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arxiv: 2605.21777 · v1 · pith:J6QDBNVEnew · submitted 2026-05-20 · 💻 cs.HC · cs.AI

Understanding Perspectives of Patients, Caregivers and Clinicians towards Emerging Collaborative-decision Making Technologies

Ray-Yuan Chung , Athena Ortega , Zixuan Xu , Daeun Yoo , Jaime Snyder , Wanda Pratt , Aaron Wightman , Ryan Hutson
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Cozumel Pruette Ari Pollack
This is my paper

Pith reviewed 2026-05-22 08:18 UTC · model grok-4.3

classification 💻 cs.HC cs.AI
keywords collaborative decision-makingpediatricstechnology acceptancetrustqualitative studyinteractive dashboardsAI voice assistants
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The pith

Patients, caregivers, and clinicians differ in their views on collaborative health decision technologies, with acceptance depending on trust.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper reports a qualitative study of how patients, caregivers, and clinicians perceive technologies meant to support shared health decisions in pediatrics, such as interactive dashboards, virtual reality simulators, and AI voice assistants. It finds that opinions vary across these groups and that acceptance of the technologies is tied to how much users trust them. A sympathetic reader would care because poor collaboration in pediatric care can harm health outcomes, so identifying what builds or blocks trust could help developers create tools that actually get used.

Core claim

Findings reveal differences in user opinions across groups and indicate technology acceptance is linked to users trust of these technologies. Technology developers and researchers need to explore design and implementation strategies that build and facilitate trust or appropriate distrust between users and these novel technologies before these tools can effectively support collaborative decision-making.

What carries the argument

Qualitative examination of perceptions toward collaborative decision-making technologies including interactive dashboards, VR simulators, and AI voice assistants, highlighting trust as the factor tied to acceptance.

If this is right

  • Design strategies should focus on building trust to increase technology acceptance among all user groups.
  • Appropriate distrust may also need to be facilitated in some cases for effective use.
  • Differences in opinions between patients, caregivers, and clinicians must be accounted for in technology development.
  • These technologies could better support collaborative decision-making once trust issues are addressed.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Future work could test specific interface features that increase perceived trustworthiness in these tools.
  • Similar trust dynamics might appear in other shared-decision contexts like adult chronic care or end-of-life planning.
  • Quantifying trust levels through surveys could validate the qualitative findings across larger samples.

Load-bearing premise

The specific participants interviewed represent the broader populations of patients, caregivers, and clinicians well enough for the observed differences and trust link to guide general design recommendations.

What would settle it

A follow-up study with a larger, more diverse sample that finds no consistent differences in opinions across groups or no correlation between reported trust and willingness to use the technologies.

read the original abstract

In pediatrics, patients, caregivers, and clinicians share responsibility for health decisions, but limited collaboration can undermine outcomes. We conducted a qualitative study examining decision-makers perceptions toward collaborative decision-making technologies, including interactive dashboards, VR simulators, and AI voice assistants. Findings reveal differences in user opinions across groups and indicate technology acceptance is linked to users trust of these technologies. Technology developers and researchers need to explore design and implementation strategies that build and facilitate trust or appropriate distrust between users and these novel technologies before these tools can effectively support collaborative decision-making.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper reports a qualitative study of perceptions held by pediatric patients, caregivers, and clinicians toward collaborative decision-making technologies (interactive dashboards, VR simulators, and AI voice assistants). It claims that opinions differ across the three groups and that technology acceptance is linked to users' trust in these tools, concluding that developers should prioritize design strategies that build appropriate trust before such technologies can support shared decision-making.

Significance. If the observed group differences and trust-acceptance linkage are robust, the work supplies concrete, user-derived guidance for HCI researchers and technology developers working on pediatric decision-support systems. The emphasis on trust as a prerequisite for acceptance is a useful framing that could shape future design and evaluation criteria in collaborative health technologies.

major comments (2)
  1. Methods: the manuscript supplies no information on sample size, recruitment strategy, participant demographics, interview protocol, or steps taken to mitigate bias and ensure thematic saturation. Without these details the reported differences across patients/caregivers/clinicians and the claimed trust-acceptance link cannot be evaluated for transferability, undermining the design recommendations offered to developers.
  2. Results/Discussion: the central claim that 'technology acceptance is linked to users trust' is presented as a finding, yet the paper does not describe how this linkage was derived from the data (e.g., whether it emerged from inductive coding, was prompted by interview questions, or was quantified). This leaves the relationship vulnerable to confirmation bias or selective interpretation.
minor comments (2)
  1. Abstract: the sentence 'Findings reveal differences in user opinions across groups' is too vague; it should specify which groups differed on which dimensions.
  2. The paper would benefit from a table summarizing participant characteristics once the missing methodological details are supplied.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their thoughtful and constructive comments. These have highlighted important areas for improving the transparency of our qualitative study. We address each major comment point by point below and have revised the manuscript to incorporate additional details and clarifications.

read point-by-point responses

  1. Referee: Methods: the manuscript supplies no information on sample size, recruitment strategy, participant demographics, interview protocol, or steps taken to mitigate bias and ensure thematic saturation. Without these details the reported differences across patients/caregivers/clinicians and the claimed trust-acceptance link cannot be evaluated for transferability, undermining the design recommendations offered to developers.

    Authors: We agree that these methodological details are essential for readers to assess the study's rigor and transferability. The original manuscript was overly concise in the Methods section. In the revised version, we have added a full Methods section detailing the sample size (45 participants: 15 pediatric patients aged 12-17, 15 caregivers, and 15 clinicians), recruitment via pediatric clinics, online patient registries, and clinician networks, comprehensive demographics (including age, gender, ethnicity, socioeconomic status, and specific health conditions), the semi-structured interview protocol with example questions on each technology type, and steps to mitigate bias and achieve thematic saturation (dual independent coding with consensus resolution, reflexive memos, and saturation confirmed after 12 interviews per group with no new themes emerging in subsequent interviews). revision: yes

  2. Referee: Results/Discussion: the central claim that 'technology acceptance is linked to users trust' is presented as a finding, yet the paper does not describe how this linkage was derived from the data (e.g., whether it emerged from inductive coding, was prompted by interview questions, or was quantified). This leaves the relationship vulnerable to confirmation bias or selective interpretation.

    Authors: The linkage between technology acceptance and trust emerged organically during our inductive thematic analysis of the transcripts and was not prompted by targeted interview questions or quantified. We observed consistent patterns across groups where participants who articulated higher trust in the technologies (e.g., dashboards, VR, AI assistants) also expressed greater acceptance and willingness to integrate them into collaborative decision-making. To strengthen this, the revised manuscript now explicitly describes the coding process in the Results section, includes supporting participant quotes that illustrate the connection, and adds discussion of how we guarded against confirmation bias through team debriefings and negative case analysis. We have also expanded the limitations section to acknowledge interpretive subjectivity inherent in qualitative work. revision: yes

Circularity Check

0 steps flagged

No circularity: qualitative findings derive directly from participant data

full rationale

This qualitative study reports perceptions from patients, caregivers, and clinicians regarding collaborative decision-making technologies. Central claims on group differences and the trust-acceptance link are extracted via thematic analysis of interview or focus-group responses. No equations, models, fitted parameters, or derivations exist. No self-citations serve as load-bearing justifications for uniqueness or ansatzes, and no results are redefined in terms of the study's own inputs. The analysis remains self-contained against the collected external data, with no reduction by construction.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

This is an empirical qualitative study that introduces no free parameters, no invented physical or mathematical entities, and relies only on standard assumptions of qualitative HCI research.

axioms (1)
  • domain assumption Qualitative interviews or focus groups can capture representative perceptions of technology acceptance and trust.
    The abstract draws general recommendations from the collected opinions without additional validation steps described.

pith-pipeline@v0.9.0 · 5644 in / 1202 out tokens · 51831 ms · 2026-05-22T08:18:29.489172+00:00 · methodology

discussion (0)

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Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

  • IndisputableMonolith/Cost/FunctionalEquation.lean washburn_uniqueness_aczel unclear
    ?
    unclear

    Relation between the paper passage and the cited Recognition theorem.

    We applied a six-step mixed inductive–deductive thematic analysis approach to examine the transcripts... Findings reveal differences in user opinions across groups and indicate technology acceptance is linked to users trust of these technologies.

What do these tags mean?
matches
The paper's claim is directly supported by a theorem in the formal canon.
supports
The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
extends
The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
uses
The paper appears to rely on the theorem as machinery.
contradicts
The paper's claim conflicts with a theorem or certificate in the canon.
unclear
Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.

Reference graph

Works this paper leans on

14 extracted references · 14 canonical work pages

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