How Can Skin Check Reminders be Personalised to Patient Conscientiousness?

Abstract

This paper explores the potential of personalising health reminders to melanoma patients based on their personality (high vs low conscientiousness). We describe a study where we presented participants with a scenario with a ctional patient who has not performed a skin check for recurrent melanoma. The patient was described as either very conscientious, or very unconscientious. We asked participants to rate reminders inspired by Cialdini's 6 principles of persuasion for their suitability for the patient. Participants then chose their favourite reminder and an alternative reminder to send if that one failed. We found that conscientiousness had an e ect on both the ratings of reminder types and the most preferred reminders selected by participants.

Keywords

• Personalised reminders
• personality
• persuasion
• eHealth

Introduction

Melanoma (skin cancer) is one of the most common cancers in 15-34 year olds. More than 1/3 of cases occur in people under 55 and, in the UK, it kills over 2,000 people every year [ 1 ]. The risk of malignant melanoma is between 8-15 times greater in people who have been diagnosed with a previous melanoma [ 2 ] and early detection of these recurrences is a critical goal of follow-up programmes [ 28 ]. For this reason it has been proposed that patients treated for cutaneous melanoma perform Total Skin Self-examinations (TSSEs) at frequent intervals [ 4 ]. Patients treated for cutaneous melanoma who detected their own recurrences have up to a 63% reduction in mortality [ 9, 20 ]. However, even if patients are taught to self-check often, it is likely that their self-checking will decrease over time without an intervention to sustain their behaviour [ 16, 19 ]. There is extensive evidence to suggest that mobile telephone and internet interventions can help promote health behaviour change (e.g. [ 13, 34, 30 ]), and evidence to suggest that apps (i.e. mobile or tablet applications) can be used to support a sustained health self-management strategy [ 35 ].

With this in mind, the ASICA (Achieving Self-directed Integrated Cancer Aftercare) Skin-Checker app was developed at the University of Aberdeen in 2013. The app is part of an intervention that aims to remove barriers between patients treated for melanoma and specialists in dermatology by enabling remote screening and diagnosis of skin changes. One goal was to ensure that patients complete TSSEs regularly (at least once per month). In a six month pilot study, patients were provided with a tablet with the skin checker app. The same reminder was sent by a member of the team monthly to all patients. We found that the reminders were generally e ective, but not for all 20 patients. Accordingly, we decided to investigate how reminders could be personalised. It is likely that personality plays a role in a patient's response to a reminder (along with other relevant factors such as their a ective state, daily schedules, etc.), and as personality is relatively stable in adults, it seems a relevant characteristic to consider for the personalization of reminders.

Personality can be measured using many methods, however, the Five-Factor model [ 14 ] from trait theory is one of the most popular and reliably validated constructs in use by psychologists. This model describes ve personality dimensions: Agreeableness (I), Extraversion (II), Conscientiousness (III), Neuroticism (IV) and Openness to Experience (V). In this paper, we focus on Conscientiousness which describes how meticulous and hard-working an individual is, because this might a ect their motivation to perform skin checks. We describe a study where we asked participants to rate twelve di erent types of reminder for their suitability, based on the conscientiousness of the patient. The results from this study will provide an indication of how reminders could be personalised by the ASICA skin checker app in the future. 2

Related Work

Experts in persuasion have proposed many di erent sets of strategies (from 6 up to over 100 persuasive strategies per set) that can be used to motivate certain behaviours [ 22 ]. In this paper we make use of Cialdini's 6 principles of persuasion [ 8 ] (shown in Table 1), as they have been used in multiple contexts including reminders [ 22 ]. Cialdini's persuasive principles [ 8 ] have been used in reminders for clinic appointments [ 33 ] and interaction with an activity monitor app [ 22 ].

An e ective way to persuade people to interact with a system is to provide reminders [ 12 ]. Arguably, in the health domain, reminders should be even more potent, as patients are already motivated by the possible threat to their well-being. Health reminders have been researched for several decades. In 1991, [ 29 ] found that computer-generated reminders e ectively improve adherence to preventative health services. This has been found in multiple domains - for example, using text message reminders in HIV patients [ 11 ]; for malaria management [ 36 ]; attending healthcare appointments [ 17 ] and using mobile noti cations to increase well-being logging on an app [ 3 ].

Personalisation in reminders is however a relatively new eld. [ 26 ] identied the need for the personalisation of reminder systems, beyond adaptation to scheduling preferences. Some research has been done on personalising reminders, e.g. adapting to the user's location and movement when providing medication reminders [ 23 ]; adapting a ect in hand washing reminders for patients with Alzheimers Disease [ 24 ]; and tailoring mammography reminders to personal risk and the patient's personal barriers to having a mammogram [ 25 ].

There has also been research into the link between personality and the result of reminders in the healthcare domain, e.g [ 18 ] found that conscientious people would likely be the most successful at achieving their health objectives, and persuasive categories with a social aspect were likely to be the most successful for conscientious people. Patients low in conscientiousness typically have lower adherence to treatments [ 5, 6 ]. Therefore, it is likely that patients who are low in conscientiousness would require di erent types of reminders, and perhaps more frequently, than those patients who are normally highly conscientious. 3

Study Design

This study investigates which types of reminder are best for patients with different levels of conscientiousness. There were two parts to the study. The rst part asked participants to rate the reminders for their suitability for \John", a ctional patient, who would either be described as having high or low conscientiousness. The second part asked participants to pick the best reminder to send. Subsequently, participants were asked how long they would wait before sending a second reminder if the rst one failed, and then asked to pick a second reminder to send. 3.1

Participants

The study was administered as an online questionnaire on Amazon's Mechanical Turk [ 27 ]. Mechanical Turk allows the creators of tasks (requesters ) to approve or reject completed work before payment. As a further check, we included a Cloze Test [ 32 ] for English uency to ensure that workers possessed enough literacy skills to understand the language based nature of the task. Participants had to have an acceptance rate of 90%, be based in the United States and pass the uency test in order to be eligible for the study. There were 68 participants (50% female, 50% male; 24% aged 18-25, 50% aged 26-40, 35% aged 41-65, 1% over 65) with a random allocation for conscientiousness (30 low, 38 high). 3.2

Materials

John is always prepared. He gets tasks

done right away, paying attention to detail. He makes plans and sticks to them and carries them out. He completes tasks successfully, doing things according to a plan. He is exacting in his work; he nishes what he starts. John is quite a nice person, tends to enjoy talking with people, and quite likes exploring new ideas.

low

John procrastinates and wastes his time.

He nds it di cult to get down to work.

He does just enough work to get by and often doesnt see things through, leaving them un nished. He shirks his duties and messes things up. He doesnt put his mind on the task at hand and needs a push to get started. John tends to enjoy talking with people.

This experiment conveys the patient's personality using short stories previously validated for describing low or high conscientiousness [ 10 ]. Originally the stories were adapted from the NEO-IPIP 20-item scales [ 15 ] by combining the phrases into sentences to form a short story, with the addition of a very common male name, John, shown in Table 2.

12 persuasive reminders were developed depicting Cialdini's six persuasion categories [ 8 ], two for each category. These were generated with a panel of experts in eHealth in a brainstorming session, and are shown in Table 3. 3.3

Experimental design

The independent variables are the conscientiousness of the patient \John" (low or high, between-subjects), and the persuasive reminder (12 reminders, withinsubjects).

The dependent variables are: Suitability; the most preferred (`best') reminder to send rst; the best reminder to send second; and the length of time between the two reminders. Suitability was based on the average rating of each reminder of four measures: e ectiveness, helpfulness, appropriateness and sensitivity developed by [ 21 ]. These have been found to be internally consistent and to contribute to a single factor in a Principal Component Analysis [ 31 ]. 90% of people with the Skin Checker iPad have already performed their skin check this month. Please check your skin now.

Thousands of people are actively checking their skin each month. Join them please check your skin now.

You have checked your skin frequently in the past. Please check your skin now.

When you decided to participate, you agreed that checking your skin monthly is a good idea. Please check your skin now.

Doctors recommend that you check your skin at least once a month as health outcomes are better if you do. Please check your skin now.

According to experts, checking your skin regularly is an e ective way of identifying recurrent skin cancer. Please check your skin now.

This is your last opportunity for your monthly skin check. Do not miss out please check your skin now.

If a recurrent skin cancer gets detected quickly, health outcomes are much better. Please check your skin now. 3.4

Procedure

The study began by asking participants to complete the English uency test. If they passed, participants were asked to select their gender and age from a range (both elds were optional). On the next screen, the participants were shown a short explanation of why skin checking is important, and the story about \John", conveying high or low conscientiousness (see Figure 1). Participants were told that John had not performed his skin check yet this month, and that the app needed to send an automated reminder. Next, they rated each of the 12 reminders in turn for their suitability for `John' using the 4 scales (see Figure 1).

Subsequently, participants were asked to select the reminder that they felt was best for John. The information about the importance of skin checking and John's personality were repeated to remind the participants (shown in Figure 2). They were then asked how long they would wait before sending a second reminder if the rst one failed to provoke John to perform his skin check (from 1-30 days, or `longer'). Finally, they were asked to pick the reminder that they would send as the second reminder. Participants could choose to send the same reminder again if they wished. 26/03/2015   Section 2 Skin checking Meet John Voluntary Research Questionnaire Read the following information, then complete the tasks. Take your time ­ there are no right or wrong answers; we are interested in what you think. It is important for people who have had skin cancer and have been successfully treated to regularly perform a skin­check, where they closely examine all of their skin for changes. This is because recurrences can occur and if they are caught early, the chances for successful treatment are much better. The next part of this study is about "John", who was successfully treated for skin cancer in the past.

John procrastinates and wastes his time. He finds it difficult to get down to work. He does just enough work to get by and often doesn’t see things through, leaving them unfinished. He shirks his duties and messes things up. He doesn’t put his mind on the task at hand and needs a push to get started. John tends to enjoy talking with people.

John’s Doctor has given him an iPad with an app on it which helps him to check his skin. When John has used the app to do a full skin check, a notification is sent to his doctor automatically. John has been advised to check his skin monthly.

A month has passed, and John has not checked his skin yet.

Reminder number 1 of 12: Please rate this reminder for the following qualities: Appropriateness Effectiveness Helpfulness Sensitivity

Very inappropriate Very ineffective Very unhelpful Very insensitive  1  1  1  1  2  2  2  2  3  3  3  3  4  4  4  4

Very appropriate  5  5  5  5 Very effective Very helpful Very sensitive 26/03/2015   © 2015 AberdeenCSD Section 3

When you are ready, please preMssQ tEhe  M "nTe xAtp" pbutton to continue.

Next Voluntary Research Questionnaire

Fig. 1. Screenshot of the rating part of the study Thank you for rating all of the reminders. We will now ask you some further information about the best reminders to send.

Here is a reminder of the situation: It is important for people who have had skin cancer and have been successfully treated to regularly perform a skin­check, where they closely examine all of their skin for changes. This is because recurrences can occur, and if caught early, the chances for successful treatment are much better.

Now that you have rated all of the reminders, we would like to you to select the one that you think is best for John from the list below.

We would love to receive confirmation that you have checked your skin. Please check your skin now. 90% of people with the Skin Checker iPad have already performed their skin check this month. Please check your skin now.

When you decided to participate, you agreed that checking your skin monthly is a good idea. Please check your skin now. https://homepages.abdn.ac.uk/m.dennis/pages/2015/asicapers/index.php?c=questionnaire&m=section2

Thousands of people are actively checking their skin each month. Join them ­ please check your skin now.

This is your last opportunity for your monthly skin check. Do not miss out ­ please check your skin now. The Skin Checker iPad was provided to you to help you check your skin. Please check your skin now.

If a recurrent skin cancer gets detected quickly, health outcomes are much better. Please check your skin now.

Your friends would feel better knowing that you are OK. Please check your skin now. You have checked your skin frequently in the past. Please check your skin now.

Continue

Fig. 2. Screenshot of the best reminder selection part of the study 1/1 Given the exploratory nature of this study, the hypotheses are open-ended with two-sided comparisons between levels of concientiousness.

Results

Analysis of Ratings

5.00 H1a. Pairwise comparisons of Reminder Type revealed 3 homogeneous subsets. Authority was the best, followed by the subset containing Scarcity, Consensus, Likability & Reciprocity. The nal subset of Reciprocity and Commitment and Consistency. These can be seen in Table 4.

To investigate the interaction e ect, pairwise comparisons (Bonferonni corrected) were performed on Reminder Type Trait Level. There was a signi cant e ect for Liking - this was rated signi cantly higher for the low trait level. There were also signi cant di erences in the highest rated reminders for each trait level (m=4.10 vs 3.74) - shown in Table 4 and Figure 4. Fig. 4. Graph of Average Rating for each Reminder Type for High and Low Conscientiousness In the second part of the experiment, we asked participants to pick the best reminder to send to John out of all twelve reminders. To analyse this, we performed a Chi-squared test of trait level Best Reminder Type. This was signi cant at 2(5) = 13:70; p < 0:05, supporting hypothesis H2. Table 5 shows the frequency of each Reminder Type selected for each trait level. For low conscientiousness, participants most commonly selected the AUT and LIK reminders, while for high conscientiousness, participants selected AUT and SCA.

After selecting their best reminder, participants were asked to choose a second reminder to send if their rst reminder failed. A Chi-squared test of trait level Second Reminder Type was not signi cant at 2(5) = 3:01; p > 0:5, meaning H3a is not supported. We explored this further by counting how many participants chose di erent Reminder Types for their rst and second reminders (changed reminder ). We performed a binomial test of changed reminder with Test Proposition of 0.50. This was signi cant at p < 0:01 { 56 of 68 participants changed their reminder type, supporting H3. This shows that participants preferred a di erent reminder type for the second reminder if the rst failed. We did not identify a predictable pattern for the second choice, in terms of direction or level of conscientiousness.

Low Conscientiousness

High Conscientiousness Fig. 5. Frequency Histogram of Number of days to wait before issuing a second reminder for high and low conscientiousness

We also asked participants how long they would wait to send the second reminder (1-30 days or longer). As shown in Figure 5, most participants would wait for 1-3 days (Low trait mean = 2:30 1:56, High trait mean = 2:92 2:57), with a maximum of 10 days in between reminders. A Mann-Whitney test showed no di erence for conscientiousness, giving no support for H4. 5

Conclusion

In this paper, we described a study where participants were asked to rate the suitability of di erent reminders for a ctional patient (with either high or low conscientiousness) to check their skin. We found that the level of conscientiousness of the described patient had a signi cant e ect on both the ratings of the reminders, and the most preferred reminder.

For low conscientiousness, reminders of the `liking' type (where the reminders appear to come from someone they like) were the most popular, followed closely by reminders of the `authority' type (where the reminder informs the patient of what doctors recommend). For high conscientiousness, reminders of the authority type were tied with reminders of the `scarcity' type (reminders that inform the patient that they cannot leave the skin check until later) were the most popular. We found that participants chose a reminder of a di erent type for a second reminder, but not in a predictable way. Surprisingly, we found no e ect of conscientiousness on the time between reminders, with most waiting 1-3 days.

This leads to several interesting questions and directions for future work. Although we found signi cant di erences, reminders of the `authority' type were universally popular. It is possible that this would be a useful default if the personality of the patient is not identi ed. Further, the `liking' type reminders were only marginally more popular than `authority' for low conscientiousness, and equally as popular as `scarcity' reminders for high conscientiousness. We still need to establish which type would be best to send. Additionally, we have not found a trend to establish the type of the second reminder if the rst fails.

A limitation of our approach is that we only investigated what people think the best reminder would be, and we do not know the e ects of these reminders on real patients. If there is a di erence between the method preferred by advice givers and which reminders are most e ective for patients, this could have a large impact on how advice giving is adapted. We also did not investigate di erences based on what participants perceived the application as representing (doctor, friend, etc.). We will work with clinicians to ensure that reminders are appropriate and safe to send to patients. After this, we can begin investigating their e ect on patients, and incorporate them into the skin-checker app.

Acknowledgments

This work was funded by the RCUK Digital Economy award to the dot.rural Digital Economy Hub, University of Aberdeen; award reference: EP/G066051/1. The dataset used by this paper can be acquired by emailing the rst author.

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