Understanding children's attention to traumatic dental injuries using eye‐tracking

Cho, Vanessa Y; Hsiao, Janet H.; Chan, Antoni B.; Ngo, Hien Chi; King, Nigel M.; Anthonappa, Robert P.

doi:10.1111/edt.12751

Cited by 11 publications

(8 citation statements)

References 18 publications

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“…15 Hence, future studies could employ eye movement analysis with hidden Markov models to overcome the limitations identified in the present study's view pattern and diagnostic competence aspects. 16,17,18 Using a think-aloud protocol, including a range of clinical images with no time constraints in viewing, and involving the entire cohort of students with no information bias strengthens the study findings. To our knowledge, the present study is the first to explore students' gaze behavior and diagnostic competence while viewing clinical images, thus, precluding possible direct comparisons.…”

Section: Discussionsupporting

confidence: 55%

Visual interpretation of clinical images among dental students using eye‐tracking technology

MS,

Cho,

FelsyPremila

et al. 2024

Journal of Dental Education

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BackgroundTele‐consultations are increasingly used for screening and diagnosis. Only a few studies have assessed dental students’ visual attention to clinical images.AimTo (i) determine dental students’ gaze behavior, visual fixations, and diagnostic competence while viewing clinical images, and (ii) explore potential opportunities to strengthen the teaching–learning approaches.DesignTobii Pro Nano‐device captured the eye‐tracking data for 65 dental undergraduate students in this cross‐sectional study. The predetermined areas of interest (AOI) for all five clinical photographs were uploaded onto Tobii software. All participants used a think‐aloud protocol with no restrictions to view time.ResultsA total of 325 clinical pictures were analyzed, and the average view time was 189.25 ± 76.90 s. Most participants started at the center of the image (three frontal photos), spent a significant share of their view time on prominent findings, did not follow a systematic pattern, and exhibited diagnostic incompetence. Also, most participants followed a “Z” viewing pattern (oscillating movement from left to right) for the remaining two pictures.ConclusionsSubjects frequently fixated on the prominent AOI, however, failed to make the correct diagnosis. Their view patterns revealed no sequential viewing. Therefore, emphasizing knowledge about common dental abnormalities and focusing on full coverage of clinical pictures can improve dental students’ diagnostic competence and view patterns.

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Section: Discussionsupporting

confidence: 55%

Visual interpretation of clinical images among dental students using eye‐tracking technology

MS,

Cho,

FelsyPremila

et al. 2024

Journal of Dental Education

Self Cite

View full text Add to dashboard Cite

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“…H. F. Chan et al, 2022; F. H. F. Chan, Suen, et al, 2020; Cho et al, 2022a, 2022b, 2022c), gaze perception (S. K. W. Chan et al, 2022), sustained attention to response (Lee et al, 2021), website viewing (Eckhardt et al, 2013), video viewing (Zheng, Ye, & Hsiao, 2022), scene perception (Hsiao, Lan, et al, 2021), reading (Liao et al, 2022), and visual search (Hsiao, Chan, et al, 2021).…”

Section: Methodsmentioning

confidence: 99%

Differential audiovisual information processing in emotion recognition: An eye-tracking study.

Zheng¹,

Hsiao²

2023

Emotion

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Recent research has suggested that dynamic emotion recognition involves strong audiovisual association; that is, facial or vocal information alone automatically induces perceptual processes in the other modality. We hypothesized that different emotions may differ in the automaticity of audiovisual association, resulting in differential audiovisual information processing. Participants judged the emotion of a talking-head video under audiovisual, video-only (with no sound), and audio-only (with a static neutral face) conditions. Among the six basic emotions, disgust had the largest audiovisual advantage over the unimodal conditions in recognition accuracy. In addition, in the recognition of all the emotions except for disgust, participants' eye-movement patterns did not change significantly across the three conditions, suggesting mandatory audiovisual information processing. In contrast, in disgust recognition, participants' eye movements in the audiovisual condition were less eyes-focused than the video-only condition and more eyes-focused than the audio-only condition, suggesting that audio information in the audiovisual condition interfered with eye-movement planning for important features (eyes) for disgust. In addition, those whose eye-movement pattern was affected less by concurrent disgusted voice information benefited more in recognition accuracy. Disgust recognition is learned later in life and thus may involve a reduced amount of audiovisual associative learning. Consequently, audiovisual association in disgust recognition is less automatic and demands more attentional resources than other emotions. Thus, audiovisual information processing in emotion recognition depends on the automaticity of audiovisual association of the emotion resulting from associative learning. This finding has important implications for real-life emotion recognition and multimodal learning.

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“…The hidden states of an HMM correspond to the ROIs, and the observable fixation data is modeled as arising from an underlying dynamic process of the sequence of ROIs viewed (Chan et al, 2018;Chuk, Crookes, et al, 2017). Since our task includes a natural set of 9 ROIs of each trial, we predefined the spatial ROIs using the area of each face's location defined by the center coordinate and a radius of 90 pixels (i.e., 4 SD of a 2-dimensional Gaussian distribution) (Cho et al, 2022a;Cho et al, 2022b;Chuk et al, 2019). The prior probabilities across the 9 ROIs were initialized as a flat distribution.…”

Section: Eye Movement Analysis With Hidden Markov Models (Emhmm)mentioning

confidence: 99%

How is Emotional Evidence from Multiple Sources Used in Perceptual Decision Making?

Ngai

Hsiao

Luhmann

et al. 2023

Preprint

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Judging the overall emotional nature of a scene often requires us to deliberately integrate pieces of evidence that range from neutral to emotional in nature. Research so far has focused on relatively rapid decisions. Hence, how evidence is valuated and sampled given ample time, and the precise computations involved in integrating emotion-related evidence to form an overall perceptual decision remain unclear. Further, it is unclear how this process is influenced by decision-makers’ endogenous (voluntary) attention directed towards emotional evidence. In two experiments, human subjects (N=33 and N = 40) viewed arrays of faces with expressions ranging from extremely fearful to extremely happy. They decided whether the faces were more fearful or happier on average in the absence (Experiment 1) and presence (Experiment 2) of endogenous attention directed towards the fearful or happy faces. Results showed that subjects evaluated the same emotional faces differently depending on the face array context. While they attentionally sampled extreme emotional evidence more, they did not weigh it higher or lower in their decision making. Rather, their decision-making strategy was best modeled by weighing all pieces of context-dependent subjective evaluated emotional evidence equally. Furthermore, endogenous attention influenced sampling of the emotional evidence, but the decision-making strategy remained unchanged. In conclusion, the findings show that when forming a judgment about multiple emotional stimuli without time pressure, humans weigh multiple pieces of subjectively valuated context-dependent evidence equally. These findings elucidate specific computational mechanisms of emotion-related decision making, shedding light on the mechanisms of normal and pathological affective decisions.

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Understanding children's attention to traumatic dental injuries using eye‐tracking

Cited by 11 publications

References 18 publications

Visual interpretation of clinical images among dental students using eye‐tracking technology

Visual interpretation of clinical images among dental students using eye‐tracking technology

Differential audiovisual information processing in emotion recognition: An eye-tracking study.

How is Emotional Evidence from Multiple Sources Used in Perceptual Decision Making?

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