Background: Skin cancer rates are increasing. Interventions to increase adolescent sunscreen use and skin self-examination (SSE) are required. Methods: Quasi-experimental design; 1 control and 4 intervention group schools in Scotland, UK. Participants were 15–16 year old students on the school register. The intervention was a theoretically-informed (Common-Sense Model and Health Action Process Approach) 50-min presentation, delivered by a skin cancer specialist nurse and young adult skin cancer survivor, to students in a classroom, supplemented by a home-based assignment. Outcome variables were sunscreen use intention, SSE intention/behaviour, planning, illness perceptions and skin cancer communication behaviour, measured 2 weeks pre- and 4 weeks post- intervention using self-completed pen and paper survey. School attendance records were used to record intervention up-take; students self-reported completion of the home-based assignment. Pearson’s chi-square test, analysis of variance, and non-parametric Wilcoxon Signed Ranks Test were used to measure outcomes and associations between variables. Focus groups elicited students’ (n = 29) views on the intervention. Qualitative data were analysed thematically. Results: Five of 37 invited schools participated. 639 (81%) students in intervention schools received the intervention; 33.8% completed the home-based assignment. 627 (69.6%) of students on the school register in intervention and control schools completed a questionnaire at baseline; data for 455 (72.6%) students were available at baseline and follow-up. Focus groups identified four themes – personal experiences of skin cancer, distaste for sunscreen, relevance of SSE in adolescence, and skin cancer conversations. Statistically significant (p <0.05) changes were observed for sunscreen use, SSE, planning, and talk about skin cancer in intervention schools but not the control. Significant associations were found between sunscreen use, planning and 2 illness perceptions (identity and consequence) and between SSE, planning and 3 illness perceptions (timeline, causes, control). Conclusions: It is feasible to promote sunscreen use and SSE in the context of an adolescent school-based psychoeducation intention. Further research is required to improve study uptake, intervention adherence and effectiveness. Trial registration: ISRCTN11141528 Keywords: Skin cancer, Skin self-examination, Adolescence * Correspondence: email@example.com School of Health, Social Care and Life Sciences, Centre for Health Sciences, University of the Highlands and Islands (UHI), Old Perth Road, Inverness IV2 3JH, Scotland Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Hubbard et al. BMC Public Health (2018) 18:666 Page 2 of 15 Background studies showed that shorter onset to melanoma diagno- Skin cancer prevention sis is associated with more favourable clinical outcomes The burden of skin cancer in Europe is high and in- . A landmark case-control study found that skin creasing rapidly . Skin cancer incidence has increased self-examination (SSE) may decrease mortality from in the United Kingdom (UK) by 360% since the 1970s melanoma by 63% , although there is lack of suffi- , with an estimated 86% of these cases attributable to cient evidence to know with certainty the effect of SSE excessive sunlight exposure . Sunburn is implicated in on melanoma incidence and stage at presentation . the pathogenesis of different skin cancers including Nonetheless, evidence suggests that over half of all mela- squamous cell carcinoma , basal cell carcinoma , nomas are self-detected [35–37]. Learning to conduct and melanoma . While rare, the recent rapid increase SSE during adolescence may increase the chances of this in skin cancer incidence in adolescence is attributed to important health behaviour becoming habitual  dur- environmental (e.g., excessive sun exposure leading to ing adulthood when skin cancer incidence is higher. One sunburn) and genetic factors [7–10]. Sunburn in child- study found that self-detection is associated with know- hood and adolescence heightens the risk of skin cancer ledge of the ABCD (asymmetry, border, colour, diam- in adulthood [6, 11–14]. For example, one United States eter) criteria used to examine moles and performance of cohort study found that the overall lifetime risk of devel- SSE . It is concerning, therefore, that a recent UK oping skin cancer nearly doubled (OR = 1.80 (95% CI, study found that less than half of adolescents recognized 1.42–2.28) if participants experienced five blistering ‘change in the appearance of existing or new mole’ as a sunburns between the ages 15 and 20 years . Sun melanoma warning sign  and another study found protection strategies (e.g., sunscreen use, covering up that SSE in young people is rare . Moreover, few with suitable clothing, avoiding going out in the sun) act young people talk about cancer ; yet, advice from by blocking or diminishing the contact of ultraviolet ra- family and friends is a trigger to seeking professional diation (UV) with the skin, thus, avoiding DNA damage advice about a symptom suggestive of cancer . and the development of skin cancer . A major con- cern is poor sunscreen application in this age group Behaviour change interventions [16–21]. In one study, adolescents were found to delib- Interventions that simultaneously promote sunscreen erately use a sunscreen with a low sun protection factor use to prevent skin cancer and SSE to improve early de- and delay application of sunscreen to get a tan . tection may be effective. A recent mobile phone text Hence, specific instructions on the correct application messaging intervention, targeting either sun protection and re-application of sunscreen and use of other sun or SSE in a population aged 18 to 42 years at high risk protection behaviours during adolescence are urgently of skin cancer, found that the SSE group improved their needed . There are other reasons why adolescents sun protection behaviours to a similar degree as that ob- are a target group for sun safety interventions. Multiple served in the sun protection group . It concluded risk behaviours – smoking, hazardous alcohol consump- that repeated messages about early detection of skin tion, low levels of physical activity, poor diet and exces- cancers and encouragement to conduct SSE prompt sive sun exposure – cluster in adolescence . Many people to consider skin cancer risk more broadly. health problems manifested in adulthood have anteced- A review of educational interventions published in ents in childhood [24–26]. Behaviours (e.g. sunbathing) 2004 concluded that simply raising awareness of the and attitudes (e.g. pro-tanning) associated with skin can- risks of UV radiation may go some way towards improv- cer emerge in adolescence and track into adulthood [27, ing sun protection behaviours during adolescence but is 28]. Adolescence therefore provides a critical window of unlikely to directly translate into sustained behaviour opportunity for the primary prevention of skin cancer change on its own . More recent studies have there- caused by sunburn across the life-course. fore focused on a range of behavioural determinants, acknowledging that individuals must be motivated to Early detection of melanoma perform specific behaviours (e.g., sunscreen use and There is no UK guidance for how often an individual SSE) and motivation must be directly translated into should examine their skin but there is a recognition to actual behaviours . make an appointment with a doctor if an individual no- Risk perceptions are social cognitions identified by tices a change to a mole, freckle or normal patch of skin many behavioural theories as primary motivators of a . The International Skin Cancer Foundation recom- range of health behaviours . Recent meta-analytic mends a head-to-toe self-examination every month . evidence suggests that interventions that successfully Early detection of melanoma improves survival, disease- engage and change risk perceptions produce subsequent and treatment-related morbidity and psychological improvements in health behaviours . This propos- adjustment [31, 32]. A recent systematic review of eight ition is supported by empirical evidence of associations Hubbard et al. BMC Public Health (2018) 18:666 Page 3 of 15 between risk perceptions and sun protection behaviours intervention (‘Do you know your skin?’)worked as in adolescents [18, 21, 48, 49] and SSE in adults [50, 51]. intended and that we would observe the following changes Illness representations are another class of social in outcomes from baseline to follow-up in adolescents’:i) cognitions that determine health behaviours and refer to sunscreen use intention and sunscreen use planning; ii) an individual’s beliefs and expectations about an illness SSE behaviour, SSE intention and SSE planning; iii) skin [52, 53]. Illness representations are central to the cancer perceptions; and iv) talk about skin cancer in inter- Common-Sense Model of illness representation and vention group schools but not the control group schools. self-regulation (CSM); a study in young adults found that CSM dimensions identity (e.g., ‘I have white or pale Methods skin’), cause (e.g., ‘Lots of sun exposure to skin without Design using sunscreen’) and timeline (e.g., ‘People of my age The feasibility study used a quasi-experimental design, are likely to develop skin cancer’) were associated with with four schools allocated by the research team to an higher SSE intentions . Expanded versions of CSM intervention group one to a control group, to find out if such as the Cognitive-Social Health Information the intervention worked as intended and examine trial Processing (C-SHIP) model include risk perceptions procedures. This was not a full randomised controlled . Illness perceptions (the term we use that includes trial; the study is not powered to measure effectiveness risk perceptions and illness representations) are and there was no aim to recruit a representative sample. multi-dimensional and in the context of this study in- clude adolescents’ beliefs about the causes of skin cancer Study population and recruitment and their perceived ability, confidence and relevance to The criteria for inclusion in the study were: males and control for skin cancer risk at their age. females aged 15–16 years of age. Participants were re- According to the Health Action Process Approach cruited from five secondary schools in Scotland. Four , behavioural intentions are more likely to be trans- schools were allocated to the intervention group and lated into action when people generate specific plans one to a control group (which received the intervention . In the context of sunscreen use, empirical evidence after the study). A letter was sent to 35 state and inde- suggests that adolescent frequent sunscreen users are pendent secondary school head teachers in one city in more likely to use action plans related to sunscreen use Scotland inviting participation, which was followed up (e.g., by planning to take sunscreen with them to use by telephone and/or email to arrange a face-to-face when at the pool or beach, during sports and when en- meeting to discuss the study and obtain agreement for gaging in outdoor activities) compared to infrequent the school’s participation. Due to poor response, two sunscreen users . Indeed, the study found that use of schools in a different area in Scotland, that were already action plans was the strongest predictor of sunscreen known to the research team through previous work, use . were invited to participate. Once a school had consented to participate, the named Study aims parent/carer on the school register was sent a study in- The intervention being tested in this feasibility study formation pack, which included a form to be returned to was designed to improve sun protection behaviours to the school if they wished to opt their child out of the prevent skin cancer and SSE to improve early detection study. The parent/carer was given the opportunity to of skin cancer. This feasibility study was for preparation contact the research team to discuss the study by of a future effectiveness trial of an intervention to in- telephone or email. Students who were not opted out by crease sunscreen use and SSE during adolescence and a parent/carer were given their study information sheet received ethical approval from the University of Stirling and consent form in the classroom. Students who had Research and Ethics committee (SREC 15/16 – Paper been opted out of the study were given education assign- No.66 – Version 2). The following trial parameters were ments to do while their classmates completed the measured to assess the feasibility of trial procedures: questionnaires. number of schools agreeing to participate, adolescent con- sent rate, and intervention adherence and acceptability. We hypothesised that we would observe at baseline asso- Intervention description ciations between: a) sunscreen use intention and sun- The intervention was developed by the research team screen use planning; b) SSE behaviour and SSE planning; with the support of an expert working group that c) SSE intention and SSE planning; d) SSE behaviour and included two people who had been treated for skin illness perceptions; e) SSE intention and illness percep- cancer, three experts in health behaviour change, one tions; f) sunscreen use intention and illness perceptions. A policy-maker in cancer early detection, one skin cancer further purpose was to determine if a psycho-educational specialist nurse and one dermatologist. The intervention Hubbard et al. BMC Public Health (2018) 18:666 Page 4 of 15 had two parts: a presentation delivered to students in Variables and measures school and a home-based assignment. Outcome variables were measured 2 weeks before (base- A practicing skin cancer nurse specialist delivered a line) and 4 weeks after (follow-up) the intervention in 50-min presentation to students about skin cancer and intervention schools using self-completed pen and paper SSE. Each presentation was delivered by the nurse on survey. Teachers administered the questionnaires in the one occasion during the school day in a classroom. After classroom. Parallel time-points were used in the control playing a 5-min video ‘Dear 16-year-old me’ (http:// school. Only students who had consented to participate in dcmf.ca), the nurse delivered the presentation with the the study completed questionnaires at these time-points. aid of Microsoft PowerPoint slides and covered: personal We adapted items from action and coping planning scales experiences of skin cancer, incidence patterns, risk fac-  to measure sunscreen planning and SSE planning. tors, associations between disease staging and survival, Items to measure illness perception were adapted and benefits of SSE. A young adult skin cancer survivor from a study about SSE in young adults , that in gave a brief 5-min talk after the nurse-delivered presen- turn had used items used in the Illness Perception tation. The talk was about his personal experience of Questionnaire . melanoma diagnosis at 16 years old, impacts on his life and his views on sunscreen use and SSE behaviour. Sunscreen use intention A home-based assignment comprised a booklet with Sunscreen use intention was measured using one item: instructions. Adolescents were given an exercise to ‘Do you intend to use a high factor sunscreen if you are self-examine their skin and asked to complete an action going out in the sun?’ A five-point continuous rating plan for regular monthly sunscreen use and an action scale was used to gauge response from 1 (definitely will plan for SSE. The SSE component of the booklet had not) to 5 (definitely will). We did not measure sunscreen three sections: a) information on the importance of use behaviour because the feasibility study was con- planning; b) instructions of what should be included in ducted in winter (January – March) and not during the the plan; c) formulating ‘if-then’ action plans (e.g., If I summer months when sunscreen use would be highly am having a shower then I will check my skin) and cop- relevant in Scotland. ing plans (e.g. To make sure I don’t forget, I will add the appointment to my calendar and put a reminder post-it Sunscreen use planning on the fridge). Sunscreen use planning was measured using five items: The school allocated to the control group, received the ‘I have made a detailed plan on… i) What sunscreen I same intervention after the study had ended. will use; ii) When I will use it; iii) Where I will get it from; iv) How I will remember to carry it’; and, iv) What Intervention adherence and acceptability to do if I am tempted not to use it.’ A five-point continu- We assessed intervention adherence and acceptability ous rating scale was used to gauge response from 1 both objectively and via self-report. Intervention adher- (completely disagree) to 5 (completely agree). ence was defined in two ways: proportion of eligible ado- lescents on a school register receiving the presentation, SSE behaviour and intention and number of participating adolescents completing the SSE behaviour was measured using one item: ‘In the past home-based assignment. The number of adolescents in month, have you examined your skin for signs of intervention schools who received the presentation was possible skin cancer?’ Responses were yes, no or don’t objectively measured using school attendance records. know. SSE intention was measured using one item: ‘Do The number of adolescents doing the home-based as- you intend to examine your skin for signs of possible signment was self-reported at follow- up. skin cancer on a regular basis.’ A five-point continuous Focus groups were conducted in intervention group rating scale was used to gauge response from 1 schools to explore adolescents’ opinions about rele- (definitely will not) to 5 (definitely will). vance, content, format and delivery methods. Focus groups (n = 3; 1 intervention group school was un- SSE planning available due to exam revision timetabling) to elicit ado- SSE planning was measured using four items: ‘I have lescents’ views on the intervention’s relevance, content, made a detailed plan regarding… i) When to examine format and delivery methods were conducted approxi- my skin for signs of possible skin cancer; ii) Where to mately 8 weeks after the intervention. Focus groups were examine my skin for signs of possible skin cancer; iii) audio-recorded and took place during school time, in a How to examine my skin for signs of possible skin can- classroom, at a time and place selected by the teacher and cer’; and, iv) ‘I have made a plan for dealing with things lasted approximately 50 min. Confidentiality was ex- that could stop me from examining my skin for signs of plained and informed consent was obtained in writing. possible skin cancer.’ A five-point continuous rating Hubbard et al. BMC Public Health (2018) 18:666 Page 5 of 15 scale was used to gauge response from 1 (completely using an open-ended question. We drew on the widely disagree) to 5 (completely agree). cited Dahlgren and Whitehead’s rainbow model of the main determinants of health as a framework to help Talking about skin cancer identify the broad range of factors that adolescents’ per- Talking about skin cancer was measured using one item: ceived to cause skin cancer. The open answers were cate- ‘Have you spoken to anyone about skin cancer in the last gorised into, 1) age, sex and constitutional factors (e.g., month?’ Responses were yes or no. age; genetics; moles; skin type; random mutation; family history; hereditary), 2) individual lifestyle factors (e.g. diet; Illness perceptions lack of sun protection; lack of skin examination; sunburn; Five dimensions of the CSM were measured using the lack of skincare; sunbeds; tanning beds; lack of hygiene; following items: tattoos), and 3) general environmental conditions (e.g. sun; sun exposure; radiation; UV light; pollution; heat). Identity: ‘How much would getting skin cancer affect Second, Pearson’s chi-square test was used to assess asso- your life?’ An eleven-point continuous rating scale was ciations between sunscreen use intention/SSE intention used to gauge response from 0 (not at all) to 10 and behaviour, and planning behaviour at baseline. Ana- (it would severely affect my life); lysis of Variance (ANOVA) was used to assess associations Control: ‘How much control do you feel you have to between SSE behaviour, intention and each of the 5 CSM prevent yourself from getting skin cancer? An dimensions at baseline. Third, to assess change in out- eleven-point continuous rating scale was used to come measures between baseline and follow-up the gauge response from 0 (not at all relevant) to 10 non-parametric Wilcoxon Signed Ranks Test was used be- (very relevant). cause data were not normally distributed. The test for sig- Timeline: ‘Given your age, how relevant is it to nificance was a within-group comparison (e.g. difference regularly examine your skin for signs of possible skin between baseline and follow-up scores within intervention cancer?’ An eleven-point continuous rating scale was group schools). The study was not designed or powered to used to gauge response from 0 (not at all relevant) to definitively measure effectiveness. However, to assess the 10 (very relevant). potential influence of confounders on results sensitivity Consequence: ‘How painful do you think the effects of analyses were conducted. There was no statistically signifi- treatments for skin cancer would be? An eleven-point cant difference between the intervention and control continuous rating scale was used to gauge response groups in terms of gender or having a close family mem- from 0 (not at all painful) to 10 (extremely painful). ber with cancer, but there was a statistically significant dif- ference of 1.2 years in the mean age of the two groups. The following open-ended question was used to meas- Repeated measures ANCOVA and logistic regression were ure the CSM dimension cause: ‘Please list in rank-order used to adjust for age in outcome analyses. Data were the three most important factors that you believe cause analysed using SPSS Statistics v21 (IBM Corporation, skin cancer. Armonk, NY). Significance tests were two-sided; p <0.05 was considered statistically significant. Social-demographic characteristics Audio-recorded qualitative data from focus groups Socio-demographic questions were included to gather were transcribed verbatim and analysed thematically data on sex and ethnicity. Using UK government statis- using the Framework approach . Qualitative findings tical service guidance , students were asked to provided contextual and explanatory understandings of choose from a list of 5 categories (White, Mixed, Asian adolescents’ experiences of the intervention. or Asian British, Black or black British, Chinese/other) which best describes their ethnic group. Results Sample characteristics Analyses No parent/carer opted their child out from the study Quantitative data analysis was conducted in three steps. and no student declined to participate in the study. First, descriptive statistics were calculated for sociode- According to school records, there were 901 eligible stu- mographic variables (i.e., age, gender) and outcome vari- dents. 627 (69.6%) completed a questionnaire at baseline. ables (e.g., sunscreen use intention and planning, SSE Student absence from school during examination revi- intention, behaviour and planning, skin cancer illness sion period explains why we did not achieve a 100% re- perceptions, and talking about cancer) at baseline and sponse rate. A CONSORT pilot and feasibility flowchart reported as n (%) for categorical data and mean (Standard is available in a Additional file 1. Deviation [SD]) for continuous data. As described above, The sample included 627 (female: 45.1%, n = 283) ado- one illness perception dimension – causes - was measured lescents with a mean age of 16.1 years (SD = 0.874); Hubbard et al. BMC Public Health (2018) 18:666 Page 6 of 15 88.0% (n = 552) were ‘White’ ethnic background; 10.7% sunscreen use. Adolescents could recall a key presenta- (n = 67) of adolescents had a close family member who tion message i.e., to regularly conduct SSE. Some adoles- had skin cancer. Complete data were available for 79 cents reported that they very quickly examined their (61%) and 376 (48%) adolescents in the control and skin after the presentation. Some adolescents did not do intervention schools respectively (i.e., we could pair the home-based assignment because in contrast to other baseline and follow-up for 455 students for analysis of homework tasks, there was no date when it had to be change in outcome measures). completed by. Nonetheless, even were the home-based assignment made compulsory, SSE is unlikely to be Intervention adherence sustained. This is because adolescents questioned the Eighty-three percent (n = 639) of adolescents in four relevance of SSE in adolescence. They understood from intervention group schools (n = 771) received the pres- the presentation that skin cancer prevalence was higher entation (85% n = 150; 75% n = 60; 78% n = 132; 87% n = in adulthood and therefore did not see the relevance of 297 in each school respectively). This is higher than the conducting SSE during adolescence. Making SSE habit- total number of students in all five schools completing ual by starting the behaviour during adolescence may baseline and/or follow-up questionnaires and indicative of therefore prove difficult to instigate. Some adolescents the difference in student absence from school on days reported that they mentioned very briefly to a parent/ when the intervention was delivered and questionnaires carer about the presentation that they had about skin administered in schools. 33.8% (n = 148) of adolescents in cancer. Others gave the impression that when they men- intervention schools reported that they did the tioned the presentation it provided the parent with an home-based assignment to conduct skin self-examination; opportunity to reinforce key messages about sun protec- 65.5% (n = 287) reported that they did not do the tion. Some adolescents reported that their parent/carer home-based assignment. looked at the home-based assignment booklet or they spoke about skin cancer with a parent/carer following Intervention acceptability the presentation. This suggests that school-delivered in- Focus group interviews in three intervention schools terventions with a home-based assignment component with 29 students (6, 10 and 13 participants in each may reach a wider audience (e.g., parents/carers) than school, respectively) were conducted. It was not feasible the direct target group (e.g., adolescents). to conduct a focus group in one intervention school due to timetabling constraints during the period when stu- dents were preparing for exams. The following key Baseline associations themes were identified – personal experiences of skin Sunscreen use intention, planning and risk perceptions cancer, distaste for sunscreen, relevance of SSE in ado- At baseline, 30.9% (n = 191) of adolescents definitely lescence and skin cancer conversations. Quotations to il- intended to use a high factor sunscreen if they were go- lustrate each theme are presented in a Additional file 2. ing out in the sun, and 5.3% (n = 33) definitely did not Two components of the presentation focused on per- intend to use a high factor sunscreen (Table 1). The sonal experiences of cancer: the ‘Dear 16 year old me’ difference between male and female intentions were sta- film that was shown at the beginning of the presentation tistically significant; more females definitely intended to and the brief talk from the young adult skin cancer sur- use sunscreen than males (37.5% (n = 105) versus 25.4% vivor at the very end of the presentation delivered by the (n = 86), p < 0.001) (Table 1). skin cancer specialist nurse. Adolescents could recall 14% (n = 87) of adolescents had made a detailed plan these personal stories because they were ‘real’, ‘emotional’ When to use sunscreen; 10.8% (n = 67) What sunscreen and they could ‘relate’. Many adolescents said that the to use; 16.7% (n = 104) Where to get sunscreen from; talk given by the young adult cancer survivor was the 8.8% (n = 55) How to get sunscreen (23.8%, n = 148); and best feature of the presentation. Nonetheless, some 8.7% (n = 54) had made a Coping plan for what to do if adolescents found the ‘Dear 16 year old me’ film too they were tempted not to use sunscreen (Table 2). contrived and ‘patronising’ because it was trying to be Adolescents who intended to use sunscreen had sta- too ‘cool’ and ‘down with the kids’. Adolescents could re- tistically significantly higher sunscreen planning be- call a key presentation message i.e., sunburn increases haviour for each of the five aspects of planning: the risk of skin cancer. Nonetheless, many adolescents When (p < 0.001); What (p < 0.001); Where (p < 0.001); expressed distaste for sunscreen because of its smell and How (p = 0.001); Coping (p = 0.001) (Table 3). For ex- texture (e.g. thickness, greasiness) and put them off ample, 86.2% (n = 150) of adolescents who intended using it. Thus, while the intervention appeared to to use sunscreen had made a plan When to use sun- improve awareness about the health risks of excessive screen compared to 40.5% (n = 121) who did not in- sun exposure, this may not be sufficient to increase tend to use sunscreen (Table 3). Hubbard et al. BMC Public Health (2018) 18:666 Page 7 of 15 Table 1 Sunscreen Use and Skin Self Examination (SSE) intention at baseline by gender Total Male Female Intention % n % n % n Sig. Sunscreen Use 1 - Definitely will not 5.3 (33) 6.8 (23) 3.6 (10) 0.001** 2 11.0 (68) 14.2 (48) 7.1 (20) 3 25.2 (156) 26.8 (91) 23.2 (65) 4 27.6 (171) 26.8 (96) 28.6 (80) 5 – Definitely will 30.9 (191) 25.4 (86) 37.5 (105) p<0.001*** SSE 1 - Definitely will not 13.3 (83) 17 (58) 8.8 (25) 0.041* 2 29.5 (184) 29.3 (100) 29.7 (84) 3 41.8 (261) 38.4 (131) 45.9 (130) 4 10.7 (67) 10.9 (37) 10.6 (67) 5 – Definitely will 4.6 (29) 4.4 (15) 4.9 (14) Have you spoken to anyone about skin Yes 9.2 (57) 8.2 (28) 10.4 (29) 0.363 cancer in the last month? No 90.8 (563) 91.8 (312) 89.6 (251) Note: *p < 0.05, **p < 0.01, ***p < 0.001 There were statistically significant associations be- No statistically significant gender differences were ob- tween sunscreen use intention and CSM dimensions served (Table 6). identity and consequences. Adolescents who intended to 4.6% (n = 29) of adolescents definitely intended to use sunscreen believed more strongly that skin cancer conduct SSE on a regular basis and 13.3% (n = 83) would affect their life compared to those who did not in- definitely did not intend to conduct SSE on a regular tend to use sunscreen (mean 8.33 versus 7.67, p < 0.001); basis (Table 1). The difference between male and fe- adolescents who believed more strongly that skin cancer male intentions were statistically significant; more would be painful compared to those who did not intend males definitely did not intend to conduct SSE than to use sunscreen (mean 7.26 versus 6.53, p = 0.002). No females (17% (n = 58) versus 8.8% (n =25), p = 0.041) statistically significant differences in sunscreen use in- (Table 1). tentions were observed for the CSM dimensions control, 1.1% (n = 7) of adolescents had made a detailed plan timeline (Table 4) and causes (Table 5). When to conduct SSE; 1.3% (n = 8) Where to conduct SSE; 1.3% (n = 8) How to conduct SSE; and 0.8% (n = 5) had made a Coping plan for dealing with things that SSE behaviour, intention, planning and risk perceptions could stop them from conducting SSE (Table 2). At baseline, 6.1% (n = 38) of adolescents reported that Adolescents who had conducted SSE in the past they had examined their skin for signs of possible cancer month or intended to conduct SSE on a regular basis in the past month and 90.1% (n = 563) had not (Table 5). had statistically significantly higher SSE planning Table 2 Sunscreen Use and Skin Self Examination (SSE) planning behaviour at baseline Planning behaviour When What Where How Coping Health Behaviour % (n)% (n)% (n)% (n)% (n) Sunscreen Use 1 – Completely disagree 23.3 (145) 28.5 (177) 30.5 (190) 34.6 (215) 39.8 (247) 2 15 (93) 19.8 (123) 18.8 (117) 20.7 (129) 19.8 (123) 3 23.5 (146) 23.8 (148) 17.4 (108) 20.9 (130) 19.8 (123) 4 24.3 (151) 17.2 (107) 16.6 (103) 15.0 (93) 11.8 (73) 5 – Completely agree 14.0 (87) 10.8 (67) 16.7 (104) 8.8 (55) 8.7 (54) Skin Self Examination 1 – Completely disagree 68.8 (431) –– 64.8 (403) 65.1 (404) 63.3 (395) 2 19.5 (122) –– 19.1 (119) 20.8 (129) 20.4 (127) 3 8.6 (54) –– 10 (62) 10.3 (64) 13.1 (82) 4 1.9 (12) –– 4.8 (30) 2.6 (16) 2.4 (15) 5 – Completely agree 1.1 (7) –– 1.3 (8) 1.3 (8) 0.8 (5) Hubbard et al. BMC Public Health (2018) 18:666 Page 8 of 15 Table 3 Associations between sunscreen use and SSE and planning behaviour at baseline Planning Behaviour (% Yes) When What Where How Coping Intention/behaviour % (n)% (n)% (n)% (n)% (n) Sunscreen Use Intention Yes 86.2 (150) 79.8 (190) 75.4 (156) 81.1 (120) 82.7 (105) Don’t know 62.2 (92) 54.8 (80) 61.1 (66) 66.9 (87) 68.3 (84) No 40.5 (121) 39.2 (93) 46.1 (141) 45.5 (156) 46.9 (173) Sig. < 0.001 < 0.001 < 0.001 0.001 0.001 SSE Intention Yes 9.4 (9) –– 11.6 (11) 11.7 (11) 9.4 (9) Don’t know 3.5 (9) –– 7.0 (18) 4.3 (11) 0.8 (2) No 0.4 (1) –– 3.4 (9) 0.4 (1) 3.5 (9) Sig. < 0.001 –– < 0.001 < 0.001 < 0.001 SSE behaviour Yes 10.5 (4) –– 16.2 (6) 22.2 (8) 13.2 (5) Don’t know 20.8 (5) –– 20.8 (5) 16.7 (4) 8.3 (2) No 1.8 (10) –– 4.8 (27) 2.1 (12) 2.3 (13) Sig. < 0.001 –– < 0.001 < 0.001 0.001 Table 4 Associations between SSE behaviour, intention and CSM attributes at baseline SSE/SSE Intention/sunscreen use intention Sig Yes Don’t know No CSM Attribute n Mean SD n Mean SD n Mean SD Skin Self Examination (SSE) Identity: How much skin cancer 38 7.66 2.122 561 8.13 1.888 24 8.13 2.071 0.375 would affect your life? Control: How much control you feel 38 6.39 2.047 562 5.65 2.256 24 5.13 2.659 0.128 you have to prevent skin cancer? Timeline: Given your age, how 38 6.42 2.332 557 5.13 2.241 24 4.92 2.749 0.008** relevant to conduct SSE? Consequences: How painful the 38 7.24 2.307 557 7.02 2.014 24 6.75 2.625 0.707 effects of skin cancer would be? SSE Intention Identity: How much skin cancer 96 8.56 1.514 261 8.12 1.759 265 7.93 2.104 0.078 would affect your life? Control: How much control you feel 96 6.00 2.088 261 5.98 2.057 265 5.24 2.433 < 0.001*** you have to prevent skin cancer? Timeline: Given your age, how 96 6.10 2.174 258 5.56 2.027 263 4.53 2.373 < 0.001*** relevant to conduct SSE? Consequences: How painful the 95 7.40 1.991 260 7.04 2.000 263 6.89 2.125 0.101 effects of skin cancer would be? Sunscreen Intention Identity: How much skin cancer 363 8.33 1.749 156 7.81 1.947 100 7.67 2.265 < 0.001*** would affect your life? Control: How much control you feel 363 5.80 2.129 157 5.60 2.287 100 5.36 2.607 0.190 you have to prevent skin cancer? Timeline: Given your age, how 359 5.29 2.214 156 5.19 2.246 100 4.95 2.560 0.412 relevant to conduct SSE? Consequences: How painful the 362 7.26 1.916 154 6.79 2.016 100 6.53 2.460 0.002** effects of skin cancer would be? Note: Aggregated from 5-point Likert scale where 1 = definitely will not and 5 = definitely will; 1–2 = No, 3 = Don’t know, 4,5 = Yes **p < 0.01, ***p < 0.001 Hubbard et al. BMC Public Health (2018) 18:666 Page 9 of 15 Table 5 Associations between CSM Causes (Age, Sex, Hereditary group but not for adolescents in the control group Factors) and SSE, intention and sunscreen intention at baseline (Table 7). For example, intention to use a high factor Yes Don’t know No Sig sunscreen significantly increased in the intervention group (mean 3.67 to 3.88, p < 0.001) but decreased in % n %(n)% (n) the control group (3.61 to 3.37, p = 0.015) (Table 7). Skin Self Examination (SSE) 9.8 19 5.2 10 85.1 165 0.006 However, after adjusting for age there were no statisti- SSE Intention 20.1 39 41.2 80 38.7 75 0.079 cally significant differences in sunscreen use intention Sunscreen Intention 61.7 119 25.9 50 12.4 24 0.187 and planning behaviour between baseline and follow-up in either the control or intervention groups (Table 7). behaviour for each of the four aspects of planning: When (p < 0.001); Where (p < 0.001); How (p = 0.001); SSE behaviour, intention and planning Coping (p = 0.001) (Table 3). For example, 10.5% (n =4) Comparisons between baseline and follow-up scores of adolescents who had conducted SSE in the past month show that proportionately more adolescents in the had made a plan when to conduct SSE compared to 1.8% intervention group changed their SSE behaviour for the (n = 10) who had not conducted SSE (Table 3). better compared with adolescents in the control group There were statistically significant associations be- (5.6 to 32.6%, p < 0.001 vs. 8.7 to 12.5%, p =0.337) (Table 7). tween SSE behaviour and CSM dimensions timeline and There was a statistically significant beneficial change cause. Adolescents who had conducted SSE in the past in intentions to regularly conduct SSE in the interven- month believed more strongly than those who had not tion group (mean 2.62 to 3.04, p < 0.001) between base- conducted SSE in the past month that it was relevant to line and follow-up whereas there was a statistically conduct SSE at their age (mean 6.42 vs. 4.92; p = 0.008) significant detrimental change in the control group (Table 4). 9.8% (n = 19) of adolescents who did SSE in (mean 2.71 to 2.49, p = 0.035) (Table 7). However, after the previous month associated skin cancer causes with adjusting for age no statistically significant differences in age, sex and constitutional factors and 4.3% (n = 17) who SSE intention between baseline and follow-up were ob- reported SSE in the previous month associated skin can- served in either the intervention (p = 0.051) or control cer causes with other factors (i.e. individual lifestyle fac- (p = 0.035) groups (Table 7). tors or general environmental conditions) (p = 0.006) Comparisons between baseline and follow-up scores (Table 5). show that there was a significant beneficial change in There were statistically significant associations be- SSE planning behaviour in the intervention group tween SSE intention and CSM dimensions timeline and whereas there were no significant changes in the control control. Adolescents who intended to conduct SSE on a group for planning when, where and how to conduct SSE regular basis believed more strongly than those who did (Table 6). For example, there was a significant beneficial not intend to conduct SSE that they had control to change in planning when to conduct SSE in the inter- prevent skin cancer (mean 6.00 vs. 5.24; p < 0.001) and vention group (mean 1.48 to 2.21, p < 0.001) and no that it was relevant to conduct SSE at their age (mean statistically significant change in the control group 6.10 vs. 4.53; p < 0.001). No significant differences were (mean 1.47 to 1.49, p = 0.3) (Table 6). There was a statis- observed for the CSM dimensions identity, consequences tically significant beneficial change in coping planning in (Table 4) and causes (Table 5). the intervention group (mean 1.65 to 2.37, p < 0.001) and in the control group (mean 1.48 to 1.76, p = 0.017) Indicative intervention outcomes (Table 7). After adjusting for age no statistically signifi- Sunscreen use intention and planning cant changes were observed for any of the four measures Comparisons between baseline and follow-up scores of SSE planning in the control group, and the only show that there were statistically significant beneficial measure that remained statistically significant in the changes in sunscreen use intention and sunscreen use intervention group was planning how to conduct SSE planning behaviour for adolescents in the intervention (p = 0.022) (Table 7). Table 6 Skin Self Examination (SSE) behaviour at baseline by Talk about skin cancer gender At baseline, 9.2% (n = 57) of adolescents reported that they had talked to someone in the past month about Total (n = 625) Male (n = 342) Female (n = 283) Sig. skin cancer (Table 1). No statistically significant gender %(n)% (n)% (n) differences were observed (Table 1). The number of ado- Yes 6.1 (38) 5.6 (19) 6.7 (19) 0.42 lescents talking about skin cancer in the last month that No 90.1 (563) 89.8 (307) 90.5 (256) received the intervention significantly increased after the Don’t Know 3.8 (24) 4.7 (16) 2.8 (8) intervention (9.2 to 53.5%, p < 0.001); no statistically Hubbard et al. BMC Public Health (2018) 18:666 Page 10 of 15 Table 7 Change in outcome measures between baseline and follow-up Control Intervention Baseline Follow-up Unadjusted Adjusted Baseline Follow-up Unadjusted Adjusted Outcome Measures Mean (SD) Mean (SD) n Sig Sig Mean (SD) Mean (SD) n Sig Sig Sunscreen Use Intention and Planning Behaviour Intention to use sunscreen 3.61 (1.203) 3.37 (1.341) 79 0.015* 0.388 3.67 (1.177) 3.88 (1.099) 360 < 0.001*** 0.186 Plan WHAT sunscreen intend 2.47 (1.440) 2.44 (1.366) 79 0.443 0.773 2.64 (1.353) 3.33 (1.268) 369 < 0.001*** 0.261 to use Plan WHEN to use sunscreen 2.52 (1.376) 2.44 (1.366) 79 0.533 0.803 3.01 (1.378) 3.33 (1.268) 369 < 0.001*** 0.817 Plan WHERE to get it 2.43 (1.420) 2.29 (1.360) 79 0.237 0.965 2.81 (1.479) 3.17 (1.358) 369 < 0.001*** 0.779 Plan HOW to get it 2.27 (1.288) 2.10 (1.257) 79 0.198 0.952 2.52 (1.365) 2.93 (1.259) 368 < 0.001*** 0.196 COPING Plan 2.11 (1.368) 2.04 (1.203) 79 0.513 0.479 2.32 (1.309) 2.91 (1.337) 366 < 0.001*** 0.915 Skin Self Examination Intention and Planning Behaviour Intention to examine skin for 2.71 (0.865) 2.49 (0.932) 79 0.035* 0.456 2.62 (0.976) 3.04 0.978 375 < 0.001*** 0.051 possible signs of skin cancer on a regular basis I have made a detailed plan 1.47 (0.875) 1.49 (0.799) 79 0.300 0.125 1.48 (0.842) 2.21 (1.103) 376 < 0.001*** 0.718 regarding WHEN I have made a detailed plan 1.56 (0.920) 1.56 (0.877) 78 0.991 0.569 1.61 (0.945) 2.62 (1.221) 374 < 0.001*** 0.192 regarding WHERE I have made a detailed plan 1.55 (0.935) 1.62 (0.901) 78 0.744 0.996 1.55 (0.858) 2.72 (1.213) 374 < 0.001*** 0.022* regarding HOW I have made a detailed plan 1.48 (0.830) 1.76 (0.950) 79 0.017* 0.672 1.65 (0.915) 2.37 (1.166) 372 < 0.001*** 0.426 for COPING Skin cancer risk representations Identity: How much skin 7.70 (2.084) 7.71 (2.316) 77 0.729 0.888 8.22 (1.806) 8.26 (1.943) 375 0.215 0.474 cancer would affect your life Control: How much control 5.29 (2.251) 5.05 (2.197) 78 0.834 0.990 5.90 (2.254) 6.62 (1.893) 376 < 0.001*** 0.029* you feel you have to prevent skin cancer Timeline: Given you age, how 4.81 (2.391) 4.59 (2.265) 78 0.767 0.104 5.23 (2.308) 7.14 (2.068) 372 < 0.001*** 0.873 relevant to conduct SSE Consequences: How painful 6.74 (2.002) 6.21 (2.223) 76 0.053 0.869 7.05 (2.036) 6.96 (2.200) 369 0.524 < 0.001*** the effects of skin cancer would be % (n) % (n) % (n) % (n) Skin Self Examination in past month + + + + (% Yes) 8.7 (8) 12.5 (13) 0.337( ) 0.599( ) 5.6 (30) 32.6 (143) < 0.001*** ( ) < 0.001*** ( ) (% No) 85.9 (79) 82.7 (86) 90.8 (486) 65.1 (286) (% Don’t know) 5.4 (5) 4.8 (5) 3.6 (19) 2.3 (10) Talk about skin cancer in the past month + + + + (% Yes) 8.7 (8) 14.6 (15) 0.866( ) 0.888( ) 9.2 (49) 53.5 (234) < 0.001***( ) < 0.001***( ) (% No) 91.3 (84) 85.4 (88) 90.8 (481) 46.5 (203) Note:*p < 0.05, ***p < 0.001 (+) p-values refer to the comparison between control and intervention for baseline and follow-up separately. Logistic regression model was applied to take into account confounder ‘Age’ significant increase was observed in the control school in CSM dimensions in the control group (Table 7). In (8.7 to 14.6%, p = 0.866) (Table 7). the intervention group, before adjusting for age, there were statistically significant changes in CSM dimensions Skin cancer risk representations control and timeline; adolescents in the intervention Comparisons between baseline and follow-up scores group believed more strongly that they had control to show that there were no statistically significant changes prevent skin cancer at follow-up than they did at Hubbard et al. BMC Public Health (2018) 18:666 Page 11 of 15 baseline (mean 5.90 versus 6.62, p < 0.001) and believed of the need for interventions to increase sunscreen use more strongly that it was relevant to conduct SSE at and SSE in this age group. The feasibility study was not their age (7.14 versus 5.23, p < 0.001) (Table 7). After designed to definitely measure effectiveness but rather to adjusting for age, changes in the CSM dimension control give an indication that the intervention worked as remained statistically significant (p = 0.029) and change intended. As hypothesised, the study suggests that the in the consequences measure was statistically significant intervention will facilitate beneficial changes in adolescent (p < 0.001) (Table 7). sunscreen use intention and SSE behaviour and intention, and adds to the body of work reporting the beneficial Discussion effects of psycho-educational interventions on sun protec- A key purpose of conducting this feasibility study was to tion behaviours in adolescents [48, 66–70]. There is, evaluate trial parameters. The response rate from however, only a very limited body of work about SSE in schools was low (only 5 out of 37 schools that were adolescents to which we can compare our findings. A approached agreed to participate) and reflects busy cur- study of Turkish teenagers (mean age 13 years) found sig- ricula timetables at the time of year when students aged nificant increases in intentions to conduct SSE following 15–16 years in the UK are studying for exams. Our can- an educational intervention ; however, the study did cer awareness intervention trials conducted with youn- not include a control group. The feasibility study high- ger adolescents who are not in an examination period lights that the use of personal stories is an important have experienced a much higher school response rate method for delivering crucial health messages. In this . Thus, the lead up to examination revision and ex- intervention, personal stories presented by video aminations should be avoided in future research with (‘Dear 16 year old me’) or in-person (young adult this age group. Nonetheless, no parent/carer opted their cancer survivor) were remembered by adolescents 8 weeks child from the study and no student declined to partici- after the intervention was delivered in schools. Our quali- pate, suggesting that it was an acceptable intervention. tative findings also suggest that a skin cancer presentation The proportion of students on the school register com- delivered in schools will provide further potential teach- pleting baseline and follow-up questionnaires was 50.5%, able moments between parents/carers and their child which we believe could be improved if the study was about sun protection. conducted outside of the examination revision period. Understanding the pathways through which behaviour The proportion of students in intervention schools re- change occurs is important during feasibility work; a key ceiving the intervention was high (81%) but only a third purpose of this feasibility study was to determine if the of students completed the home-based assignment. Our above observed intervention effects on sunscreen use findings suggest that the number of students completing intention and SSE behaviour/intention occurred through the home-based assignment could be improved if adoles- hypothesised pathways of theoretical mediation. To cents saw the relevance of SSE (a key part of the assign- evaluate this, we first examined associations between ment) for their age group. planning, illness perceptions and sunscreen use and SSE The onset of multiple risk behaviours, including exces- at baseline and second, we measured changes in plan- sive sun exposure, cluster in adolescence and there is a ning and illness perceptions from baseline to follow-up. recognised need to determine the effectiveness of inter- As hypothesised, at baseline, we found significant associa- ventions to address this problem . Hence, a further tions between planning and sunscreen use intention, SSE purpose of the feasibility study was to determine if the behaviour and SSE intention. Other studies have also intervention worked as intended. The study shows that reported associations between planning and sunscreen use at baseline, 58.5% of adolescents intended to use a high in adolescents  and adults  and between planning factor sunscreen if they were going out in the sun and and SSE . A mobile text messaging-delivered behav- that female adolescents had a greater intention to use ioural intervention in a population aged 18 to 42 years sunscreen than males. This finding is similar to other found that those who had made plans to check their skin studies conducted in the UK [16, 63]and elsewhere for early signs of skin cancer were more likely to conduct [17, 64–66]. The number of adolescents who reported SSE . There is therefore a growing body of empirical that they had conducted SSE was low (6.1%) and only evidence to corroborate theoretical models suggesting that 15.3% intended to examine their skin on a regular basis. behavioural intentions are more likely to be translated into This is similar to a figure of 4% of 16 to 25 year olds re- action when people generate specific plans [45, 56]and ported by a survey conducted in Northern Ireland . points to the inclusion of planning activities in interven- We found females had a greater intention to conduct SSE tions to increase sunscreen use and SSE in adolescents. on a regular basis than males. Other studies have also We also, as hypothesised, observed significant associations found that SSE is associated with being female . Taken at baseline between illness perceptions (including risk per- together, this body of work provides convincing evidence ception) and sunscreen use intention and SSE behaviour/ Hubbard et al. BMC Public Health (2018) 18:666 Page 12 of 15 intention. Hence, our study findings are consistent with increasing sunscreen use. Further research should there- other research showing associations between risk percep- fore consider objective measurement of sunscreen use and tions and sunscreen use in adolescents [18, 21, 48, 49, 73] sunburn incidence. Similarly, any study that relies on and between the CSM dimension timeline and SSE in self-reported SSE is subject to recall bias, and may lead to young adults  and are consistent with the thesis that the overestimation of SSE behaviour. Increasing use of risk perceptions influence behaviour . We can only mobile photo-documentation means that future studies speculate reasons why we did not consistently find associ- may be in a position to include objective measurement of ations between all five CSM dimensions and sunscreen SSE [75, 76]. We did not ask participants whether they ex- and SSE behaviour/intention. It could be that some illness amined their whole body during SSE, only arms and legs, perceptions are more influential than others and vary by and how SSE is measured can yield different results . behaviours. However, a more likely explanation is that our Fourth, as mentioned previously, risk perception was only findings are an artefact of study design; perhaps it is not operationalised using CSM and other behaviour theories surprising that we did not observe an association between could strengthen the intervention. This is because there relevance beliefs (i.e. measured in this study by the CSM are other social cognitions that may influence behaviour dimension timeline) and sunscreen use intention because and should therefore be considered in future studies. For we only included one item and that item related specific- example, outcome expectancy (a belief about the likeli- ally to adolescents’ perceived relevance of SSE during hood of the behaviour leading to a specific outcome) has adolescence and we did not measure their perceived rele- been associated with sun protection and SSE and vance of using sunscreen during adolescence. Importantly, appearance motives have been associated with sunscreen we only operationalised illness perceptions using CSM di- use intention in adolescents . Fifth, while promising, mensions of illness representation. It has been suggested our study suggests that this brief intervention on its own that different risk perception operationalisations explain has limitations. Our qualitative findings suggest that ado- the inconsistent findings in literature regarding the rela- lescents may defer using sunscreen because they do not tionship between risk perceptions and cancer-related like its texture or smell. Whether the intervention mes- behaviours . Hence, future studies should consider sages about sun protection are sufficiently powerful to operationalising illness perceptions using a range of overcome these barriers in the long-term is unclear from behaviour change theories and theoretical constructs. this study. Adolescents also questioned the relevancy of SSE during adolescence. While they understood and Limitations retained the message that sunburn in childhood and ado- Our study provides new evidence regarding interven- lescence increases their chances of skin cancer, they also tions that simultaneously address sunscreen use to pre- understood and retained the message that the negative ef- vent skin cancer and SSE to improve early detection that fects on health are likely only to be apparent many years was previously lacking internationally. However, several later. Making SSE habitual by beginning in adolescence limitations of the study must be noted. First, the sample may therefore prove challenging. We may need to develop consists of a small number of mainly white British ‘Do you know your skin?’ by increasing intervention inten- adolescents selected from only five schools and so may sity, the relevance of SSE during adolescence, and consider not generalise to populations with different cultural combining it with other interventions (e.g. increasing avail- backgrounds. Second, the study was conducted during ability of adolescent-friendly sunscreen) as part of a larger January to March when it is cold in the UK and when programme of effort to promote sunscreen use and SSE. the population is less likely to think about use of sun protection. Whether the findings would be similar dur- Conclusion ing the summer months is unclear but given that we This study suggests that it is feasible to simultaneously found the intervention appeared to influence sunscreen promote sun safe behaviours and skin self-examination use and SSE when the population is possibly less recep- using a theory-based psycho-educational intervention tive to sun safe messaging we are confident that this but further research is required to improve study uptake, would be the case. Third, the study relied on self-report intervention adherence and effectiveness. and is therefore prone to social desirability reporting biases. In this study, we did not measure actual Additional files sunscreen use (we only measured intention) nor did we examine associations between sunscreen use and sunburn Additional file 1: CONSORT flowchart for trials. Number of participants screened, enrolled, allocated to intervention or control arms, and follow incidence. If sunscreen use does not lead to a reduction in up and assessment rates. (DOCX 64 kb) sunburn then even if an intervention were to improve Additional file 2: Qualitative data from the focus groups. Table with sunscreen use it would not necessarily improve health thematic headings and related quotations from participants. (DOCX 102 kb) outcomes unless sunburn declined as a consequence of Hubbard et al. BMC Public Health (2018) 18:666 Page 13 of 15 Abbreviations 7. Alston RD, Rowan S, Eden TOB, Moran A, Birch JM. Cancer incidence CSM: Common-sense model of illness representation; SSE: Skin self-examination patterns by region and socioeconomic deprivation in teenagers and young adults in England. Brit J Cancer. 2007;96(11):1760–6. Acknowledgements 8. Mitsis DKL, Groman A, Beaupin LM, Salerno KE, Francescutti V, Skitzki JJ, We thank Sheena Dryden, skin cancer specialist nurse and Jack Brodie, Kane JM, Khushalani NI. Trends in demographics, incidence, and survival in young adult skin cancer survivor who delivered the intervention. We also children, adolescents and young adults (AYA) with melanoma: A thank students and teachers who participated in the study. Surveillance, Epidemiology and End Results (SEER) population-based analysis. J Clin Oncol. 2015;33(15):9058. Funding 9. Deady S, Sharp L, Comber H. Increasing skin cancer incidence in young, This work was supported by the UK charity Melanoma Focus. affluent, urban populations: a challenge for prevention. Brit J Dermatol. 2014;171(2):324–31. Availability of data and materials 10. Youl P, Aitken J, Hayward N, Hogg D, Liu L, Lassam N, Martin N, Green A: The datasets used and/or analysed during the current study are available Melanoma in adolescents: a case-control study of risk factors in Queensland, from the corresponding author on reasonable request. Australia Int J Cancer 2002, 98(1):92–98. 11. Oliveria SA, Saraiya M, Geller AC, Heneghan MK, Jorgensen C. Sun exposure Authors’ contributions and risk of melanoma. Arch Dis Child. 2006;91(2):131–8. GH, SD, RK, RN, designed the study; GH led the study and prepared first draft 12. Iannacone MR, Wang W, Stockwell HG, O'Rourke K, Giuliano AR, Sondak VK, of the manuscript; GH, ZW recruited schools, collected data and conducted Messina JL, Roetzheim RG, Cherpelis BS, Fenske NA, et al. Patterns and thematic analysis; VM conducted statistical analyses; all authors reviewed and timing of sunlight exposure and risk of basal cell and squamous cell agreed the final manuscript. carcinomas of the skin–a case-control study. BMC Cancer. 2012;12:417. 13. Vranova J, Arenbergerova M, Arenberger P, Stanek J, Vrana A, Zivcak J, Ethics approval and consent to participate Rosina J. Incidence of cutaneous malignant melanoma in the Czech The study was approved at University of Stirling Research and Ethics Republic: the risks of sun exposure for adolescents. Neoplasma. committee (SREC 15/16 – Paper No.66 – Version 2). The consent procedure 2012;59(3):316–25. was as follows: Once a school had consented to participate, the named 14. Wu SW, Han JL, Laden F, Qureshi AA. Long-term ultraviolet flux, other parent/carer on the school register was sent a study information pack, which potential risk factors, and skin Cancer risk: a cohort study. Cancer Epidem included a form to be returned to the school if they wished to opt their Biomar. 2014;23(6):1080–9. child out of the study. The parent/carer was given the opportunity to 15. Sanchez G, Nova J, Rodriguez-Hernandez AE, Medina RD, Solorzano- contact the research team to discuss the study by telephone or email. Restrepo C, Gonzalez J, Olmos M, Godfrey K, Arevalo-Rodriguez I. Sun Students who were not opted out by a parent/carer were given their study protection for preventing basal cell and squamous cell skin cancers. information sheet and consent form in the classroom. Students who had Cochrane Db Syst Rev. 2016;7. Art. No.: CD011161. https://doi.org/10.1002/ been opted out of the study were given education assignments to do while 14651858.CD011161.pub2. their classmates completed the questionnaires. 16. Kyle RG, Macmillan I, Forbat L, Neal RD, O'Carroll RE, Haw S, Hubbard G. Scottish adolescents' sun-related behaviours, tanning attitudes and Competing interests associations with skin cancer awareness: a cross-sectional study. The authors have no competing interests. BMJ Open. 2014;4(5):e005137. 17. Buendia Eisman A, Arias Santiago S, Moreno-Gimenez JC, Cabrera-Leon A, Prieto L, Castillejo I, Conejo-Mir J. An internet-based programme to promote Publisher’sNote adequate UV exposure behaviour in adolescents in Spain. J Eur Acad Springer Nature remains neutral with regard to jurisdictional claims in Dermatol Venereol. 2013;27(4):442–53. published maps and institutional affiliations. 18. de Vries H, Mesters I, van't Riet J, Willems K, Reubsaet A. Motives of Belgian adolescents for using sunscreen: the role of action plans. Cancer Epidem Author details 1 Biomar. 2006;15(7):1360–6. School of Health, Social Care and Life Sciences, Centre for Health Sciences, 19. Davis KJ, Cokkinides VE, Weinstock MA, O'Connell MC, Wingo PA. Summer University of the Highlands and Islands (UHI), Old Perth Road, Inverness IV2 2 sunburn and sun exposure among US youths ages 11 to 18: national 3JH, Scotland. School of Health and Social Care, Edinburgh Napier 3 prevalence and associated factors. Pediatrics. 2002;110(1 Pt 1):27–35. University, Sighthill Court, Edinburgh EH11 4BN, UK. Academic Unit of 20. Lupton D, Gaffney D. Discourses and practices related to suntanning and Primary Care, Institute of Health Sciences, University of Leeds, Worsley 4 solar protection among young Australians. Health Educ Res. 1996;11(2):147–59. Building, Leeds LS2 9NL, UK. Department of Management, Faculty of 21. Wichstrom L. Predictors of Norwegian adolescents' sunbathing and use of Economics, Management and Accountancy, University of Malta, Humanities B sunscreen. Health Psychol. 1994;13(5):412–20. (FEMA), Msida, MSD 2080, Malta. Division of Psychology, Faculty of Natural 22. NICE: Sunlight exposure: Risks and benefits NG34. In.; 2016. Sciences, University of Stirling, FK10 4LA Stirling, Scotland. 23. Kipping RR, Campbell RM, MacArthur GJ, Gunnell DJ, Hickman M. Multiple risk behaviour in adolescence. J Public Health (Oxf). Received: 13 November 2017 Accepted: 16 May 2018 2012;34(Suppl 1):i1–2. 24. Degenhardt L, Chiu WT, Sampson N, Kessler RC, Anthony JC, Angermeyer M, Bruffaerts R, de Girolamo G, Gureje O, Huang Y, et al. Toward a global References view of alcohol, tobacco, cannabis, and cocaine use: findings from the WHO 1. de Vries E, Arnold M, Altsitsiadis E, Trakatelli M, Hinrichs B, Stockfleth E, world mental health surveys. PLoS Med. 2008;5(7):e141. Coebergh J, Group E. Potential impact of interventions resulting in reduced 25. Viner R. Life stage: adolescence in: Our Children Deserve Better: Prevention exposure to ultraviolet (UV) radiation (UVA and UVB) on skin cancer Pays. Edn. Edited by chief medical officer. London: Department of Health; 2012. incidence in four European countries, 2010-2050. Br J Dermatol. 26. Kendler KS, Myers J, Damaj MI, Chen X. Early smoking onset and risk for 2012;167(Suppl 2):53–62. subsequent nicotine dependence: a monozygotic co-twin control study. 2. Skin cancer incidence statistics [http://www.cancerresearchuk.org/health- Am J Psychiatry. 2013;170(4):408–13. professional/cancer-statistics/statistics-by-cancer-type/skin-cancer]. 27. Lostritto K, Ferrucci LM, Cartmel B, Leffell DJ, Molinaro AM, Bale AE, Mayne 3. Parkin DM, Mesher D, Sasieni P. 13. Cancers attributable to solar (ultraviolet) ST. Lifetime history of indoor tanning in young people: a retrospective radiation exposure in the UK in 2010. Br J Cancer. 2011;105(Suppl 2):S66–9. assessment of initiation, persistence, and correlates. BMC Public Health. 4. Green A, Battistutta D. Incidence and determinants of skin cancer in a high- 2012;12:118. risk Australian population. Int J Cancer. 1990;46(3):356–61. 5. Kricker A, Armstrong BK, English DR, Heenan PJ. A dose-response curve for 28. Marks R. Skin cancer–childhood protection affords lifetime protection. Med sun exposure and basal cell carcinoma. Int J Cancer. 1995;60(4):482–8. J Aust. 1987;147(10):475–6. 6. Elwood JM, Jopson J. Melanoma and sun exposure: an overview of 29. Skin cancer - Be clear on cancer [https://www.nhs.uk/be-clear-on-cancer/ published studies. Int J Cancer. 1997;73(2):198–203. symptoms/skin-cancer#Kh628JoIWz1xI2VU.97]. Hubbard et al. BMC Public Health (2018) 18:666 Page 14 of 15 30. Step by Step Self-examination [https://www.skincancer.org/skin-cancer- region of residence in determining clinical and self-conducted skin information/early-detection/step-by-step-self-examination]. examination. Arch Dermatol. 2012;148(10):1142–51. 31. Hamidi R, Peng D, Cockburn M. Efficacy of skin self-examination for the 52. Leventhal H. Findings and theory in the study of fear communications. early detection of melanoma. Int J Dermatol. 2010;49(2):126–34. Adv Exp Soc Psychol. 1970;5:119–86. 32. Rutherford MJ, Ironmonger L, Ormiston-Smith N, Abel GA, Greenberg DC, 53. Leventhal H, Phillips LA, Burns E. The common-sense model of self- Lyratzopoulos G, Lambert PC. Estimating the potential survival gains by regulation (CSM): a dynamic framework for understanding illness self- eliminating socioeconomic and sex inequalities in stage at diagnosis of management. J Behav Med. 2016;39(6):935–46. melanoma. Br J Cancer. 2015;112(Suppl 1):S116–23. 54. Cameron LD. Illness risk representations and motivations to engage in 33. Neal RD,Tharmanathan P,FranceB, Din NU,CottonS,Fallon-Ferguson protective behavior: the case of skin cancer risk. Psychol Health. J, Hamilton W, Hendry A, Hendry M, Lewis R, et al. Is increased time 2008;23(1):91–112. to diagnosis and treatment in symptomatic cancer associated 55. Miller SMD, M. A. C-SHIP: A cognitive-social health information processing with poorer outcomes? Systematic review. Br J Cancer. approach to cancer. In: Krantz D, editor. Perspectives in Behavioral Medicine. 2015;112(Suppl 1):S92–107. NJ: Lawrence Erlbaum; 1998. p. 219–44. 34. Berwick M, Begg CB, Fine JA, Roush GC, Barnhill RL. Screening for cutaneous 56. Sniehotta FF, Nagy G, Scholz U, Schwarzer R. The role of action control in melanoma by skin self-examination. J Natl Cancer Inst. 1996;88(1):17–23. implementing intentions during the first weeks of behaviour change. 35. Hamidi R, Cockburn MG, Peng DH. Prevalence and predictors of skin self- Br J Soc Psychol. 2006;45(Pt 1):87–106. examination: prospects for melanoma prevention and early detection. 57. Araujo-Soares V, McIntyre T, Sniehotta FF. Predicting changes in Int J Dermatol. 2008;47(10):993–1003. physical activity among adolescents: the role of self-efficacy, 36. Richard MA, Grob JJ, Avril MF, Delaunay M, Gouvernet J, Wolkenstein P, intention, action planning and coping planning. Health Educ Res. Souteyrand P, Dreno B, Bonerandi JJ, Dalac S, et al. Delays in diagnosis 2009;24(1):128–39. and melanoma prognosis (I): the role of patients. Int J Cancer. 58. Moss-Morris R, Weinman J, Petrie K, Horne R, Cameron L, Buick D. The 2000;89(3):271–9. revised illness perception questionnaire (IPQ-R). Psychol Health. 37. Koh HK, Miller DR, Geller AC, Clapp RW, Mercer MB, Lew RA. Who discovers 2002;17(1):1–16. melanoma? Patterns from a population-based survey. J Am Acad Dermatol. 59. Government Statistical Service: Ethnic Group. Harmonised Concepts and 1992;26(6):914–9. Questions for Social Data Sources: Primary Principles. London; 2015. 38. Gardner B, Lally P, Wardle J. Making health habitual: the psychology 60. Whitehead M, Dahlgren G. What can be done about inequalities in health? of 'habit-formation' and general practice. Br J Gen Pract. Lancet. 1991;338(8774):1059–63. 2012;62(605):664–6. 61. Spencer LR, Ritchie J, O’Connor, W. Analysis: practices, principles and 39. Carli P, De Giorgi V, Palli D, Maurichi A, Mulas P, Orlandi C, Imberti G, processes. In: Qualitative Research Practice: A Guide for Social Science Stanganelli I, Soma P, Dioguardi D, et al. Patterns of detection of superficial Students and Researchers. edn. Edited by Ritchie JL. London: SAGE; spreading and nodular-type melanoma: a multicenter Italian study. 2003: 199–218. Dermatol Surg. 2004;30(11):1371–5. discussion 1375-1376 62. Hubbard G, Stoddart I, Forbat L, Neal RD, O'Carroll RE, Haw S, Rauchhaus P, 40. Gavin A, Boyle R, Donnelly D, Donnelly C, Gordon S, McElwee G, Kyle RG. School-based brief psycho-educational intervention to raise O'Hagan A. Trends in skin cancer knowledge, sun protection practices adolescent cancer awareness and address barriers to medical help-seeking and behaviours in the Northern Ireland population. Eur J Pub Health. about cancer: a cluster randomised controlled trial. Psychooncology. 2012;22(3):408–12. 2016;25(7):760–71. 41. Hubbard G, Macmillan I, Canny A, Forbat L, Neal RD, O'Carroll RE, Haw S, 63. Gould M, Farrar MD, Kift R, Berry JL, Mughal MZ, Bundy C, Vail A, Webb Kyle RG. Cancer symptom awareness and barriers to medical help seeking AR, Rhodes LE. Sunlight exposure and photoprotection behaviour of in Scottish adolescents: a cross-sectional study. BMC Public Health. white Caucasian adolescents in the UK. J Eur Acad Dermatol. 2014;14:1117. 2015;29(4):732–7. 42. Walter FM, Birt L, Cavers D, Scott S, Emery J, Burrows N, Cavanagh G, MacKie 64. Cokkinides V, Weinstock M, Glanz K, Albano J, Ward E, Thun M. Trends in R, Weller D, Campbell C. 'This isn't what mine looked like': a qualitative sunburns, sun protection practices, and attitudes toward sun exposure study of symptom appraisal and help seeking in people recently diagnosed protection and tanning among US adolescents, 1998-2004. Pediatrics. with melanoma. BMJ Open. 2014;4(7):e005566. 2006;118(3):853–64. 43. Youl PH, Soyer HP, Baade PD, Marshall AL, Finch L, Janda M. Can skin 65. Richards R, McGee R, Knight RG. Sunburn and sun protection among New cancer prevention and early detection be improved via mobile phone Zealand adolescents over a summer weekend. Aust Nz J Publ Heal. text messaging? A randomised, attention control trial. Prev Med. 2001;25(4):352–4. 2015;71:50–6. 66. Dusza SW, Halpern AC, Satagopan JM, Oliveria SA, Weinstock MA, 44. Saraiya M, Glanz K, Briss PA, Nichols P, White C, Das D, Smith SJ, Tannor B, Scope A, Berwick M, Geller AC. Prospective study of sunburn Hutchinson AB, Wilson KM, et al. Interventions to prevent skin cancer by and sun behavior patterns during adolescence. Pediatrics. reducing exposure to ultraviolet radiation: a systematic review. Am J Prev 2012;129(2):309–17. Med. 2004;27(5):422–66. 67. Olson AL, Gaffney CA, Starr P, Dietrich AJ. The impact of an appearance- 45. Schwarzer R. Modeling health behavior change: how to predict and modify based educational intervention on adolescent intention to use sunscreen. the adoption and maintenance of health behaviors. Appl Psychol. Health Educ Res. 2008;23(5):763–9. 2008;57(1):1–29. 68. Miljkovic S, Baljozovic D, Krajnovic D, Tasic L, Sbutega-Milosevic G. The 46. Floyd DL, Prentice-Dunn S, Rogers RW. A meta-analysis of research on impact of education on Adolescents' sun behavior: experiences from Serbia. protection motivation theory. J Appl Soc Psychol. 2000;30(2):407–29. Srp Ark Celok Lek. 2014;142(5–6):330–6. 47. Sheeran P, Harris PR, Epton T. Does heightening risk appraisals change 69. Buller DB, Reynolds KD, Yaroch A, Cutter GR, Hines JM, Geno CR, Maloy people's intentions and behavior? A meta-analysis of experimental studies. JA, Brown M, Woodall WG, Grandpre J. Effects of the sunny days, Psychol Bull. 2014;140(2):511–43. healthy ways curriculum on students in grades 6 to 8. Am J Prev Med. 48. Schuz N, Eid M. Beyond the usual suspects: target group- and behavior- 2006;30(1):13–22. specific factors add to a theory-based sun protection intervention for 70. White KM, Hyde MK, O'Connor EL, Naumann L, Hawkes AL. Testing a belief- teenagers. J Behav Med. 2013;36(5):508–19. based intervention encouraging sun-safety among adolescents in a high 49. Lowe JB, Borland R, Stanton WR, Baade P, White V, Balanda KP. Sun-safe risk area. Prev Med. 2010;51(3–4):325–8. behaviour among secondary school students in Australia. Health Educ Res. 71. Balyaci OE, Kostu N, Temel AB. Training program to raise consciousness 2000;15(3):271–81. among adolescents for protection against skin cancer through 50. Robinson JK, Fisher SG, Turrisi RJ. Predictors of skin self-examination performance of skin self examination. Asian Pac J Cancer Prev. performance. Cancer. 2002;95(1):135–46. 2012;13(10):5011–7. 51. Kasparian NA, Branstrom R, Chang YM, Affleck P, Aspinwall LG, Tibben A, 72. Craciun C, Schuz N, Lippke S, Schwarzer R. Enhancing planning strategies Azizi E, Baron-Epel O, Battistuzzi L, Bruno W, et al. Skin examination for sunscreen use at different stages of change. Health Educ Res. behavior: the role of melanoma history, skin type, psychosocial factors, and 2012;27(5):857–67. Hubbard et al. BMC Public Health (2018) 18:666 Page 15 of 15 73. Mermelstein RJ, Riesenberg LA. Changing knowledge and attitudes about skin cancer risk factors in adolescents. Health Psychol. 1992;11(6):371–6. 74. Janssen E, van Osch L, de Vries H, Lechner L. Measuring risk perceptions of skin cancer: reliability and validity of different operationalizations. Br J Health Psychol. 2011;16(Pt 1):92–112. 75. Janda M, Loescher LJ, Soyer HP. Enhanced skin self-examination: a novel approach to skin cancer monitoring and follow-up. JAMA Dermatol. 2013;149(2):231–6. 76. Vano-Galvan S, Paoli J, Rios-Buceta L, Jaen P. Skin self-examination using smartphone photography to improve the early diagnosis of melanoma. Actas Dermosifiliogr. 2015;106(1):75–7.
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