PURPOSE: To develop and evaluate a measure of cancer genetics knowledge relevant to multigene panel testing. METHODS: The instrument was developed using systematic input from a national panel of genetics experts, acceptability evaluation by patient advocates, and cognitive testing. Twenty-four candidate items were completed by 591 breast or gynecological patients who had undergone genetic counseling and multigene panel testing in the past 18 months. A unidimensional item response theory model was fit with a mix of 2-parameter logistic nested response (2 plnrm) and 2-parameter logistic (2 pl) items. RESULTS: Key domains addressing cancer genetics knowledge were found to be overlapping. Of the 24 candidate items, 8 items were removed due to poor discrimination or local dependence. The remaining 16 items had good fit (RMSEA = 0.045, CFI = 0.946) and discrimination parameters ranging from 0.49 to 1.60. The items specified as 2 plnrm distinguish between those answering incorrect versus don't know, with discrimination ranging from 0.51 to 1.02. Information curves were highest among those with lower knowledge. CONCLUSION: KnowGene is a rigorously developed and effective measure of knowledge after cancer genetic counseling and multigene panel testing. PRACTICE IMPLICATIONS: Measuring knowledge in a systematic way will inform practice and research initiatives in cancer genetics.
PURPOSE: To develop and evaluate a measure of cancer genetics knowledge relevant to multigene panel testing. METHODS: The instrument was developed using systematic input from a national panel of genetics experts, acceptability evaluation by patient advocates, and cognitive testing. Twenty-four candidate items were completed by 591 breast or gynecological patients who had undergone genetic counseling and multigene panel testing in the past 18 months. A unidimensional item response theory model was fit with a mix of 2-parameter logistic nested response (2 plnrm) and 2-parameter logistic (2 pl) items. RESULTS: Key domains addressing cancer genetics knowledge were found to be overlapping. Of the 24 candidate items, 8 items were removed due to poor discrimination or local dependence. The remaining 16 items had good fit (RMSEA = 0.045, CFI = 0.946) and discrimination parameters ranging from 0.49 to 1.60. The items specified as 2 plnrm distinguish between those answering incorrect versus don't know, with discrimination ranging from 0.51 to 1.02. Information curves were highest among those with lower knowledge. CONCLUSION: KnowGene is a rigorously developed and effective measure of knowledge after cancer genetic counseling and multigene panel testing. PRACTICE IMPLICATIONS: Measuring knowledge in a systematic way will inform practice and research initiatives in cancer genetics.
Authors: C Sloane Furniss; Matthew B Yurgelun; Chinedu Ukaegbu; Pamela E Constantinou; Catherine C Lafferty; Eliana R Talcove-Berko; Alison N Schwartz; Jill E Stopfer; Meghan Underhill-Blazey; Barbara Kenner; Scott H Nelson; Sydney Okumura; Sherman Law; Alicia Y Zhou; Tara B Coffin; Nicolette J Rodriguez; Hajime Uno; Allyson J Ocean; Florencia McAllister; Andrew M Lowy; Scott M Lippman; Alison P Klein; Lisa Madlensky; Gloria M Petersen; Judy E Garber; Michael G Goggins; Anirban Maitra; Sapna Syngal Journal: Cancer Prev Res (Phila) Date: 2021-10-08
Authors: Rachel A Pozzar; Fangxin Hong; Niya Xiong; Jill E Stopfer; Manan M Nayak; Meghan Underhill-Blazey Journal: Fam Cancer Date: 2021-03-10 Impact factor: 2.375
Authors: Dana Watnick; Jacqueline A Odgis; Sabrina A Suckiel; Katie M Gallagher; Nehama Teitelman; Katherine E Donohue; Bruce D Gelb; Eimear E Kenny; Melissa P Wasserstein; Carol R Horowitz; Siobhan M Dolan; Laurie J Bauman Journal: HGG Adv Date: 2021-02-03
Authors: Deborah Cragun; Jason Beckstead; Meagan Farmer; Gillian Hooker; Marleah Dean; Ellen Matloff; Sonya Reid; Ann Tezak; Anne Weidner; Jennifer G Whisenant; Tuya Pal Journal: BMC Cancer Date: 2021-10-13 Impact factor: 4.430
Authors: Kimberly A Kaphingst; Wendy Kohlmann; Rachelle Lorenz Chambers; Melody S Goodman; Richard Bradshaw; Priscilla A Chan; Daniel Chavez-Yenter; Sarah V Colonna; Whitney F Espinel; Jessica N Everett; Amanda Gammon; Eric R Goldberg; Javier Gonzalez; Kelsi J Hagerty; Rachel Hess; Kelsey Kehoe; Cecilia Kessler; Kadyn E Kimball; Shane Loomis; Tiffany R Martinez; Rachel Monahan; Joshua D Schiffman; Dani Temares; Katie Tobik; David W Wetter; Devin M Mann; Kensaku Kawamoto; Guilherme Del Fiol; Saundra S Buys; Ophira Ginsburg Journal: BMC Health Serv Res Date: 2021-06-02 Impact factor: 2.655