Efficacy of a web-based intelligent tutoring system for communicating genetic risk of breast cancer: a fuzzy-trace theory approach.

BACKGROUND: . Many healthy women consider genetic testing for breast cancer risk, yet BRCA testing issues are complex. OBJECTIVE: . To determine whether an intelligent tutor, BRCA Gist, grounded in fuzzy-trace theory (FTT), increases gist comprehension and knowledge about genetic testing for breast cancer risk, improving decision making. DESIGN: . In 2 experiments, 410 healthy undergraduate women were randomly assigned to 1 of 3 groups: an online module using a Web-based tutoring system (BRCA Gist) that uses artificial intelligence technology, a second group read highly similar content from the National Cancer Institute (NCI) Web site, and a third that completed an unrelated tutorial. INTERVENTION: . BRCA Gist applied FTT and was designed to help participants develop gist comprehension of topics relevant to decisions about BRCA genetic testing, including how breast cancer spreads, inherited genetic mutations, and base rates. MEASURES: . We measured content knowledge, gist comprehension of decision-relevant information, interest in testing, and genetic risk and testing judgments. RESULTS: . Control knowledge scores ranged from 54% to 56%, NCI improved significantly to 65% and 70%, and BRCA Gist improved significantly more to 75% and 77%, P < 0.0001. BRCA Gist scored higher on gist comprehension than NCI and control, P < 0.0001. Control genetic risk-assessment mean was 48% correct; BRCA Gist (61%) and NCI (56%) were significantly higher, P < 0.0001. BRCA Gist participants recommended less testing for women without risk factors (not good candidates; 24% and 19%) than controls (50%, both experiments) and NCI (32%), experiment 2, P < 0.0001. BRCA Gist testing interest was lower than in controls, P < 0.0001. LIMITATIONS: . BRCA Gist has not been tested with older women from diverse groups. CONCLUSIONS: . Intelligent tutors, such as BRCA Gist, are scalable, cost-effective ways of helping people understand complex issues, improving decision making.

Implementation outcomes of military provider training in cognitive processing therapy and prolonged exposure therapy for post-traumatic stress disorder.

Between 2006 and 2012, the Department of Defense trained thousands of military mental health providers in the use of evidence-based treatments for post-traumatic stress disorder. Most providers were trained in multiday workshops that focused on the use of Cognitive Processing Therapy and Prolonged Exposure. This study is a follow-up evaluation of the implementation practices of 103 Air Force mental health providers. A survey was administered online to workshop participants; 34.2% of participants responded. Findings on treatment implementation with the providers indicated that a majority of respondents found the trainings valuable and were interested in using the treatments, yet they reported a lack of time in their clinic appointment structure to support their use. Insufficient supervision was also cited as a barrier to treatment use. Results suggest the need to improve strategies for implementing evidence-based practices with providers to enhance clinical outcomes in military settings.

A signal detection analysis of gist-based discrimination of genetic breast cancer risk.

Pervasive biases in probability judgment render the probability scale a poor response mode for assessing risk judgments. By applying fuzzy trace theory, we used ordinal gist categories as a response mode, coupled with a signal detection model to assess risk judgments. The signal detection model is an extension of the familiar model used in binary choice paradigms. It provides three measures of discriminability-low versus medium risk, medium versus high risk, and low versus high risk-and two measures of response bias. We used the model to assess the effectiveness of BRCA Gist, an intelligent tutoring system designed to improve women's judgments and understanding of genetic risk for breast cancer. Participants were randomly assigned to the BRCA Gist intelligent tutoring system, the National Cancer Institute (NCI) Web pages, or a control group, and then they rated cases that had been developed using the Pedigree Assessment Tool and also vetted by medical experts. BRCA Gist participants demonstrated increased discriminability for all three risk categories, relative to the control group; the NCI group showed increased discriminability for two of the three levels. This result suggests that BRCA Gist best improved discriminability among genetic risk categories, and both BRCA Gist and the NCI website improved participants' ability to discriminate, rather than simply shifting their decision criterion. A spreadsheet that fits the model and compares parameters across the conditions can be downloaded from the Behavior Research Methods website and used in any research involving categorical responses.

The development and analysis of tutorial dialogues in AutoTutor Lite.

The goal of intelligent tutoring systems (ITS) that interact in natural language is to emulate the benefits that a well-trained human tutor provides to students, by interpreting student answers and appropriately responding in order to encourage elaboration. BRCA Gist is an ITS developed using AutoTutor Lite, a Web-based version of AutoTutor. Fuzzy-trace theory theoretically motivated the development of BRCA Gist, which engages people in tutorial dialogues to teach them about genetic breast cancer risk. We describe an empirical method to create tutorial dialogues and fine-tune the calibration of BRCA Gist's semantic processing engine without a team of computer scientists. We created five interactive dialogues centered on pedagogic questions such as "What should someone do if she receives a positive result for genetic risk of breast cancer?" This method involved an iterative refinement process of repeated testing with different texts and successively making adjustments to the tutor's expectations and settings in order to improve performance. The goal of this method was to enable BRCA Gist to interpret and respond to answers in a manner that best facilitated learning. We developed a method to analyze the efficacy of the tutor's dialogues. We found that BRCA Gist's assessment of participants' answers was highly correlated with the quality of the answers found by trained human judges using a reliable rubric. The dialogue quality between users and BRCA Gist predicted performance on a breast cancer risk knowledge test completed after exposure to the tutor. The appropriateness of BRCA Gist's feedback also predicted the quality of answers and breast cancer risk knowledge test scores.

Does the repressor coping style predict lower posttraumatic stress symptoms?

We tested whether a continuous measure of repressor coping style predicted lower posttraumatic stress disorder (PTSD) symptoms in 122 health care professionals serving in Operation Iraqi Freedom. Zero-order correlational analyses indicated that predeployment repressor coping scores negatively predicted postdeployment PTSD symptoms, r(s) = -0.29, p = 0.001, whereas predeployment Connor-Davidson Resilience Scale (CD-RISC) scores did not predict postdeployment PTSD symptoms, r(s) = -0.13, p = 0.14. However, predeployment trait anxiety was chiefly responsible for the association between repressor coping and PTSD symptom severity, r(s) = 0.38, p = 0.001. Four percent of the subjects qualified for a probable PTSD diagnosis. Although service members with relatively higher PTSD scores had lower repressor coping scores than did the other subjects, their level of predeployment anxiety was chiefly responsible for this relationship. Knowing someone's predeployment level of trait anxiety permits better prediction of PTSD symptoms among trauma-exposed service members than does knowing his or her level of repressive coping.