---
_id: '6986'
abstract:
- lang: eng
  text: "Background: Artificial intelligence–based skin cancer screening apps (AISCSAs)
    offer diagnostic potential but face limited adoption. App store cues, such as
    ratings, may influence acceptance; yet, little is known about how users cognitively
    process app store information in high-stakes health contexts. To address this
    gap, eye-tracking was used to measure visual attention while participants evaluated
    a mock AISCSA app store listing.\r\n\r\nObjective: This study aimed to test whether
    a single negative rating captures visual attention and whether an extended technology
    acceptance model (TAM) can predict behavioral intention to use (BI) AISCSAs.\r\n\r\nMethods:
    Participants (N=76) evaluated a mock app store listing for an AISCSA under positive
    (n=42) or negative (n=34) rating conditions while their eye movements were recorded.
    Analyses combined fixation durations in defined areas of interest (AOIs) with
    self-reported measures of perceived usefulness (PU), perceived ease of use (PEOU),
    trust, BI, willingness to pay, and the self-rated importance of app attributes.\r\n\r\nResults:
    Normalized fixation durations (seconds per square pixel) revealed the highest
    attention to the description (0.166 s/px2), followed by the reviews (0.11 s/px2)
    and the ratings (0.04 s/px2), while the price and the data protection received
    the least attention. Of the 5 self-rated app attributes, only reviews correlated
    positively with fixation durations on the reviews-AOI (r=0.28; P=.01). Rating
    valence had no significant effect on gaze patterns, PU, PEOU, trust, BI, or willingness
    to pay (all Ps>.05). However, PEOU (P=.001), PU (P<.001), and trust (P<.001) were
    significantly correlated with BI.\r\n\r\nConclusions: Although the expected attentional
    capture effect of the negative rating was not observed, the weak or nonexistent
    associations between fixation durations on the AOIs and the self-rated importance
    of app attributes suggest that eye-tracking captures aspects of information processing
    that are not directly reflected in self-reported evaluations. These findings indicate
    that eye-tracking provides a more direct approximation of actual user behavior
    by revealing implicit attentional processes beyond what is captured by questionnaires.
    While the technology acceptance model constructs and trust predicted BI, rating
    valence alone did not affect acceptance or gaze behavior. In high-stakes health
    contexts, textual information may outweigh rating valence in driving adoption.
    Future research should explore conditions under which rating valence matters,
    including more extreme rating contrasts, variations in accompanying review texts,
    and the influence of individual differences such as preexisting attitudes toward
    artificial intelligence and levels of artificial intelligence literacy."
author:
- first_name: Inga
  full_name: Jagemann, Inga
  id: '252878'
  last_name: Jagemann
  orcid: 0000-0002-3468-3423
  orcid_put_code_url: https://api.orcid.org/v2.0/0000-0002-3468-3423/work/217580444
- first_name: Sabrina
  full_name: Hegner, Sabrina
  last_name: Hegner
- first_name: Gerrit
  full_name: Hirschfeld, Gerrit
  id: '234690'
  last_name: Hirschfeld
  orcid: 0000-0003-2143-4564
  orcid_put_code_url: https://api.orcid.org/v2.0/0000-0003-2143-4564/work/217580445
citation:
  alphadin: '<span style="font-variant:small-caps;">Jagemann, Inga</span> ; <span
    style="font-variant:small-caps;">Hegner, Sabrina</span> ; <span style="font-variant:small-caps;">Hirschfeld,
    Gerrit</span>: The Role of Rating Valence in AI Skin Cancer App Acceptance: Eye-Tracking
    and Questionnaire Study. In: <i>JMIR Human Factors</i> Bd. 13, JMIR Publications
    Inc. (2026), S. e93489–e93489'
  ama: 'Jagemann I, Hegner S, Hirschfeld G. The Role of Rating Valence in AI Skin
    Cancer App Acceptance: Eye-Tracking and Questionnaire Study. <i>JMIR Human Factors</i>.
    2026;13:e93489-e93489. doi:<a href="https://doi.org/10.2196/93489">10.2196/93489</a>'
  apa: 'Jagemann, I., Hegner, S., &#38; Hirschfeld, G. (2026). The Role of Rating
    Valence in AI Skin Cancer App Acceptance: Eye-Tracking and Questionnaire Study.
    <i>JMIR Human Factors</i>, <i>13</i>, e93489–e93489. <a href="https://doi.org/10.2196/93489">https://doi.org/10.2196/93489</a>'
  bibtex: '@article{Jagemann_Hegner_Hirschfeld_2026, title={The Role of Rating Valence
    in AI Skin Cancer App Acceptance: Eye-Tracking and Questionnaire Study}, volume={13},
    DOI={<a href="https://doi.org/10.2196/93489">10.2196/93489</a>}, journal={JMIR
    Human Factors}, publisher={JMIR Publications Inc.}, author={Jagemann, Inga and
    Hegner, Sabrina and Hirschfeld, Gerrit}, year={2026}, pages={e93489–e93489} }'
  chicago: 'Jagemann, Inga, Sabrina Hegner, and Gerrit Hirschfeld. “The Role of Rating
    Valence in AI Skin Cancer App Acceptance: Eye-Tracking and Questionnaire Study.”
    <i>JMIR Human Factors</i> 13 (2026): e93489–e93489. <a href="https://doi.org/10.2196/93489">https://doi.org/10.2196/93489</a>.'
  ieee: 'I. Jagemann, S. Hegner, and G. Hirschfeld, “The Role of Rating Valence in
    AI Skin Cancer App Acceptance: Eye-Tracking and Questionnaire Study,” <i>JMIR
    Human Factors</i>, vol. 13, pp. e93489–e93489, 2026.'
  mla: 'Jagemann, Inga, et al. “The Role of Rating Valence in AI Skin Cancer App Acceptance:
    Eye-Tracking and Questionnaire Study.” <i>JMIR Human Factors</i>, vol. 13, JMIR
    Publications Inc., 2026, pp. e93489–e93489, doi:<a href="https://doi.org/10.2196/93489">10.2196/93489</a>.'
  short: I. Jagemann, S. Hegner, G. Hirschfeld, JMIR Human Factors 13 (2026) e93489–e93489.
date_created: 2026-06-11T21:15:29Z
date_updated: 2026-06-13T08:39:23Z
doi: 10.2196/93489
intvolume: '        13'
language:
- iso: eng
main_file_link:
- open_access: '1'
oa: '1'
page: e93489-e93489
publication: JMIR Human Factors
publication_identifier:
  eissn:
  - 2292-9495
publication_status: published
publisher: JMIR Publications Inc.
status: public
title: 'The Role of Rating Valence in AI Skin Cancer App Acceptance: Eye-Tracking
  and Questionnaire Study'
type: journal_article
user_id: '220548'
volume: 13
year: '2026'
...