Memory bias in observer-performance literature

Abstract. The objective of our study was to determine how authors of published observer–performance experiments dealt with memory bias in study design. We searched American Journal of Roentgenology online and Radiology using “observer study” and “observer performance.” We included articles from 1970 or later that reported an observer performance experiment using human observers. We recorded the methods used by the authors to order presentation of the conditions being tested and images within sets for viewing. We recorded use and length of any time gap between viewings. We included 110 experiments. Forty-five used methods not subject to memory bias. Of 68 remaining experiments, 30 (44.1%) ordered the viewing of tested conditions to decrease memory bias. Fifteen (22.1%) ordered the tested conditions in ways that may create memory bias. Eleven (16.2%) intermixed the tested conditions. Forty-three (63.2%) used random or pseudorandom ordering of images within sets. Forty-six (67.6%) used a time gap (median 14 days) between viewings. Six (8.8%) did not use a time gap. Thirty-six (52.9%) did not indicate what methods they used in at least one studied parameter. Therefore, we conclude that 22.1% of the experiments could improve their methods of ordering tested conditions. Completeness of reporting could be improved by including more details regarding methods of ameliorating memory bias.

[1]  Alexander Schick,et al.  Comparison of dual-energy subtraction and electronic bone suppression combined with computer-aided detection on chest radiographs: effect on human observers' performance in nodule detection. , 2013, AJR. American journal of roentgenology.

[2]  Mathias Prokop,et al.  Flat-panel display (LCD) versus high-resolution gray-scale display (CRT) for chest radiography: an observer preference study. , 2005, AJR. American journal of roentgenology.

[3]  Tamara Miner Haygood,et al.  Radiologists remember mountains better than radiographs, or do they? , 2015, Journal of medical imaging.

[4]  Alexandros Georgakopoulos,et al.  Quantitative evaluation of the memory bias effect in ROC studies with PET/CT , 2012, Medical Imaging.

[5]  Hilde Bosmans,et al.  The effect of image processing on the detection of cancers in digital mammography. , 2014, AJR. American journal of roentgenology.

[6]  K. Doi,et al.  Radiologists' performance for differentiating benign from malignant lung nodules on high-resolution CT using computer-estimated likelihood of malignancy. , 2004, AJR. American journal of roentgenology.

[7]  Thomas K. Landauer,et al.  How Much do People Remember? Some Estimates of the Quantity of Learned Information in Long-Term Memory , 1986, Cogn. Sci..

[8]  Raymond S. Nickerson,et al.  A note on long-term recognition memory for pictorial material , 1968 .

[9]  J. S. Keene,et al.  Diagnosis of meniscal tears of the knee with MR imaging: effect of observer variation and sample size on sensitivity and specificity. , 1993, AJR. American journal of roentgenology.

[10]  D. Rennie,et al.  Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative , 2003, BMJ : British Medical Journal.

[11]  Kunio Doi,et al.  Improved detection of small lung cancers with dual-energy subtraction chest radiography. , 2008, AJR. American journal of roentgenology.

[12]  Johannes B Reitsma,et al.  STARD 2015 guidelines for reporting diagnostic accuracy studies: explanation and elaboration , 2016, BMJ Open.

[13]  B. Baxter,et al.  The development of radiologic schemata through training and experience. A preliminary communication. , 1985, Investigative radiology.

[14]  Tamara Miner Haygood,et al.  The "memory effect" for repeated radiologic observations. , 2011, AJR. American journal of roentgenology.

[15]  C E Metz,et al.  Some practical issues of experimental design and data analysis in radiological ROC studies. , 1989, Investigative radiology.

[16]  N. Obuchowski,et al.  Comparing the performance of mammographic enhancement algorithms: a preference study. , 2000, AJR. American journal of roentgenology.

[17]  N. Petrick,et al.  CT colonography with computer-aided detection as a second reader: observer performance study. , 2008, Radiology.

[18]  Jan Stam,et al.  Observer variation in MRI evaluation of patients suspected of lumbar disk herniation. , 2005, AJR. American journal of roentgenology.

[19]  Gregory T Sica,et al.  Bias in research studies. , 2006, Radiology.