Computer programs that use whatâ€™s called computer-adapted testingâ€”or CATâ€”may be significantly more likely to lead to better outcomes patients who are at risk for skin cancer.
A study in the Journal of Medical Internet Research suggests that computer programs that use what’s called computer-adapted testing—or CAT—may be significantly more likely to lead to better outcomes patients who are at risk for skin cancer.
The finding is potentially important because online surveying and screening of patients with skin cancer is an emerging and important field, but it can be hindered by participation rates. Removing some of the obstacles to participation could be a significant boon to overall screening efforts.
The study is from Australia, a country with an incredibly high incidence of skin cancers. In the land down under, skin cancers account for approximately 80% of all newly diagnosed cancers. “From a population of only 23 million, more than 434,000 people are treated for one or more nonmelanoma skin cancers in Australia each year,” the study authors observe.
The researchers have been working with questionnaires that assess the underlying risk of potential cancer patients. The researchers posited that using responses to questions about attitudes toward sunblock usage, indoor and outdoor tanning, body freckles, eye color, and tendency to burn, among other questions, it should be possible to create a scale to measure these attributes and calculate an overall skin cancer risk score.
They compared the efficiency of non-adaptive (NAT) and CAT facilitated by Partial Credit Model (PCM)-derived calibration to estimate skin cancer risk, using a random sample from a population-based Australian cohort study of skin cancer risk (N=43,794). Using statistical models, including popular Rasch models, they found that use of CAT led to smaller person standard error of the estimated measure than NAT, with substantially higher efficiency but no loss of precision. The CAT test reduced response burden by 48%, 66%, and 66% for dichotomous, Rating Scale Model, and PCM models, respectively.
“A brief CAT such as the one we developed could be used to inform people quickly about their skin cancer risk and how to improve their sun protection behaviors,” the researchers concluded. “A mobile online CAT could be used for evaluating skin cancer risk and might reduce the item length in clinical settings.”
Strengths of the study include a very large sample size. Possible limitations include possible need to modify the CAT module for non-English speaking populations.