Effects of contrasting category, conjoint frequency and typicality on categorization

Das-Smaal, E.A.; Swart, J.H. De

doi:10.1016/0001-6918(86)90003-x

Cited by 7 publications

(5 citation statements)

References 11 publications

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“…These results support numerous studies that have found that examples of stimuli that resemble their prototypes are responded to more quickly. 7 8 9 …”

Section: Discussionmentioning

confidence: 99%

“…At the outset, it was expected that experienced clinicians would be able to focus on the relevant details in the images and correctly categorize more boundary images in the no-cue and prototypical-cue condition, because previous research suggests that learning with exemplary diversity facilitates categorization of novel examples that deviate more from the category prototype. 8 9 24 25 26 27 The clinicians had the advantage of years of learning from multiple examples; thus, they should have been able to organize the FHR variability categories around mental prototypes acquired through their experience and outperform the novices at categorizing boundary images. However, the results suggest that categorization of the FHR images may require more perceptual processing, guided by how similar each example is to the learned prototype of each category, making it difficult to categorize boundary images when needing to rely on memory.…”

Section: Discussionmentioning

confidence: 99%

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Categorizing Fetal Heart Rate Variability with and without Visual Aids

Ashdown

2016

AJP Rep

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Objective This study examined the ability of clinicians to correctly categorize images of fetal heart rate (FHR) variability with and without the use of exemplars. Study Design A sample of 33 labor and delivery clinicians inspected static FHR images and categorized them into one of four categories defined by the National Institute of Child Health and Human Development (NICHD) based on the amount of variability within absent, minimal, moderate, or marked ranges. Participants took part in three conditions: two in which they used exemplars representing FHR variability near the center or near the boundaries of each range, and a third control condition with no exemplars. The data gathered from clinicians were compared with those from a previous study using novices. Results Clinicians correctly categorized more images when the FHR variability fell near the center rather than the boundaries of each range, F (1,32) = 71.69, p < 0.001, partial η2 = 0.69. They also correctly categorized more images when exemplars were available, F (2,64) = 5.44, p = 0.007, partial η2 = 0.15. Compared with the novices, the clinicians were more accurate and quicker in their category judgments, but this difference was limited to the condition without exemplars. Conclusion The results suggest that categorizing FHR variability is more difficult when the examples fall near the boundaries of each NICHD-defined range. Thus, clinicians could benefit from training with visual aids to improve judgments about FHR variability and potentially enhance safety in labor and delivery.

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“…These results support numerous studies that have found that examples of stimuli that resemble their prototypes are responded to more quickly. 7 8 9 …”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Categorizing Fetal Heart Rate Variability with and without Visual Aids

Ashdown

2016

AJP Rep

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“…The results show that clinicians correctly categorized significantly more prototypical images compared with the boundary images, which supports other findings and suggests that examples of stimuli that are similar to their prototypes are easier to categorize. 8,9,17 The participants also took longer to respond to the boundary images as compared with the prototypical images. These results support numerous studies that have found that examples of stimuli that resemble their prototypes are responded to more quickly.…”

Section: Image Typementioning

confidence: 99%

“…At the outset, it was expected that experienced clinicians would be able to focus on the relevant details in the images and correctly categorize more boundary images in the no-cue and prototypical-cue condition, because previous research suggests that learning with exemplary diversity facilitates categorization of novel examples that deviate more from the category prototype. 8,9,[24][25][26][27] The clinicians had the advantage of years of learning from multiple examples; thus, they should have been able to organize the FHR variability categories around mental prototypes acquired through their experience and outperform the novices at categorizing boundary images. However, the results suggest that categorization of the FHR images may require more perceptual processing, guided by how similar each example is to the learned prototype of each category, making it difficult to categorize boundary images when needing to rely on memory.…”

Section: 14mentioning

confidence: 99%

“…Stimuli that deviate further from the prototype become more difficult to categorize. [7][8][9] Stimuli falling near a boundary between two categories are more ambiguous and can impede the judgment process. Research also shows that when categorizing ambiguous stimuli, cues, and visual aids can facilitate performance because they direct attention to salient information.…”

mentioning

confidence: 99%

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Categorizing Fetal Heart Rate Variability with and without Visual Aids

Ashdown

Scerbo

Belfore

et al. 2015

Proceedings of the Human Factors and Ergonomics Society Annual

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Analysis of the fetal heart rate (FHR) is important for monitoring fetal wellbeing. Although the NICHD classification system provides a framework for FHR assessment, there is still potential for clinicians to misclassify FHR variability. This can result in the inappropriate operative intervention (i.e., cesarean procedures) and even increase the cost of obstetrics and malpractice insurance. 2,3Keywords ► categorization ► cues ► clinical judgment ► exemplars ► fetal heart rate variability AbstractObjective This study examined the ability of clinicians to correctly categorize images of fetal heart rate (FHR) variability with and without the use of exemplars. Study Design A sample of 33 labor and delivery clinicians inspected static FHR images and categorized them into one of four categories defined by the National Institute of Child Health and Human Development (NICHD) based on the amount of variability within absent, minimal, moderate, or marked ranges. Participants took part in three conditions: two in which they used exemplars representing FHR variability near the center or near the boundaries of each range, and a third control condition with no exemplars. The data gathered from clinicians were compared with those from a previous study using novices.Results Clinicians correctly categorized more images when the FHR variability fell near the center rather than the boundaries of each range, F (1,32) ¼ 71.69, p < 0.001, partial η2 ¼ 0.69. They also correctly categorized more images when exemplars were available, F (2,64) ¼ 5.44, p ¼ 0.007, partial η2 ¼ 0.15. Compared with the novices, the clinicians were more accurate and quicker in their category judgments, but this difference was limited to the condition without exemplars. Conclusion The results suggest that categorizing FHR variability is more difficult when the examples fall near the boundaries of each NICHD-defined range. Thus, clinicians could benefit from training with visual aids to improve judgments about FHR variability and potentially enhance safety in labor and delivery.

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Typicality effects in artificial categories: Is there a hemisphere difference?

Richards

Chiarello

1990

Brain and Language

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Effects of contrasting category, conjoint frequency and typicality on categorization

Cited by 7 publications

References 11 publications

Categorizing Fetal Heart Rate Variability with and without Visual Aids

Categorizing Fetal Heart Rate Variability with and without Visual Aids

Categorizing Fetal Heart Rate Variability with and without Visual Aids

Typicality effects in artificial categories: Is there a hemisphere difference?

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