Widening access to online health education for lung cancer: a feasibility study

Having lung cancer is associated with accessibility issues because people afflicted with lung cancer tend to be older and less familiar with technology, and have low education levels and low health literacy. Fear, embarrassment and stigmatization also play a role. This makes it difficult for people to access the information they need to understand and manage their illness, particularly in the time before the diagnosis. We can mitigate these disadvantages and bridge the accessibility gap by ensuring people at risk for lung cancer are informed about symptoms and when to seek medical advice. The Web is uniquely placed to fulfill this role. We therefore developed an online lung cancer symptom appraisal tool tailored towards people with low education levels and health literacy and based on psychological theory to target barriers like fear and embarrassment. At present we are conducting a feasibility study to assess whether it is possible to reach the high risk population and encourage early help-seeking. So far, 97 users have participated, 97.9% of which report symptoms and risk factors that indicate they should seek medical help. 34% report education levels below school leaving qualification. Our tool led to a significantly higher intention to seek medical help than the same information without theory-based components (p = 0.01). Our initial analyses suggest this is a suitable approach to widening health education to excluded groups.

[1]  Icek Ajzen,et al.  From Intentions to Actions: A Theory of Planned Behavior , 1985 .

[2]  Matthew W Kreuter,et al.  Tailored and targeted health communication: strategies for enhancing information relevance. , 2003, American journal of health behavior.

[3]  Tana M Luger,et al.  Older Adult Experience of Online Diagnosis: Results From a Scenario-Based Think-Aloud Protocol , 2014, Journal of medical Internet research.

[4]  E. Davies,et al.  Coverage of common cancer types in UK national newspapers: a content analysis , 2014, BMJ Open.

[5]  J. Wardle,et al.  Knowledge of lung cancer symptoms and risk factors in the UK: development of a measure and results from a population-based survey , 2012, Thorax.

[6]  Jacob Cohen Statistical Power Analysis for the Behavioral Sciences , 1969, The SAGE Encyclopedia of Research Design.

[7]  J. Corner,et al.  Experience of health changes and reasons for delay in seeking care: a UK study of the months prior to the diagnosis of lung cancer. , 2006, Social science & medicine.

[8]  J. Beckmann,et al.  Action control : from cognition to behavior , 1985 .

[9]  E. V. Kardorff,et al.  The use of the Internet by women with breast cancer and men with prostate cancer-results of online research , 2008, Journal of Public Health.

[10]  R. H. Browne On the use of a pilot sample for sample size determination. , 1995, Statistics in medicine.

[11]  Lucy Yardley,et al.  Understanding reactions to an internet-delivered health-care intervention: accommodating user preferences for information provision , 2010, BMC Medical Informatics Decis. Mak..

[12]  A. Jemal,et al.  Lung Cancer Statistics. , 2016, Advances in experimental medicine and biology.

[13]  Sallimah M. Salleh Examining the influence of teachers ' beliefs towards technology integration in classroom , 2016 .