"Where is history": Toward Designing a Voice Assistant to help Older Adults locate Interface Features quickly

Yu, Ja Eun; Parde, Natalie; Chattopadhyay, Debaleena

doi:10.1145/3544548.3581447

Cited by 22Technology Use by Older AdultsUsability and User Interface DesignDigital Accessibility for Disabilities

"Where is history": Toward Designing a Voice Assistant to help Older Adults locate Interface Features quickly

Open access

Yu, Ja Eun, Parde, Natalie, Chattopadhyay, Debaleena·2023·Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

DOI 10.1145/3544548.3581447

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Abstract

Older adults often struggle to locate a function quickly in feature-rich user interfaces (UIs). Mobile UIs not only pack a ton of features in a small screen but also get frequent updates to their visual layouts—thereby exacerbating the problem. This paper explores a design solution where users could search for a UI feature using spoken-word queries. We investigated: 1) what type of questions older users ask when facing interaction challenges in unfamiliar scenarios, 2) how those query types compare with younger users’ inquiries, and 3) how older adults use a voice assistant design probe in a Wizard-of-Oz (WoZ) study. Results reveal five query types when verbally articulating interaction issues: validation, directed and undirected informational, navigational, and conceptual. In the WoZ study, older users typically asked for help following a series of non-unique or off-task feature selections (n = 13/15), and in 77% of those instances, they completed the task in the next interaction.

Integrity signals

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Crossref · 10.1145/3544548.3581447

Cites

70 of 70 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

22 of 88 cited sources checked · 9 supported · 0 flagged · accuracy not yet measured

Premisecitation
Older adults fixate more on the central part of the screen than the peripheral top and left parts, where many mobile interface menus often reside.
“Studies have also shown that older adults fxate more on the central part of the screen than the peripheral top and left parts, where many mobile interface menus often reside [37,50].”
Quote in the paperSubstantial claim1 of 2 sources checked
- cites [37] 37. Qingchuan Li and Yan Luximon. 2020. Older adults' use of mobile device: us- ability challenges while navigating various interfaces. Behaviour & Information Technology 39, 8 (2020), 837-861. source
  In “Designing for menu-oriented navigation” (page unavailable), the study says participants focused more on content in the middle of the screen and had difficulty directing attention to tab menus alongside it. It does not establish that they fixated less on both the top and left parts of the screen; the same section reports that top-placed tabs improved menu noticeability. (LLM, conf=0.85)
  Experimental — accuracy not yet measured
- cites [50] 50. Jennifer C Romano Bergstrom, Erica L Olmsted-Hawala, and Matt E Jans. 2013. Age-related diferences in eye tracking and usability performance: website us- ability for older adults. International Journal of Human-Computer Interaction 29, 8 (2013), 541-548. source
Findingown data
Study 1 participants' MDPQ-14 scores were not significantly different (p = 0.51) from MDPQ-14 scores reported in the literature from 60-plus adults (Mdn = 41.5, M = 41.3).
“They were not signifcantly diferent (p = 0.51) from MDPQ-14 scores reported in the literature from 60-plus adults (Mdn= 41.5, M = 41.3)[46]”
Quote in the paperNot a substantial claim1 of 1 sources checked
- cites [46] 46. Andraž Petrovčič, Walter R Boot, Tomaž Burnik, and Vesna Vesna Dolničar. 2019. Improving the Measurement of Older Adults' Mobile Device Profciency: Results and Implications from a Study of Older Adult Smartphone Users. IEEE Access 7 (2019), 150412-150422. source
  The MDPQ-14 short-form and Criterion Validity sections say the paper constructed the MDPQ-14 and calculated scores for its participants. Our copy does not report the cited median of 41.5 or mean of 41.3; searches for both values and for MDPQ-14 score summaries found no matching passage. The p = 0.51 comparison concerns the citing study’s participants, not a comparison reported by this source. (LLM, conf=0.72)
  Experimental — accuracy not yet measured
Premisecitation
Even tens of features and hidden navigation menu structures can cause usability issues.
“Although mobile apps do not have hundreds of features as found in desktop interfaces, even tens of features and hidden navigation menu structures can cause usability issues [37].”
Quote in the paperSubstantial claim1 of 1 sources checked
- cites [37] 37. Qingchuan Li and Yan Luximon. 2020. Older adults' use of mobile device: us- ability challenges while navigating various interfaces. Behaviour & Information Technology 39, 8 (2020), 837-861. source
  The Results of activity analysis and Designing for menu-oriented navigation sections report usability problems with side-drawer menus and their hamburger-button entry point among older adults. The paper does not establish that apps with ‘tens of features’ cause such problems, and its findings do not directly cover users generally. (LLM, conf=0.85)
  Experimental — accuracy not yet measured
Premisecitation
Not being able to locate the correct features within a reasonable amount of time at either the beginning or during a task constitutes the core struggle of older adults when trying to explore and use a feature-rich UI.
“Most recently, it has been observed that not being able to locate the correct features-within a reasonable amount of time-at either the beginning or during a task constitutes the core struggle of older adults when trying to explore and use a feature-rich UI [37,45].”
Quote in the paperSubstantial claim1 of 2 sources checked
- cites [37] 37. Qingchuan Li and Yan Luximon. 2020. Older adults' use of mobile device: us- ability challenges while navigating various interfaces. Behaviour & Information Technology 39, 8 (2020), 837-861. source
  The Results of activity analysis and the section on assisted navigation buttons report that older adults struggled to find entry points and target buttons, supporting the feature-location aspect. The Tasks section says participants had no time limit, and the paper does not establish failure to locate features within a reasonable time, at either task stage, as the core struggle of using a feature-rich UI. Page numbers were not provided in our copy. (LLM, conf=0.83)
  Experimental — accuracy not yet measured
- cites [45] 45. Carolyn Pang, Zhiqin Collin Wang, Joanna McGrenere, Rock Leung, Jiamin Dai, and Karyn Mofatt. 2021. Technology Adoption and Learning Preferences for Older Adults: Evolving Perceptions, Ongoing Challenges, and Emerging Design Opportunities. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 1-13. source
Premisecitation
There is a need for both tightly-coupled and loosely-coupled support for older users.
“Studies show that there is a need for both these types of support for older users: tightly- [25] and loosely-coupled [45,69] with the optimal interaction path.”
Quote in the paperNot a substantial claim1 of 3 sources checked
- cites [25] 25. Xiaofu Jin, Xiaozhu Hu, Xiaoying Wei, and Mingming Fan. 2022. Synapse: Interactive Guidance by Demonstration with Trial-and-Error Support for Older Adults to Use Smartphone Apps. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 6, 3 (2022), 1-24. source
  The introduction (p. 3) describes support that lets older adults depart from a demonstrated interaction path, then helps them recover. The description of Basic and Trial-and-Error modes (p. 1) also shows both step-by-step guidance and freer exploration. This supports the need for different degrees of guidance, but our copy does not establish that the demonstrated path is optimal. (LLM, conf=0.82)
  Experimental — accuracy not yet measured
- cites [45] 45. Carolyn Pang, Zhiqin Collin Wang, Joanna McGrenere, Rock Leung, Jiamin Dai, and Karyn Mofatt. 2021. Technology Adoption and Learning Preferences for Older Adults: Evolving Perceptions, Ongoing Challenges, and Emerging Design Opportunities. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 1-13. source
- cites [69] 69. Ja Eun Yu and Debaleena Chattopadhyay. 2020. "Maps are hard for me": How Older Adults Struggle with Mobile Maps. In The 22nd International ACM SIGAC- CESS Conference on Computers and Accessibility. in press. source

Interpretationown data
Study 1 participants' mobile device proficiency was similar to people considered older adults elsewhere in the literature.
“which suggests that the mobile device profciency of our participants were similar to people considered older adults elsewhere in the literature.”
Quote in the paperNot a substantial claim1 of 1 sources checked
- cites [46] 46. Andraž Petrovčič, Walter R Boot, Tomaž Burnik, and Vesna Vesna Dolničar. 2019. Improving the Measurement of Older Adults' Mobile Device Profciency: Results and Implications from a Study of Older Adult Smartphone Users. IEEE Access 7 (2019), 150412-150422. source
  The Subjects section (page unavailable) describes a sample of 50 smartphone users aged 60+, and the Background section describes how their mobile-device proficiency was measured. The paper therefore provides an older-adult point of reference, but our copy does not establish that the citing study’s participants had similar proficiency. (LLM, conf=0.78)
  Experimental — accuracy not yet measured
Premisecitation
App navigation issues have been reported repeatedly when studying how older adults use feature-rich mobile interfaces.
“In particular, app navigation issues have been reported repeatedly when studying how older adults use feature-rich mobile interfaces [37,38].”
Quote in the paperSubstantial claim1 of 2 sources checked
- cites [37] 37. Qingchuan Li and Yan Luximon. 2020. Older adults' use of mobile device: us- ability challenges while navigating various interfaces. Behaviour & Information Technology 39, 8 (2020), 837-861. source
- cites [38] 38. Qingchuan Li, Yan Luximon, et al. 2018. Understanding older adults' post- adoption usage behavior and perceptions of mobile technology. (2018).
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Premisecitation
Older adults would prefer to learn about new technology from and with family and friends.
“They also would prefer to learn about new technology from and with family and friends [28,45].”
Quote in the paperNot a substantial claim1 of 2 sources checked
- cites [28] 28. Brittne Kakulla. 2021. 2021 Tech Trends and the 50-Plus: Top 10 Biggest Trends. Retrieved December 12, 2022 from https://doi.org/10.26419/res.00420.011. source
- cites [45] 45. Carolyn Pang, Zhiqin Collin Wang, Joanna McGrenere, Rock Leung, Jiamin Dai, and Karyn Mofatt. 2021. Technology Adoption and Learning Preferences for Older Adults: Evolving Perceptions, Ongoing Challenges, and Emerging Design Opportunities. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 1-13. source
Premisecitation
Failing to locate the correct feature even once during a task often leads to looping, several back-and-forths, and ultimately task abandonment and user frustration.
“Although this number might seem low, studies have shown that failing to locate the correct feature even once during a task often leads to looping, several back-andforths, and ultimately task abandonment and user frustration [37,69].”
Quote in the paperSubstantial claim1 of 2 sources checked
- cites [37] 37. Qingchuan Li and Yan Luximon. 2020. Older adults' use of mobile device: us- ability challenges while navigating various interfaces. Behaviour & Information Technology 39, 8 (2020), 837-861. source
  The Results of activity analysis (page unavailable) describe participants searching in the wrong places or switching tabs when they could not locate buttons, and report some resulting action failures. They also describe several forward-and-backward flips, but not as a demonstrated sequence from one missed feature to task abandonment. The cited paper does not establish that a single failure to locate a feature often causes that sequence or user frustration. (LLM, conf=0.85)
  Experimental — accuracy not yet measured
- cites [69] 69. Ja Eun Yu and Debaleena Chattopadhyay. 2020. "Maps are hard for me": How Older Adults Struggle with Mobile Maps. In The 22nd International ACM SIGAC- CESS Conference on Computers and Accessibility. in press. source
Findingown data
In 77% of those instances, older users completed the task in the next interaction.
“and in 77% of those instances, they completed the task in the next interaction.”
Quote in the paperSubstantial claim
Findingown data
The most common type of questions asked by younger users was conceptual.
“In contrast, the most common type of questions asked by younger users was conceptual.”
Quote in the paperNot a substantial claim
Findingown data
Older users asked significantly more directed informational questions than younger users.
“For example, older users asked signifcantly more directed informational questions (e.g.,”
Quote in the paperSubstantial claim
Findingown data
Older users asked significantly more validation questions than their younger counterparts (U = 46, p = 0.004, r = 0.6).
“we found that older users asked signifcantly more validation questions than their younger counterparts (U = 46, p = 0.004, r = 0.6)”
Quote in the paperSubstantial claim
Findingown data
The most common type of questions that older adults asked was validation, followed by informational, directed and navigational.
“The most common type of questions that older adults asked was validation, followed by informational, directed and navigational.”
Quote in the paperSubstantial claim
Findingown data
In the WoZ study, older users typically asked for help following a series of non-unique or off-task feature selections (n = 13/15).
“In the WoZ study, older users typically asked for help following a series of non-unique or of-task feature selections (n = 13/15)”
Quote in the paperNot a substantial claim
Findingown data
On average, older adults asked two questions about finding correct interface features.
“On average, older adults asked two questions about fnding correct interface features (Table 1, # UI Qs).”
Quote in the paperNot a substantial claim
Findingown data
Older adults' questions during interface exploration fall into five types: validation, directed informational, undirected informational, navigational, and conceptual.
“Results reveal fve query types when verbally articulating interaction issues: validation, directed and undirected informational, navigational, and conceptual.”
- Also stated in: § lists some query examples. · plain
  “A question could only be classifed as one of the fve types.”
Quote in the paperSubstantial claim
- Rests on an assumption: The five query types identified from older adults are sufficient to inform the design of a voice assistant.
Findingown data
Older users asked significantly more directed informational questions than their younger counterparts (U = 53, p = 0.007, r = 0.53).
“as well as more directed informational questions (U = 53, p = 0.007, r = 0.53).”
Quote in the paperSubstantial claim
Findingreasoning
No patterns of a common sequence of questions or question preferences per demographic were identified.
“Given that this was an open-ended exploratory study, no patterns of a common sequence of questions or question preferences per demographic were identifed.”
Quote in the paperNot a substantial claim
Findingown data
The mobile device proficiency of younger participants was significantly more than older participants in Study 1 (U = 20, p = 0.03, r = 0.48).
“As expected, the mobile device profciency of our younger participants was signifcantly more than our older participants in Study 1 (U = 20, p = 0.03, r = 0.48).”
Quote in the paperNot a substantial claim
Findingcitation
When encountering interaction problems, older users use question words (e.g., 'what', 'why', 'how', 'where').
“Similar to a previous study, older users sometimes used question words, like”
- Also stated in: § 4 DESIGN PROBE STUDY · plain
  “when encountering such problems, older users use question words, like”
Quote in the paperSubstantial claim0 of 1 sources checked
- cites [17] 17. Mingming Fan, Qiwen Zhao, and Vinita Tibdewal. 2021. Older adults' think-aloud verbalizations and speech features for identifying user experience problems. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 1-13. source
Findingown data
Getting lost primarily appeared in the form of repeatedly scrolling the screen up and down or moving back and forth through several pages.
“Getting lost primarily appeared in the form of repeatedly scrolling the screen up and down or moving back and forth through several pages.”
Quote in the paperNot a substantial claim
Findingown data
Participants often repeated the suggested features from one task to the next once they found success with them in the former task.
“For example, often participants repeated the suggested features from one task to the next once they found success with them in the former task.”
Quote in the paperNot a substantial claim
Findingown data
13 out of 15 users used the voice assistant (VA).
“Results from our design probe study found 13/15 users used the voice assistant (VA).”
Quote in the paperSubstantial claim
Findingown data
The three most common types of questions older users ask when encountering interaction problems with feature-rich mobile apps were validation, directed informational, and navigational.
“The three most common types of questions were validation, directed informational, and navigational.”
Quote in the paperSubstantial claim
Findingown data
When lost, 63% of the time users used the voice assistant to ask a question.
“When lost, 63% of the time users used the voice assistant to ask a question.”
Quote in the paperSubstantial claim
Findingown data
When a voice assistant was used after getting lost, 77% of the time users were able to recover immediately and successfully complete the task.
“When a voice assistant was used after getting lost, 77% of the time users were able to recover immediately and successfully complete the task.”
Quote in the paperSubstantial claim
Findingnone given
Older users asked significantly more UI-related questions than younger users.
“Older users asked signifcantly more UI-related questions than their younger counterparts.”
Quote in the paperSubstantial claim
Findingown data
From our study, it appeared that simple shapes like circles, rectangles, and arrows are sufficiently helpful.
“While from our study, it appeared that simple shapes like circles, rectangles, and arrows are sufciently helpful, it remains to be investigated if additional cues like instructions snippets would be more helpful.”
Quote in the paperNot a substantial claim
Findingown data
On average, older users asked two questions about finding correct interface features.
“On average, older users asked two questions about fnding correct interface features (Table 1).”
Quote in the paperNot a substantial claim
Findingown data
Seven participants recovered only when they used the VA.
“When examining individual-level data, we found that all participants except for P7 and P15 asked at least one question, and seven of them recovered only when they used the VA (Figure 4, right).”
Quote in the paperSubstantial claim
Findingown data
Participants used the VA significantly more after getting lost (26) than when not lost (Z = 2.3 p = 0.01, r = 0.71).
“Participants used the VA signifcantly more after getting lost (26) than when not lost (Z = 2.3 p = 0.01, r = 0.71; Figure 4, left).”
Quote in the paperSubstantial claim
Findingown data
The two participants who preemptively used the VA reported a lot of enthusiasm about the technology in the post-study interview.
“The two participants who preemptively used the VA reported a lot of enthusiasm about the technology in the post-study interview, e.g., P2 said,”
Quote in the paperNot a substantial claim
Findingown data
67 off-task selections were observed.
“67 of-task selections and 64 non-unique selections were observed, and a total of 41 'getting lost' were identifed.”
Quote in the paperNot a substantial claim
Findingown data
All participants except for P7 and P15 asked at least one question.
“When examining individual-level data, we found that all participants except for P7 and P15 asked at least one question, and seven of them recovered only when they used the VA (Figure 4, right).”
Quote in the paperNot a substantial claim
Findingown data
In the rest of the 15 cases, users 'recovered' by themselves.
“In the rest of the 15 cases, users 'recovered' by themselves (Figure 4, right).”
Quote in the paperSubstantial claim
Findingown data
Among participants who used the VA at least once, VA was used significantly more frequently than self-exploration when recovering from getting lost (Z = 2.4 p = 0.009, r = 0.86).
“Among participants who used the VA at least once, VA was used signifcantly more frequently than selfexploration when recovering from getting lost in an interaction sequence (Z = 2.4 p = 0.009, r = 0.86; Figure 4, right).”
Quote in the paperSubstantial claim
Findingown data
64 non-unique selections were observed.
“67 of-task selections and 64 non-unique selections were observed, and a total of 41 'getting lost' were identifed.”
Quote in the paperNot a substantial claim
Findingown data
UI-related queries were among the top three most frequent types of questions asked by older adults.
“UI-related queries were among the top three most frequent types of questions asked by older adults (directed informational, and navigational, Tables 3 and 2).”
Quote in the paperSubstantial claim
Findingown data
Directed informational and navigational questions were mostly verbalized using question words like 'how' or 'where'.
“Directed informational and navigational questions were mostly verbalized using question words, like 'how', or 'where' (Table 2).”
Quote in the paperSubstantial claim
Findingown data
26 out of 41 'getting lost' events were followed by the participant asking the VA a question.
“26 out of 41 'getting lost' events were followed by the participant asking the VA a question.”
Quote in the paperSubstantial claim
Findingown data
A total of 41 'getting lost' events were identified.
“67 of-task selections and 64 non-unique selections were observed, and a total of 41 'getting lost' were identifed.”
Quote in the paperSubstantial claim
Findingown data
Validation-type questions were among the top three most frequently asked question types during interactions.
“However, another type of question among the top three frequently asked during interactions was validation-type questions.”
Quote in the paperNot a substantial claim
Findingown data
Of the users who used the VA, 11 out of 13 used it only when they were lost during a task.
“Of the users who used the VA, 11/13 used it only when they were lost during a task.”
Quote in the paperSubstantial claim
Findingown data
In 20 instances out of 26 questionings, the participant recovered immediately after the intervention.
“In 20 instances out of 26 questionings, the participant recovered immediately after the intervention.”
Quote in the paperSubstantial claim
Findingown data
Users mostly invoked the VA for help when lost in the interaction steps.
“Furthermore, users mostly invoked the VA for help when lost in the interaction steps (Figure 4) which suggests that our design can help in the exploration of feature-rich mobile interfaces without frst identifying and then prescribing a complete sequence of steps.”
Quote in the paperSubstantial claim
Findingown data
Participants did not report noticing a substantial delay in getting VA assistance during the post-study interview.
“Participants did not report noticing a substantial delay in getting VA assistance during the post-study interview.”
Quote in the paperNot a substantial claim
Findingown data
In the design probe/Wizard-of-Oz study, 87% (13/15) of participants used the voice assistant.
“In our design probe study, 87% of our participants used the voice assistant”
- Also stated in: § A RESEARCH INSTRUMENTS A.1 Mobile Device Profciency Questionnaire-14 (MDPQ-14) · plain
  “During the Wizard-of-Oz experiment, 13/15 participants used the voice assistant (VA).”
Quote in the paperSubstantial claim
Findingown data
In the design probe study, participants were able to recover immediately and successfully complete the task 77% of the time assistance was requested.
“In our design probe study, 87% of our participants used the voice assistant, mostly when getting lost during exploration, and were able to recover immediately and successfully complete the task 77% of the time assistance was requested.”
Quote in the paperSubstantial claim
Findingown data
In the design probe study, participants used the voice assistant mostly when getting lost during exploration.
“In our design probe study, 87% of our participants used the voice assistant, mostly when getting lost during exploration, and were able to recover immediately and successfully complete the task 77% of the time assistance was requested.”
Quote in the paperNot a substantial claim
Findingown data
All questions collected in Study 2 could be categorized using the taxonomy created in Study 1.
“All the questions collected in Study 2 could be categorized using the taxonomy created in Study 1.”
Quote in the paperNot a substantial claim
Findingown data
No new question categories were identified in Study 2.
“No new categories were identifed.”
Quote in the paperNot a substantial claim
Premisecitation
A detailed design solution to help older adults locate features in feature-rich mobile interfaces has not yet been developed nor examined.
“While this issue has been identifed, and some design implications discussed briefy [42,69,70], a detailed design solution has not yet been developed nor examined.”
Quote in the paperSubstantial claim0 of 3 sources checked
- cites [42] 42. Shareen Mahmud, Jessalyn Alvina, Parmit K Chilana, Andrea Bunt, and Joanna McGrenere. 2020. Learning through exploration: how children, adults, and older adults interact with a new feature-rich application. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1-14. source
- cites [69] 69. Ja Eun Yu and Debaleena Chattopadhyay. 2020. "Maps are hard for me": How Older Adults Struggle with Mobile Maps. In The 22nd International ACM SIGAC- CESS Conference on Computers and Accessibility. in press. source
- cites [70] 70. Ja Eun Yu and Debaleena Chattopadhyay. 2020. Supporting Older Adults in Locating Mobile Interface Features with Voice Input. In The 22nd International ACM SIGACCESS Conference on Computers and Accessibility. in press.
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Premisecitation
Older adults often struggle to locate a function quickly in feature-rich user interfaces.
“Older adults often struggle to locate a function quickly in featurerich user interfaces (UIs).”
- Also stated in: § Abstract · plain
  “Prior work has reported that older adults frequently struggle with identifying and locating the correct feature in desktop [42] and mobile interfaces [69].”
Quote in the paperSubstantial claim0 of 2 sources checked
- cites [42] 42. Shareen Mahmud, Jessalyn Alvina, Parmit K Chilana, Andrea Bunt, and Joanna McGrenere. 2020. Learning through exploration: how children, adults, and older adults interact with a new feature-rich application. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1-14. source
- cites [69] 69. Ja Eun Yu and Debaleena Chattopadhyay. 2020. "Maps are hard for me": How Older Adults Struggle with Mobile Maps. In The 22nd International ACM SIGAC- CESS Conference on Computers and Accessibility. in press. source
Premisecitation
Older users tend to verbalize question words, like 'what', 'why', and 'how', when encountering an interaction problem.
“older users tend to verbalize question words, like 'what', 'why', and 'how', when encountering an interaction problem [17].”
Quote in the paperSubstantial claim0 of 1 sources checked
- cites [17] 17. Mingming Fan, Qiwen Zhao, and Vinita Tibdewal. 2021. Older adults' think-aloud verbalizations and speech features for identifying user experience problems. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 1-13. source
- Rests on an assumption: Older adults' verbal questions during think-aloud can serve as input to a voice assistant.
Premisecitation
In spite of the uptake in mobile devices, older adults use way fewer apps and app functions than younger adults.
“In spite of the uptake in mobile devices, older adults use way fewer apps and app functions than younger adults [38].”
Quote in the paperSubstantial claim0 of 1 sources checked
- cites [38] 38. Qingchuan Li, Yan Luximon, et al. 2018. Understanding older adults' post- adoption usage behavior and perceptions of mobile technology. (2018).
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Premisenone given
No prior HCI work has characterized the questions asked during interface exploration by older adults.
“Although prior taxonomies exist for search queries-typed or spoken-to our knowledge, no prior HCI work has characterized the questions asked during interface exploration by older adults.”
Quote in the paperNot a substantial claim
Premisecitation
Older adults also struggled when familiar with an application but unfamiliar with a particular task or an updated version of the interface.
“Older adults also struggled when familiar with an application but unfamiliar with a particular task or an updated version of the interface [69].”
Quote in the paperNot a substantial claim0 of 1 sources checked
- cites [69] 69. Ja Eun Yu and Debaleena Chattopadhyay. 2020. "Maps are hard for me": How Older Adults Struggle with Mobile Maps. In The 22nd International ACM SIGAC- CESS Conference on Computers and Accessibility. in press. source
Premisenone given
None of the prior design ideas (tooltips, heatmaps, gaze cues, action lists) have been systematically examined, designed, or evaluated with users.
“Note that these design ideas have been briefy discussed in the prior literature, but none of them have been systematically examined, designed, or evaluated with users.”
Quote in the paperNot a substantial claim
Premisenone given
There are no data on how older users might ask for assistance when facing the problem of locating features.
“Despite multiple reports of this problem, there are no data on how older users might ask for assistance when facing the problem.”
Quote in the paperNot a substantial claim
Premisecitation
Younger users are more comfortable exploring different menus compared to older users.
“Younger users may often quickly fnd the relevant features because studies show that they are more comfortable exploring diferent menus compared to older users [42].”
Quote in the paperNot a substantial claim0 of 1 sources checked
- cites [42] 42. Shareen Mahmud, Jessalyn Alvina, Parmit K Chilana, Andrea Bunt, and Joanna McGrenere. 2020. Learning through exploration: how children, adults, and older adults interact with a new feature-rich application. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1-14. source
Interpretationown data
Younger adults are less likely to ask interface-related questions than older users.
“This suggests that younger adults are less likely to ask interface-related questions, which could be interpreted as either they encounter relatively few problems, or they fnd the answer themselves by exploring the UI.”
Quote in the paperSubstantial claim
Interpretationreasoning
Different question words could further indicate different types of interaction problems (or information needs), e.g., 'how' and 'where' questions to express a lack of knowledge about the UI location of a particular function.
“We extend this fnding to show how diferent question words could further indicate diferent types of interaction problems (or information needs), e.g., 'how' and 'where' questions to express a lack of knowledge about the UI location of a particular function.”
Quote in the paperSubstantial claim
Interpretationown data
Our design can help in the exploration of feature-rich mobile interfaces without first identifying and then prescribing a complete sequence of steps.
“Furthermore, users mostly invoked the VA for help when lost in the interaction steps (Figure 4) which suggests that our design can help in the exploration of feature-rich mobile interfaces without frst identifying and then prescribing a complete sequence of steps.”
Quote in the paperSubstantial claim
Study design and conductcitation
The criteria for marking users as 'getting lost' were able to capture cycle, retry, repeated reverts, and other inefficient paths, reflecting navigational disorientation, inefficient pathways, and inverse operations.
“These criteria were able to capture the cycle, retry, repeated reverts, and other inefcient paths that a user might generate while exploring, which refects the characteristics of navigational disorientation-looping, inefcient pathways, and inverse operations [18,69].”
Quote in the paperSubstantial claim0 of 2 sources checked
- cites [18] 18. Carolyn L Foss. 1989. Detecting lost users: Empirical studies on browsing hyper- text. source
- cites [69] 69. Ja Eun Yu and Debaleena Chattopadhyay. 2020. "Maps are hard for me": How Older Adults Struggle with Mobile Maps. In The 22nd International ACM SIGAC- CESS Conference on Computers and Accessibility. in press. source
Premisecitation
Older adults are rarely adopting simplified, senior-purpose apps.
“Older adults are rarely adopting simplifed, senior-purpose apps [62,65].”
Quote in the paperSubstantial claim0 of 2 sources checked
- cites [62] 62. John Vines, Stephen Lindsay, Gary W Pritchard, Mabel Lie, David Greathead, Patrick Olivier, and Katie Brittain. 2013. Making family care work: dependence, privacy and remote home monitoring telecare systems. In Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing. 607-616. source
- cites [65] 65. Jenny Waycott, Frank Vetere, Sonja Pedell, Amee Morgans, Elizabeth Ozanne, and Lars Kulik. 2016. Not for me: Older adults choosing not to participate in a social isolation intervention. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. ACM, 745-757. source
Premisecitation
Older users tend to only look for features where they would expect them to be without scanning the current view comprehensively.
“In a similar vein, post-study interviews found that older users tend to only look for features where they would expect them to be without scanning the current view comprehensively [42].”
Quote in the paperSubstantial claim0 of 1 sources checked
- cites [42] 42. Shareen Mahmud, Jessalyn Alvina, Parmit K Chilana, Andrea Bunt, and Joanna McGrenere. 2020. Learning through exploration: how children, adults, and older adults interact with a new feature-rich application. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1-14. source
Interpretationown data
The design solves a hard problem reported in the literature: once lost, older adults can keep going back and forth on the same interaction flow until they are frustrated enough to give up.
“This solves a hard problem reported in the literature: once lost, older adults can keep going back and forth on the same interaction fow until they are frustrated enough to give up (Figure 3, [69]).”
Quote in the paperSubstantial claim0 of 1 sources checked
- cites [69] 69. Ja Eun Yu and Debaleena Chattopadhyay. 2020. "Maps are hard for me": How Older Adults Struggle with Mobile Maps. In The 22nd International ACM SIGAC- CESS Conference on Computers and Accessibility. in press. source
Study design and conductnone given
A major limitation of our design solution is that we only provide relevant features on the current UI view.
“A major limitation of our design solution is that we only provide relevant features on the current UI view.”
Quote in the paperNot a substantial claim

Classified as probably not a substantial claim. 41
May combine two claims. 26
The quote only partly states this claim. 2

Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation
Studies continue to report that older adults use voice assistants for finding information.
“Nevertheless, studies continue to report that older adults use VAs for fnding information [31,32,49,57].”
Quote in the paperNot a substantial claim1 of 4 sources checked
- cites [31] 31. Pegah Karimi, Kallista Ballard, Pooja Vazirani, Ravi Teja Narasimha Jorigay, and Aqueasha Martin-Hammond. 2022. Designing Conversational Assistants to Support Older Adults' Personal Health Record Access. In International Conference on Pervasive Computing Technologies for Healthcare. Springer, 253-271. source
- cites [32] 32. Sunyoung Kim and Abhishek Choudhury. 2021. Exploring older adults' per- ception and use of smart speaker-based voice assistants: A longitudinal study. Computers in Human Behavior 124 (2021), 106914. source
- cites [49] 49. Alisha Pradhan, Amanda Lazar, and Leah Findlater. 2020. Use of intelligent voice assistants by older adults with low technology use. ACM Transactions on Computer-Human Interaction (TOCHI) 27, 4 (2020), 1-27. source
- cites [57] 57. Brodrick Stigall, Jenny Waycott, Steven Baker, and Kelly Caine. 2019. Older adults' perception and use of voice user interfaces: a preliminary review of the computing literature. In Proceedings of the 31st Australian Conference on Human- Computer-Interaction. 423-427. source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premisecitation
In the literature, older adults are defined from ages 50 and above, 55 and above, and 70 and above.
“In the literature too, older adults are defned from ages 50 and above [15,61,66], 55 and above [2,67] and 70 and above [59,60].”
Quote in the paperNot a substantial claim2 of 7 sources checked
- cites [15] 15. Mark Dunlop, Andreas Komninos, Emma Nicol, and Iain Hamiliton. 2014. Shake'n'Tap: a gesture enhanced keyboard for older adults. In Proceedings of the 16th international conference on Human-computer interaction with mobile devices & services. 525-530. source
- cites [61] 61. Andrea Vianello, Luca Chittaro, Stefano Burigat, and Riccardo Budai. 2017. Motor- Brain: a mobile app for the assessment of users' motor performance in neurology. Computer methods and programs in biomedicine 143 (2017), 35-47. source
- cites [66] 66. Tzu-Ning Wen, Po-Liang Cheng, and Po-Lun Chang. 2017. Evaluate the usability of the mobile instant messaging software in the elderly. In MEDINFO 2017: Precision Healthcare through Informatics. IOS Press, 818-822. source
- cites [2] 2. Sofaniza Abd Malik and Alistair DN Edwards. 2010. Investigation of cultural dependency in mobile technology and older adults. In CHI'10 Extended Abstracts on Human Factors in Computing Systems. 3835-3840. source
- cites [67] 67. Leigh Ann Wilson, Kate O'Loughlin, Robyn Hector, and Deborah Ann Black. 2021. Using a smartphone application (App) to assist older adults to navigate their local area during extreme weather events and changing environmental conditions: A qualitative study. Australasian Journal on Ageing 40, 1 (2021), e95-e99. source
- cites [59] 59. Tifany Tong, Mark Chignell, Mary C Tierney, and Jacques Lee. 2016. A serious game for clinical assessment of cognitive status: validation study. JMIR serious games 4, 1 (2016), e5006. source
- cites [60] 60. Joan Vermeulen, Jacques CL Neyens, Marieke D Spreeuwenberg, Erik van Rossum, Walther Sipers, Herbert Habets, David J Hewson, and Luc P De Witte. 2013. User- centered development and testing of a monitoring system that provides feedback regarding physical functioning to elderly people. Patient preference and adherence 7 (2013), 843. source
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation
No set chronological age makes an individual 'older' as opposed to younger.
“Before introducing our core research questions, we must acknowledge that no set chronological age makes an individual 'older' as opposed to younger [34].”
Quote in the paperNot a substantial claim1 of 1 sources checked
- cites [34] 34. Bran Knowles, Vicki L Hanson, Yvonne Rogers, Anne Marie Piper, Jenny Waycott, Nigel Davies, Aloha Hufana Ambe, Robin N Brewer, Debaleena Chattopadhyay, Marianne Dee, et al. 2021. The harm in confating aging with accessibility. Commun. ACM 64, 7 (2021), 66-71. source
May combine two claims.
Premisecitation
Users focused more on the content than navigation cues and did not open vertical menus, such as the side drawer and springboard, to explore menu options further.
“Users focused more on the content than navigation cues, similar to prior studies [50], and did not open vertical menus, such as the side drawer and springboard to explore menu options further [37].”
Quote in the paperSubstantial claim1 of 2 sources checked
- cites [50] 50. Jennifer C Romano Bergstrom, Erica L Olmsted-Hawala, and Matt E Jans. 2013. Age-related diferences in eye tracking and usability performance: website us- ability for older adults. International Journal of Human-Computer Interaction 29, 8 (2013), 541-548. source
- cites [37] 37. Qingchuan Li and Yan Luximon. 2020. Older adults' use of mobile device: us- ability challenges while navigating various interfaces. Behaviour & Information Technology 39, 8 (2020), 837-861. source
  For the claim attached to [37], the Results of activity analysis (page unavailable) report that some older adults could not find the side-drawer entry point or recognize that the side drawer and springboard could be scrolled. But the paper also reports successful menu selection and says participants could search and select side-drawer items once they found its entry point; it does not establish that users generally did not open these menus to explore further options. The content-versus-navigation-cues clause is attached to [50], not [37]. (LLM, conf=0.86)
  Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation
Older adults are much less likely to adopt senior-friendly technology variants designed specifically for them than people with a different ability to adopt assistive tools.
“We have learned that older adults are much less likely to adopt senior-friendly technology variants that are designed specifcally for them than people with a diferent ability to adopt assistive tools [33,34].”
Quote in the paperNot a substantial claim1 of 2 sources checked
- cites [33] 33. Bran Knowles and Vicki L Hanson. 2018. The Wisdom of Older Technology (Non-) Users. Commun. ACM 61, 3 (2018), 72-77. source
- cites [34] 34. Bran Knowles, Vicki L Hanson, Yvonne Rogers, Anne Marie Piper, Jenny Waycott, Nigel Davies, Aloha Hufana Ambe, Robin N Brewer, Debaleena Chattopadhyay, Marianne Dee, et al. 2021. The harm in confating aging with accessibility. Commun. ACM 64, 7 (2021), 66-71. source
  The WHAT'S THE HARM? section says technologies designed specifically for older people are rarely adopted unless users have no other choice. It does not compare their adoption with adoption of assistive tools by people with different abilities, so the comparative part of the claim is unsupported. Page numbers are unavailable in our copy. (LLM, conf=0.87)
  Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premisecitation
The body of research examining older adults' use and perception of voice-based interfaces is still emerging and reports both positive results, like user preference in looking up information, and negative results, like cultural barriers to use.
“The body of research examining older adults' use and perception of voice-based interfaces is still emerging and report both positive results, like user preference in looking up information [49] and negative results, like cultural barriers to use [22].”
Quote in the paperNot a substantial claim2 of 2 sources checked
- cites [49] 49. Alisha Pradhan, Amanda Lazar, and Leah Findlater. 2020. Use of intelligent voice assistants by older adults with low technology use. ACM Transactions on Computer-Human Interaction (TOCHI) 27, 4 (2020), 1-27. source
- cites [22] 22. Christina N Harrington, Radhika Garg, Amanda Woodward, and Dimitri Williams. 2022. "It's Kind of Like Code-Switching": Black Older Adults' Experiences with a Voice Assistant for Health Information Seeking. (2022). source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premisecitation
Older adults do not view aging as disabling, at least not in all-encompassing life circumstances but maybe in certain everyday contexts.
“That is perhaps because older adults do not view aging as disabling [34]-at least not in all-encompassing life circumstances but maybe in certain everyday contexts [6].”
Quote in the paperNot a substantial claim1 of 2 sources checked
- cites [34] 34. Bran Knowles, Vicki L Hanson, Yvonne Rogers, Anne Marie Piper, Jenny Waycott, Nigel Davies, Aloha Hufana Ambe, Robin N Brewer, Debaleena Chattopadhyay, Marianne Dee, et al. 2021. The harm in confating aging with accessibility. Commun. ACM 64, 7 (2021), 66-71. source
  The Introduction (page unavailable) argues that aging is neither an illness nor a disability, supporting the distinction behind the claim. It does not establish that older adults themselves generally view aging this way. The qualification about particular everyday contexts is attached to a different citation, not this source. (LLM, conf=0.83)
  Experimental — accuracy not yet measured
- cites [6] 6. Eva Brandt, Thomas Binder, Lone Malmborg, and Tomas Sokoler. 2010. Communi- ties of everyday practice and situated elderliness as an approach to co-design for senior interaction. In Proceedings of the 22nd Conference of the Computer-Human Interaction Special Interest Group of Australia on Computer-Human Interaction. 400-403. source
May combine two claims.
Premisecitation
When studying how older users accomplish different tasks using a smartphone, researchers observed difficulty in directing attention to tab menus, recognizing scrollable tab menus, and distinguishing between neighboring or similar-appearing icons and buttons.
“For example, when studying how older users accomplish diferent tasks using a smartphone, researchers observed difculty in directing attention to tab menus, recognizing scrollable tab menus, and distinguishing between neighboring or similar-appearing icons and buttons [37].”
Quote in the paperSubstantial claim1 of 1 sources checked
- cites [37] 37. Qingchuan Li and Yan Luximon. 2020. Older adults' use of mobile device: us- ability challenges while navigating various interfaces. Behaviour & Information Technology 39, 8 (2020), 837-861. source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductcitation
The MDPQ-14 is an objective measure of smartphone skills and has been validated with older adults.
“we asked them to complete the mobile device profciency questionnaire (MDPQ-14), which is an objective measure of smartphone skills and has been validated with older adults (Appendix, Table 6) [46].”
Quote in the paperNot a substantial claim1 of 1 sources checked
- cites [46] 46. Andraž Petrovčič, Walter R Boot, Tomaž Burnik, and Vesna Vesna Dolničar. 2019. Improving the Measurement of Older Adults' Mobile Device Profciency: Results and Implications from a Study of Older Adult Smartphone Users. IEEE Access 7 (2019), 150412-150422. source
  The Discussion reports that the MDPQ-14 was evaluated in older smartphone users and had the same strength of association with criterion metrics as the longer version. But the Background describes the MDPQ as a self-report measure and distinguishes it from objective smartphone task-performance metrics. Calling the MDPQ-14 an objective measure is therefore incorrect. (LLM, conf=0.91)
  Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation
Researchers have explored the concept of users teaching a virtual assistant to completely automate complex tasks on mobile devices by offering natural language instructions.
“Elsewhere, researchers have explored the concept of users teaching a virtual assistant to completely automate complex tasks on mobile devices by ofering natural language instructions [4,39].”
Quote in the paperNot a substantial claim1 of 2 sources checked
- cites [4] 4. Amos Azaria, Jayant Krishnamurthy, and Tom M Mitchell. 2016. Instructable Intelligent Personal Agent.. In AAAI, Vol. 4. source
  The Introduction (p. 1) says users teach LIA new action sequences through natural-language instructions, and that it can later execute those commands. But it says LIA operates in an email environment; the Conclusions (p. 7) call it a partial, initial implementation and discuss availability on mobile devices as a future possibility. The source therefore does not establish complete automation of complex tasks on mobile devices. (LLM, conf=0.88)
  Experimental — accuracy not yet measured
- cites [39] 39. Toby Jia-Jun Li, Amos Azaria, and Brad A Myers. 2017. SUGILITE: creating multimodal smartphone automation by demonstration. In Proceedings of the 2017 CHI conference on human factors in computing systems. 6038-6049.
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
The quote only partly states this claim.
Findingcitation
The F1 score for the best-performing algorithm was .8.
“We matched the two sets of keywords and identifed up to the top three relevant UI components using ConceptNet's numerical similarity score [55] (F1 score = .8).”
Quote in the paperNot a substantial claim1 of 1 sources checked
- cites [55] 55. Robyn Speer, Joshua Chin, and Catherine Havasi. 2017. Conceptnet 5.5: An open multilingual graph of general knowledge. In Thirty-frst AAAI conference on artifcial intelligence. source
  Table 1 (An Evaluation of Common-Sense Stories, p. 5) reports correlations and accuracies, including a .810 correlation, but no F1 score. The Word Relatedness section (p. 6) likewise describes correlation and accuracy measures; a search for F1 and numerical similarity found no reported F1 score of .8. (LLM, conf=0.78)
  Experimental — accuracy not yet measured
May combine two claims.
Findingown data
Both older and younger users asked questions that ranged all across the taxonomy, but the frequency of different types of questions differed significantly.
“Although both older and younger users asked questions that ranged all across our taxonomy, the frequency of diferent types of questions difered signifcantly (Table 3).”
Quote in the paperSubstantial claim
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingown data
8 out of 12 younger participants completed the MDPQ-14 questionnaire (Mdn = 64, M = 62.1).
“8 out of 12 participants completed the MDPQ-14 questionnaire (Mdn = 64, M = 62.1).”
Quote in the paperNot a substantial claim
May combine two claims.
Findingreasoning
The study tasks or apps were unfamiliar to the participants, but they were familiar with the type of apps (e.g., social media, online shopping, food delivery) and touchscreen smartphones.
“The study tasks or apps were unfamiliar to the participants, but they were familiar with the type of apps (e.g., social media, online shopping, food delivery) and touchscreen smartphones.”
Quote in the paperSubstantial claim
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingown data
All participants in Study 1 asked questions during interface exploration (Mdn = 5).
“All of the participants asked questions during interface exploration (Mdn = 5).”
Quote in the paperNot a substantial claim
Classified as probably not a substantial claim.
Findingown data
MDPQ-14 scores were reported by 12/19 participants in Study 1 (Mdn = 44.5, M = 44.75).
“MDPQ-14 scores were reported by 12/19 participants (Mdn = 44.5,M = 44.75).”
Quote in the paperSubstantial claim
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingown data
Twelve younger users participated in Study 2 (6 females, Mdn = 31 years, IQR = 8.5).
“Twelve younger users participated in the study (6 females, Mdn= 31 years, IQR = 8.5).”
Quote in the paperNot a substantial claim
May combine two claims.
Findingown data
Younger users asked the same types of questions as older adults, but how frequently they asked these questions varied significantly.
“While younger users asked the same types of questions as older adults, how frequently they asked these questions varied signifcantly.”
Quote in the paperNot a substantial claim
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingown data
The study did not encounter examples that would make classification into the five question types problematic.
“We did not encounter examples in our study that would make such a classifcation problematic.”
Quote in the paperNot a substantial claim
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingown data
A total of 931 events were tagged.
“A total of 931 events were tagged.”
Quote in the paperNot a substantial claim
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingown data
In Study 3, one user specifically mentioned that it would be good if the voice assistant answered the question when they ask if they are doing well.
“Furthermore, in our Study 3, one user specifcally mentioned”
Quote in the paperNot a substantial claim
May combine two claims. The quote only partly states this claim.
Findingown data
During the post-study interview, participants mentioned that VA helped them to learn about new features and when stuck.
“during the post-study interview participants mentioned that VA helped them to learn about new features (P11:”
Quote in the paperSubstantial claim
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown data
Participants P2 and P5 used the VA without getting lost and asked questions right after beginning the task at hand.
“Participants (P2 and P5) who used the VA without getting lost asked questions right after beginning the task at hand, which could have been a novelty efect, with participants wanting to try out new technology.”
Quote in the paperNot a substantial claim
May combine two claims.
Findingown data
In our WoZ experiment, we found that users indirectly learned from the output of the voice assistant (VA) and used them in consecutive tasks.
“Indeed, in our WoZ experiment, we found that users indirectly learned from the output of the voice assistant (VA) and used them in consecutive tasks.”
Quote in the paperNot a substantial claim
May combine two claims.
Findingown data
Participants used the assistance to learn about an unfamiliar app and reuse the features highlighted by the VA in a previous task.
“Another interesting fnding from this study, that we did not anticipate, was how participants used the assistance to learn about an unfamiliar app and reuse the features highlighted by the VA in a previous task.”
Quote in the paperNot a substantial claim
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingown data
Participants P7 (62, F) and P15 (61, M) did not ask any questions in Study 3.
“P7 (62, F) and P15 (61, M) did not ask any questions.”
Quote in the paperNot a substantial claim
May combine two claims.
Premisecitation
Older adults lag behind younger counterparts in both the number of mobile apps (breadth) and the number of features per app (depth) they use.
“Older adults lag behind their younger counterparts in both the number of mobile apps (breadth) and the number of features per app (depth) they use [19,36,72].”
Quote in the paperSubstantial claim0 of 3 sources checked
- cites [19] 19. Helene Gelderblom, Tobie van Dyk, and Judy van Biljon. 2010. Mobile phone adoption: Do existing models adequately capture the actual usage of older adults?. In Proceedings of the 2010 annual research conference of the south african institute of computer scientists and information technologists. 67-74. source
- cites [36] 36. Qingchuan Li and Yan Luximon. 2016. Older adults and digital technology: A study of user perception and usage behavior. In Advances in physical ergonomics and human factors. Springer, 155-163.
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites [72] 72. Jia Zhou, Pei-Luen Patrick Rau, and Gavriel Salvendy. 2012. Use and design of handheld computers for older adults: A review and appraisal. International Journal of Human-Computer Interaction 28, 12 (2012), 799-826. source
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation
Older adults do not consider themselves as 'old' in all-encompassing life circumstances but only in certain situational aspects of environments, objects, and life changes (situated elderliness).
“older adults do not consider themselves as 'old' in all-encompassing life circumstances but only in certain situational aspects of environments, objects, and life changes (situated elderliness [6]).”
Quote in the paperNot a substantial claim0 of 1 sources checked
- cites [6] 6. Eva Brandt, Thomas Binder, Lone Malmborg, and Tomas Sokoler. 2010. Communi- ties of everyday practice and situated elderliness as an approach to co-design for senior interaction. In Proceedings of the 22nd Conference of the Computer-Human Interaction Special Interest Group of Australia on Computer-Human Interaction. 400-403. source
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation
60-plus older adults who already own a smart speaker are more likely to use it daily than people ages 30 or younger.
“For instance, 60-plus older adults who already own a smart speaker are more likely to use it daily than people ages 30 or younger [64].”
Quote in the paperNot a substantial claim0 of 1 sources checked
- cites [64] 64. Josh Wardini. 2022. Voice search statistics 2022: Smart speakers, VA, and users: Serpwatch. https://serpwatch.io/blog/voice-search-statistics/
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
Premisecitation
Older users may remain in a forever-early adoption stage of feature-rich user interfaces because of lack of onboarding support and continuing peer-support, challenges in interface exploration, or personal choice.
“Older users may remain in a forever-early adoption stage of feature-rich user interfaces [19,36,72] because of a lack of onboarding support and continuing peer-support [63], challenges in interface exploration [42,69], or as a personal choice [33].”
Quote in the paperSubstantial claim0 of 4 sources checked
- cites [63] 63. Lin Wang, Pei-Luen Patrick Rau, and Gavriel Salvendy. 2011. Older adults' acceptance of information technology. Educational Gerontology 37, 12 (2011), 1081-1099. source
- cites [42] 42. Shareen Mahmud, Jessalyn Alvina, Parmit K Chilana, Andrea Bunt, and Joanna McGrenere. 2020. Learning through exploration: how children, adults, and older adults interact with a new feature-rich application. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1-14. source
- cites [69] 69. Ja Eun Yu and Debaleena Chattopadhyay. 2020. "Maps are hard for me": How Older Adults Struggle with Mobile Maps. In The 22nd International ACM SIGAC- CESS Conference on Computers and Accessibility. in press. source
- cites [33] 33. Bran Knowles and Vicki L Hanson. 2018. The Wisdom of Older Technology (Non-) Users. Commun. ACM 61, 3 (2018), 72-77. source
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Interpretationreasoning
Tooltips, heatmaps, and action lists are better suited for desktop interfaces because mobile devices offer limited-screen real estate.
“Tooltips, heatmaps, and action lists are better suited for desktop interfaces because mobile devices ofer limited-screen real estate.”
Quote in the paperNot a substantial claim
May combine two claims.
Premisereasoning
Mobile UIs pack many features into a small screen and receive frequent updates to their visual layouts, thereby exacerbating the difficulty of locating features.
“Mobile UIs not only pack a ton of features in a small screen but also get frequent updates to their visual layouts-thereby exacerbating the problem.”
- Also stated in: § Abstract · plain
  “We focus on mobile interfaces because they tend to get more frequent updates than desktop apps, and these updates often modify the visual layouts of menus, interface components, and buttons-thereby worsening the problem of quickly locating the correct feature during interface exploration, whether using it for the frst time (onboarding) or not.”
Quote in the paperSubstantial claim
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation
A recent study with 35 older adults (55 years or older) reported an average use of 2.86 apps, including 1.97 third-party apps.
“A recent study with 35 older adults (55 years or older) reported an average use of 2.86 apps, including 1.97 third-party apps [38].”
Quote in the paperNot a substantial claim0 of 1 sources checked
- cites [38] 38. Qingchuan Li, Yan Luximon, et al. 2018. Understanding older adults' post- adoption usage behavior and perceptions of mobile technology. (2018).
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
Premisecitation
In a recent study with Microsoft OneNote, on average, older users missed over twice the features as younger adults, and the difficulty in locating the correct feature did not only occur when using an application for the first time.
“In a recent study with Microsoft OneNote, on average, older users missed over twice the features as younger adults, and the difculty in locating the correct feature did not only occur when using an application for the frst time [42].”
Quote in the paperSubstantial claim0 of 1 sources checked
- cites [42] 42. Shareen Mahmud, Jessalyn Alvina, Parmit K Chilana, Andrea Bunt, and Joanna McGrenere. 2020. Learning through exploration: how children, adults, and older adults interact with a new feature-rich application. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1-14. source
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown data
The greater number of older (n = 19) than younger participants (n = 12) may have had an effect on the total number of questions asked.
“However, we had a greater number of older (n = 19) than younger participants (n = 12) in our study which may have had an efect on the total number of questions asked.”
Quote in the paperNot a substantial claim
Classified as probably not a substantial claim.
Study design and conductreasoning
Each participant used an unfamiliar mobile app from a familiar category to ensure they were unfamiliar with the app interface but familiar with the app concept.
“Each participant used an unfamiliar mobile app from a familiar category to ensure they were unfamiliar with the app interface but familiar with the app concept.”
Quote in the paperSubstantial claim
Classified as probably not a substantial claim.
Study design and conductreasoning
Given the exploratory objective, the study opted for ecological and external validity over internal validity.
“Given the exploratory objective of this study, we opted for ecological and external validity over internal validity.”
Quote in the paperSubstantial claim
May combine two claims.
Premisecitation
Older users did not only miss relevant features at the onset of a task but also en route to completing a task.
“Older users did not only miss relevant features at the onset of a task but also en route to completing a task.”
Quote in the paperSubstantial claim0 of 2 sources checked
- cites [42] 42. Shareen Mahmud, Jessalyn Alvina, Parmit K Chilana, Andrea Bunt, and Joanna McGrenere. 2020. Learning through exploration: how children, adults, and older adults interact with a new feature-rich application. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1-14. source
- cites [69] 69. Ja Eun Yu and Debaleena Chattopadhyay. 2020. "Maps are hard for me": How Older Adults Struggle with Mobile Maps. In The 22nd International ACM SIGAC- CESS Conference on Computers and Accessibility. in press. source
May combine two claims.
Premisecitation
Even when on the right track, older adults could get confused about the correct features, make off-task feature selections, and get stuck into cycles where they would repeat the same sequence of incorrect feature selections over and over.
“Even when on the right track, older adults could get confused about the correct features, make of-task feature selections, and get stuck into cycles where they would repeat the same sequence of incorrect feature selections over and over [42,69].”
Quote in the paperSubstantial claim0 of 2 sources checked
- cites [42] 42. Shareen Mahmud, Jessalyn Alvina, Parmit K Chilana, Andrea Bunt, and Joanna McGrenere. 2020. Learning through exploration: how children, adults, and older adults interact with a new feature-rich application. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1-14. source
- cites [69] 69. Ja Eun Yu and Debaleena Chattopadhyay. 2020. "Maps are hard for me": How Older Adults Struggle with Mobile Maps. In The 22nd International ACM SIGAC- CESS Conference on Computers and Accessibility. in press. source
May combine two claims.
Premisecitation
While non-use could be a deliberate choice, another reason for limited use repeatedly observed in the HCI literature is a lack of exploration support.
“While non-use could be a deliberate choice [33,52], another reason for limited use repeatedly observed in the HCI literature is a lack of exploration support [42,69].”
Quote in the paperSubstantial claim0 of 4 sources checked
- cites [33] 33. Bran Knowles and Vicki L Hanson. 2018. The Wisdom of Older Technology (Non-) Users. Commun. ACM 61, 3 (2018), 72-77. source
- cites [52] 52. Nina Sakhnini and Debaleena Chattopadhyay. 2022. A Review of Smartphone Fact-Checking Apps and their (Non) Use Among Older Adults. In Adjunct Publi- cation of the 24th International Conference on Human-Computer Interaction with Mobile Devices and Services. 1-8. source
- cites [42] 42. Shareen Mahmud, Jessalyn Alvina, Parmit K Chilana, Andrea Bunt, and Joanna McGrenere. 2020. Learning through exploration: how children, adults, and older adults interact with a new feature-rich application. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1-14. source
- cites [69] 69. Ja Eun Yu and Debaleena Chattopadhyay. 2020. "Maps are hard for me": How Older Adults Struggle with Mobile Maps. In The 22nd International ACM SIGAC- CESS Conference on Computers and Accessibility. in press. source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premisecitation
Older adults now prefer more social learning methods and rely less on instruction manuals than observed in the past.
“Older adults now prefer more social learning methods and have come to rely less on instruction manuals than observed in the past [45].”
Quote in the paperNot a substantial claim0 of 1 sources checked
- cites [45] 45. Carolyn Pang, Zhiqin Collin Wang, Joanna McGrenere, Rock Leung, Jiamin Dai, and Karyn Mofatt. 2021. Technology Adoption and Learning Preferences for Older Adults: Evolving Perceptions, Ongoing Challenges, and Emerging Design Opportunities. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 1-13. source
Classified as probably not a substantial claim.
Study design and conductcitation
The study took inspiration from conversation analysis to decide what talk should be considered a question.
“we took inspiration from conversation analysis (CA) to decide what talk should be considered as a question [11,54].”
Quote in the paperSubstantial claim0 of 2 sources checked
- cites [11] 11. Debaleena Chattopadhyay, Francesca Salvadori, Kenton O'hara, and Sean Rintel. 2018. Beyond presentation: Shared slideware control as a resource for collocated collaboration. Human-Computer Interaction 33, 5-6 (2018), 455-498. source
- cites [54] 54. Jack Sidnell and Tanya Stivers. 2012. The handbook of conversation analysis. Vol. 121. John Wiley & Sons. source
Classified as probably not a substantial claim. May combine two claims.
Premisenone given
It is still unknown how older adults might articulate difficulty locating features verbally and whether that articulation can serve as an input to a voice assistant.
“But we still do not know how older adults might articulate such a difculty verbally and whether that articulation can serve as an input to a voice assistant.”
Quote in the paperSubstantial claim
- Rests on an assumption: Older adults' verbal questions during think-aloud can serve as input to a voice assistant.
Probably not a substantial claim: may not pass S4 (based).
Study design and conductreasoning
Using the same application and same tasks, irrespective of users' familiarity with them, would not be a valid UI exploration scenario.
“Using the same application and same tasks, irrespective of users' familiarity with them would not be a valid UI exploration scenario.”
Quote in the paperNot a substantial claim
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductreasoning
The number of UI-queries reported is a conservative estimate.
“So the number of UI-queries we report here is a conservative estimate-and done to ensure the rigor of our analysis.”
Quote in the paperNot a substantial claim
Classified as probably not a substantial claim.
Interpretationreasoning
Adding visual cues to an already busy UI of a feature-rich interface could add clutter and hinder rather than better user experiences.
“However, that meant adding visual cues to an already busy UI of a feature-rich interface, which could add clutter and hinder rather than better user experiences.”
Quote in the paperSubstantial claim
- Rests on an assumption: Any additional visual information on a UI would add to users' cognitive load and could make older users inefficient while trying to improve learnability.
Probably not a substantial claim: may not pass S3 (load-bearing).
Interpretationown data
Users may want the correct answer right away.
“The choice to ofer three options was made to accommodate algorithmic errors but users may want the correct answer right away, e.g., P5 said,”
Quote in the paperNot a substantial claim
Classified as probably not a substantial claim.
Premisecitation
The failure to notice UI components at certain parts of the screen may stem from older adults' narrow useful field of view (UFOV) and difficulty rapidly shifting their UFOV.
“For example, it has been suggested that the failure to notice UI components at certain parts of the screen may stem from older adults' narrow useful feld of view (UFOV) and difculty rapidly shifting their UFOV [69].”
Quote in the paperSubstantial claim0 of 1 sources checked
- cites [69] 69. Ja Eun Yu and Debaleena Chattopadhyay. 2020. "Maps are hard for me": How Older Adults Struggle with Mobile Maps. In The 22nd International ACM SIGAC- CESS Conference on Computers and Accessibility. in press. source
Probably not a substantial claim: may not pass S3 (load-bearing).
Interpretationown data
The preemptive use of the VA by P2 and P5 could have been a novelty effect.
“Participants (P2 and P5) who used the VA without getting lost asked questions right after beginning the task at hand, which could have been a novelty efect, with participants wanting to try out new technology.”
Quote in the paperNot a substantial claim
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation
A prior study found that when encountering an interaction problem, older users tend to verbalize question words like 'what', 'why', and 'how'.
“A prior study looking into older users' think-aloud (TA) verbalization and speech features found that when encountering an interaction problem, older users tend to verbalize question words, like 'what', 'why', and 'how' [17].”
Quote in the paperNot a substantial claim0 of 1 sources checked
- cites [17] 17. Mingming Fan, Qiwen Zhao, and Vinita Tibdewal. 2021. Older adults' think-aloud verbalizations and speech features for identifying user experience problems. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 1-13. source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premisecitation
Voice input is not without its challenges, e.g., problems include knowing what to say, how to say, whether the input was correctly recognized, difficulty in error recognition, and difficulty in error correction.
“Second, voice input is not without its challenges-e.g., problems include knowing what to say, how to say [22], whether the input was correctly recognized (P2:”
Quote in the paperNot a substantial claim0 of 1 sources checked
- cites [22] 22. Christina N Harrington, Radhika Garg, Amanda Woodward, and Dimitri Williams. 2022. "It's Kind of Like Code-Switching": Black Older Adults' Experiences with a Voice Assistant for Health Information Seeking. (2022).
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation
Repeated non-unique and off-task selections have also been found in older users' interactions with desktop applications.
“This type of repeated non-unique and of-task selections has also been found in older users' interactions with desktop applications [42].”
Quote in the paperNot a substantial claim0 of 1 sources checked
- cites [42] 42. Shareen Mahmud, Jessalyn Alvina, Parmit K Chilana, Andrea Bunt, and Joanna McGrenere. 2020. Learning through exploration: how children, adults, and older adults interact with a new feature-rich application. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1-14. source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone given
The video corpus was tagged and classified using an existing codebook by the first author and supervised by the last author.
“Our video corpus was tagged and classifed using an existing codebook [42] by the frst author and supervised by the last author.”
Quote in the paperNot a substantial claim0 of 1 sources checked
- cites [42] 42. Shareen Mahmud, Jessalyn Alvina, Parmit K Chilana, Andrea Bunt, and Joanna McGrenere. 2020. Learning through exploration: how children, adults, and older adults interact with a new feature-rich application. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1-14. source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premisecitation
As we age, fluid intelligence declines and increases the difficulty in processing multiple information cues in parallel.
“Or it could be because as we age, our fuid intelligence declines and so increases the difculty in processing multiple information cues in parallel [21,44].”
Quote in the paperNot a substantial claim0 of 2 sources checked
- cites [21] 21. Graeme S Halford, Nelson Cowan, and Glenda Andrews. 2007. Separating cogni- tive capacity from knowledge: A new hypothesis. Trends in cognitive sciences 11, 6 (2007), 236-242. source
- cites [44] 44. Rui Mata, Lael J Schooler, and Jörg Rieskamp. 2007. The aging decision maker: cognitive aging and the adaptive selection of decision strategies. Psychology and aging 22, 4 (2007), 796. source
Probably not a substantial claim: may not pass S3 (load-bearing).
Interpretationown data
Non-use of the VA might have been a personal preference.
“Non-use might have been a personal preference, e.g., P7 mentioned post-study that”
Quote in the paperNot a substantial claim
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation
Validation-type articulations have also been reported in the literature when older users encountered interaction problems.
“These types of articulations have also been reported in the literature when older users encountered interaction problems [17,69].”
Quote in the paperNot a substantial claim0 of 2 sources checked
- cites [17] 17. Mingming Fan, Qiwen Zhao, and Vinita Tibdewal. 2021. Older adults' think-aloud verbalizations and speech features for identifying user experience problems. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 1-13. source
- cites [69] 69. Ja Eun Yu and Debaleena Chattopadhyay. 2020. "Maps are hard for me": How Older Adults Struggle with Mobile Maps. In The 22nd International ACM SIGAC- CESS Conference on Computers and Accessibility. in press. source
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Interpretationreasoning
Scaling our design solution to multiple views without negatively affecting the user's orientation would be a challenge.
“Scaling our design solution to multiple views without negatively afecting the user's orientation would be a challenge.”
Quote in the paperNot a substantial claim
May combine two claims.
Study design and conductown data
The study did not conduct a controlled study to compare the question types of older and younger users, so it cannot rule out contextual confounding factors.
“Second, we did not conduct a controlled study to compare the question types of older and younger users and thus, cannot rule out any contextual confounding factors that may have played a role.”
Quote in the paperNot a substantial claim

58 of 58

The paper relies on this without support.
Older adults' verbal questions during think-aloud can serve as input to a voice assistant.
“But we still do not know how older adults might articulate such a difculty verbally and whether that articulation can serve as an input to a voice assistant.”
“With a voice assistant, then, users could verbally ask about a function and receive visual cues that would reduce their search space of UI features.”
The paper relies on this without support.
A voice assistant that provides visual cues can reduce older adults' search space of UI features.
“With a voice assistant, then, users could verbally ask about a function and receive visual cues that would reduce their search space of UI features.”
The paper relies on this without support.
The five query types identified from older adults are sufficient to inform the design of a voice assistant.
“We inform the design of our voice-based assistant on data collected from our observations with older adults.”
The paper relies on this without support.
Older adults want to use technologies with family and friends across generations.
“They want to use technologies with family and friends across generations.”
The paper relies on this without support.
Any additional visual information on a UI would add to users' cognitive load and could make older users inefficient while trying to improve learnability.
“First, any additional visual information on a UI would add to users' cognitive load and could make older users inefcient while trying to improve learnability.”
The paper relies on this without support.
The mobile version of the study websites closely emulated similar native mobile apps in terms of front-end interactions.
“The mobile version of these websites closely emulated similar native mobile apps in terms of front-end interactions.”
The paper relies on this without support.
Not all mobile apps have comprehensive UI labels and descriptions.
“First, since UI labels and descriptions are optional, not all mobile apps have them in a comprehensive manner.”
The paper relies on this without support.
33% of 50-plus and 40% of 65-plus older adults recently reported user interface experience as a key barrier to tech use.
“33% of 50-plus and 40% of 65-plus older adults recently reported user interface experience as a key barrier to tech use.”

8 of 8

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Background
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Jakob, D., Wilhelm, S., Gerl, A., Ahrens, D., & Wahl, F. (2025) · Digital · doi:10.3390/digital5010004 · Cited by 17 · see citing works
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Influential
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“For instance, prior work shows that older adults experience greater difficulty navigating complex interfaces than younger users [45]–[49], often due to difficulty recognizing navigation structures, re-luctance to explore unfamiliar menus, and confusion between similar icons and buttons [45], [50],…”
Self-citation

Supporting Older Adults in Locating Mobile Interface Features with Voice Input
Yu, J. E., & Chattopadhyay, D. (2020) · International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS) · doi:10.1145/3373625.3418044 · Cited by 9 · see citing works
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Reducing the Search Space on demand helps Older Adults find Mobile UI Features quickly, on par with Younger Adults
Yu, J. E., & Chattopadhyay, D. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642796 · Cited by 16 · see citing works
Self-citation
Supporting Older Adults Navigate Feature-rich Mobile UIs with Voice Input
Yu, J. E. (2024) · Figshare · doi:10.25417/uic.26107303
Self-citation
How Do Older Adults Envision a Vocal Assistant? Results of a Voice User Interface Co-Design Session
Franceschetti, C., Marziali, R. A., Zanutto, O., Lionetti, L., Tombolesi, V., Rossi, L., & Rosa, M. D. (2024) · Lecture notes in bioengineering · doi:10.1007/978-3-031-77318-1_1

Authors: Yu, J. E., Parde, N., & Chattopadhyay, D.
Affiliations: University of Illinois Chicago (US)
ORCID: Yu, Ja Eun
Parde, Natalie
Chattopadhyay, Debaleena
Venue: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
Publisher: ACM
Published: 2023-04-19
Pages: 1-19
DOI: 10.1145/3544548.3581447
OpenAlex: W4366551350
Cited by: 22
References: 52
Citations by year: 2026: 9 · 2025: 5 · 2024: 5 · 2023: 3
FWCI: 20.09
Type: conference paper
Language: en
Open access: bronze
doi.org
Licence: www.acm.org/publications/policies/copyright_policy#Background (vor)
Locations: CHI Conference on Human Factors in Computing Systems (publishedVersion)
Topics: Social Sciences › Demography › Technology Use by Older Adults
Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
Social Sciences › Human Factors and Ergonomics › Digital Accessibility for Disabilities
Keywords: older adults, voice assistants, mobile user interface, feature location, query types, Wizard-of-Oz study, assistive technology design

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"Where is history": Toward Designing a Voice Assistant to help Older Adults locate Interface Features quickly

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