A randomised controlled trial of the effect of providing online risk information and lifestyle advice for the most common preventable cancers: study protocol

BackgroundCancer is a leading cause of mortality and morbidity worldwide. Prevention is recognised by many, including the World Health Organization, to offer the most cost-effective long-term strategy for the control of cancer. One approach that focuses on individuals is the provision of personalised risk information. However, whether such information motivates behaviour change and whether the effect is different with varying formats of risk presentation is unclear. We aim to assess the short-term effect of providing information about personalised risk of cancer in three different formats alongside lifestyle advice on health-related behaviours, risk perception and risk conviction.MethodsIn a parallel group, randomised controlled trial 1000 participants will be recruited through the online platform Prolific. Participants will be allocated to either a control group receiving cancer-specific lifestyle advice alone or one of three intervention groups receiving the same lifestyle advice alongside their estimated 10-year risk of developing one of the five most common preventable cancers, calculated from self-reported modifiable behavioural risk factors, in one of three different formats (bar chart, pictograph or qualitative scale). The primary outcome is change from baseline in computed risk relative to an individual with a recommended lifestyle at three months. Secondary outcomes include: perceived risk of cancer; anxiety; cancer-related worry; intention to change behaviour; and awareness of cancer risk factors.DiscussionThis study will provide evidence on the short-term effect of providing online information about personalised risk of cancer alongside lifestyle advice on risk perception and health-related behaviours and inform the development of interventions.Trial registrationISRCTN17450583. Registered 30 January 2018.

[1]  I. Lipkus.  Numeric, Verbal, and Visual Formats of Conveying Health Risks: Suggested Best Practices and Future Recommendations , 2007, Medical decision making : an international journal of the Society for Medical Decision Making.

[2]  Michael D. Buhrmester,et al.  Amazon's Mechanical Turk , 2011, Perspectives on psychological science : a journal of the Association for Psychological Science.

[3]  Lisa M. Schwartz,et al.  The Role of Numeracy in Understanding the Benefit of Screening Mammography , 1997, Annals of Internal Medicine.

[4]  N. Day,et al.  EPIC-Norfolk: study design and characteristics of the cohort. European Prospective Investigation of Cancer. , 1999, British journal of cancer.

[5]  D. Bowen,et al.  Effects of Breast Cancer Risk Counseling for Sexual Minority Women , 2006, Health care for women international.

[6]  A. Lophatananon,et al.  Responses to provision of personalised cancer risk information: a qualitative interview study with members of the public , 2017, BMC Public Health.

[7]  N. Guha,et al.  European Code against Cancer, 4th Edition: Tobacco and cancer. , 2015, Cancer epidemiology.

[8]  Jennifer M. Taber,et al.  The role of conviction in personal disease risk perceptions: What can we learn from research on attitude strength? , 2016, Social and personality psychology compass.

[9]  Cecily Morrison,et al.  Analyzing Engagement in a Web-Based Intervention Platform Through Visualizing Log-Data , 2014, Journal of medical Internet research.

[10]  P. Ubel,et al.  Reducing the Influence of Anecdotal Reasoning on People’s Health Care Decisions: Is a Picture Worth a Thousand Statistics? , 2005, Medical decision making : an international journal of the Society for Medical Decision Making.

[11]  D M Parkin,et al.  16. The fraction of cancer attributable to lifestyle and environmental factors in the UK in 2010 , 2011, British Journal of Cancer.

[12]  F. Berrino,et al.  European Code against Cancer 4 th Edition : Alcohol drinking and cancer , 2015 .

[13]  Elisa Bertino,et al.  Quality Control in Crowdsourcing Systems: Issues and Directions , 2013, IEEE Internet Computing.

[14]  Mack T Ruffin,et al.  Family history assessment: impact on disease risk perceptions. , 2012, American journal of preventive medicine.

[15]  S. Suttona,et al.  Health Behavior : Psychosocial Theories , 2004 .

[16]  G. Colditz,et al.  Colon Cancer: Risk Perceptions and Risk Communication , 2004, Journal of health communication.

[17]  Melissa L. Finucane,et al.  Risk as Analysis and Risk as Feelings: Some Thoughts about Affect, Reason, Risk, and Rationality , 2004, Risk analysis : an official publication of the Society for Risk Analysis.

[18]  F. Berrino,et al.  European Code against Cancer 4th Edition: Alcohol drinking and cancer. , 2015, Cancer epidemiology.

[19]  Sophie Hill,et al.  Absolute risk representation in cardiovascular disease prevention: comprehension and preferences of health care consumers and general practitioners involved in a focus group study , 2010, BMC public health.

[20]  R. W. Rogers,et al.  A Protection Motivation Theory of Fear Appeals and Attitude Change1. , 1975, The Journal of psychology.

[21]  James G. Dolan,et al.  Risk communication formats for low probability events: an exploratory study of patient preferences , 2008, BMC Medical Informatics Decis. Mak..

[22]  M. Stefanek,et al.  Younger women at increased risk for breast cancer: perceived risk, psychological well-being, and surveillance behavior. , 1994, Journal of the National Cancer Institute. Monographs.

[23]  John Weinman,et al.  Time orientation and health-related behaviour: Measurement in general population samples , 2009, Psychology & health.

[24]  Robert Fletcher,et al.  Tailored Computer-Based Cancer Risk Communication: Correcting Colorectal Cancer Risk Perception , 2004, Journal of health communication.

[25]  S. Sharp,et al.  Effect of interventions incorporating personalised cancer risk information on intentions and behaviour: a systematic review and meta-analysis of randomised controlled trials , 2018, BMJ Open.

[26]  F. Berrino,et al.  European Code against Cancer 4th Edition: Obesity, body fatness and cancer. , 2015, Cancer epidemiology.

[27]  T. Marteau,et al.  The development of a six-item short-form of the state scale of the Spielberger State-Trait Anxiety Inventory (STAI). , 1992, The British journal of clinical psychology.

[28]  B. Trock,et al.  Psychological and behavioral implications of abnormal mammograms. , 1991, Annals of internal medicine.

[29]  S. Michie,et al.  Psychological and Behavioral Responses to Genetic Test Results Indicating Increased Risk of Obesity: Does the Causal Pathway from Gene to Obesity Matter? , 2009, Public Health Genomics.

[30]  Julie O. Culver,et al.  Results of a randomized study of telephone versus in-person breast cancer risk counseling. , 2006, Patient education and counseling.

[31]  F. Berrino,et al.  European Code against Cancer 4th Edition: Physical activity and cancer. , 2015, Cancer epidemiology.

[32]  Daniel M. Oppenheimer,et al.  Instructional Manipulation Checks: Detecting Satisficing to Increase Statistical Power , 2009 .

[33]  S. Sutton.  Health Behavior, Psychosocial Theories of , 2001 .

[34]  G. Glendon,et al.  A focus group study on breast cancer risk presentation: one format does not fit all , 2012, European Journal of Human Genetics.

[35]  D. Cella,et al.  A brief assessment of concerns associated with genetic testing for cancer: the Multidimensional Impact of Cancer Risk Assessment (MICRA) questionnaire. , 2002, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.

[36]  A. Acquisti,et al.  Reputation as a sufficient condition for data quality on Amazon Mechanical Turk , 2013, Behavior Research Methods.

[37]  A. Acquisti,et al.  Beyond the Turk: Alternative Platforms for Crowdsourcing Behavioral Research , 2016 .

[38]  Trudy van der Weijden,et al.  What are effective strategies to communicate cardiovascular risk information to patients? A systematic review. , 2011, Patient education and counseling.

[39]  Jude Robinson,et al.  Utilizing Lung Cancer Risk Prediction Models to Promote Smoking Cessation: Two Randomized Controlled Trials , 2018, American journal of health promotion : AJHP.

[40]  Stacey L. Sheridan,et al.  Designing and implementing a comparative effectiveness study of two strategies for delivering high quality CHD prevention: methods and participant characteristics for the Heart to Health study. , 2013, Contemporary clinical trials.

[41]  F. Berrino,et al.  European Code against Cancer 4th Edition: Alcohol drinking and cancer. , 2016, Cancer epidemiology.

[42]  Stefan Palan,et al.  Prolific.ac—A subject pool for online experiments , 2017 .

[43]  W. Klein,et al.  The Tripartite Model of Risk Perception (TRIRISK): Distinguishing Deliberative, Affective, and Experiential Components of Perceived Risk , 2016, Annals of behavioral medicine : a publication of the Society of Behavioral Medicine.

[44]  D. French,et al.  Can Communicating Personalised Disease Risk Promote Healthy Behaviour Change? A Systematic Review of Systematic Reviews , 2017, Annals of behavioral medicine : a publication of the Society of Behavioral Medicine.

[45]  R. W. Rogers,et al.  Effects of components of protection-motivation theory on adaptive and maladaptive coping with a health threat. , 1987, Journal of personality and social psychology.

[46]  R. Peto,et al.  The fraction of cancer attributable to lifestyle and environmental factors in the UK in 2010 , 2011, British Journal of Cancer.

[47]  T. Marteau,et al.  The impact of communicating genetic risks of disease on risk-reducing health behaviour: systematic review with meta-analysis , 2016, British Medical Journal.

[48]  S. Griffin,et al.  Impact of provision of cardiovascular disease risk estimates to healthcare professionals and patients: a systematic review , 2015, BMJ Open.

[49]  Elizabeth Murray,et al.  Patient reactions to a web-based cardiovascular risk calculator in type 2 diabetes: a qualitative study in primary care , 2015, The British journal of general practice : the journal of the Royal College of General Practitioners.