:
Sorry, you have unsuccessfully completed this CME quiz with a score of
The following questions were not answered correctly:
Commitment to Change (optional):
Indicate what change(s) you will implement in your practice, if any, based on this CME course.
Your quiz results:
The filled radio buttons indicate your responses. The preferred responses are highlighted
For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
Indicate what changes(s) you will implement in your practice, if any, based on this CME course.

Multimedia

Supplemental Content

Examinations after intervention with interactive education and telecommunication reminders: a randomized controlled study. Arch Dermatol. doi:10.1001/archdermatol.2012.2480.

eFigure 1: Baseline questionnaire completed by the participants in the control and intervention groups at enrollment.

eFigure 2: Follow-up questionnaire completed during a phone interview 3 months after enrollment.

Supplemental Content

Some tools below are only available to our subscribers or users with an online account.

1,806 Views
8 Citations
×

Related Content

Customize your page view by dragging & repositioning the boxes below.

Articles Related By Topic
Related Collections
PubMed Articles
Jobs
JAMAevidence.com

The Rational Clinical Examination: Evidence-Based Clinical Diagnosis
Melanoma

The Rational Clinical Examination: Evidence-Based Clinical Diagnosis
Make the Diagnosis: Melanoma