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Patient AI Trust Dynamics Before and After Orthopedic Consultation (ORTHO-OP-GPT) (ORTHO-OP-GPT)

1. června 2026 aktualizováno: Utku Gürhan

Longitudinal Pre-Post Patient AI Trust Dynamics in Orthopedic Outpatients: A Mixed-Methods Observational Study With Matched Physician-Patient Dyads

Patients increasingly consult artificial intelligence (AI) chatbots such as ChatGPT for health information before clinical visits, yet the impact of an actual orthopedic consultation on patient trust in AI-derived information remains unknown. This prospective longitudinal observational study quantifies how a single orthopedic outpatient consultation modifies patient trust in AI chatbots, the concordance between AI-derived and physician-delivered information, and patient anxiety, using a paired pre-post survey design supplemented by a matched physician-side assessment. Adult patients (18 years and older) presenting to two orthopedic outpatient clinics in Cyprus complete a brief pre-consultation questionnaire (T0) capturing demographics, AI use patterns, prior AI consultation regarding the current complaint, baseline trust, expectations, and anxiety. Immediately after their consultation they complete a second questionnaire (T1) assessing concordance with physician advice, trust change, consultation facilitation, post-consultation anxiety, and future intention. The consulting physician completes a brief 30-second post-visit form capturing whether AI was discussed, the medical accuracy of AI-derived information conveyed by the patient, and the effect of the AI discussion on consultation duration. The primary outcomes are the paired within-patient change in AI trust between T0 and T1 and physician-patient concordance on AI versus physician advice. Target enrollment is 180 to obtain 150 paired completed assessments.

Přehled studie

Postavení

Zatím nenabíráme

Podmínky

Detailní popis

Background and Rationale: Cross-sectional surveys have documented increasing patient use of AI chatbots for health information seeking. However, no published study has assessed how an actual physician consultation modifies patient trust in AI in a paired pre/post design, nor has any study captured the physician perspective on the same encounter in a matched dyad. Routine clinical encounters may be the primary mechanism by which patients calibrate their trust in AI-derived medical information.

Setting and Population: Two university-affiliated orthopedic outpatient clinics in North Cyprus.

Procedures:

  • T0 (pre-consultation, waiting room, approximately 5 minutes): 14-item self-report questionnaire.
  • Consultation: usual care.
  • T1 (post-consultation, departure, approximately 5 minutes): 10-item self-report questionnaire.
  • Physician form (post-consultation, approximately 30 seconds): 5-item brief assessment.
  • Patient and physician forms are linked by an anonymous Participant ID.

Statistical Analysis Plan: Paired t-tests or Wilcoxon signed-rank tests for paired continuous outcomes; McNemar test or Stuart-Maxwell for paired categorical outcomes; Cohen's kappa for inter-rater agreement (AI versus physician); multinomial logistic regression for predictors of trust shift. All analyses two-sided, alpha equals 0.05. SPSS version 28.

Data Management: Anonymous CSV stored locally, encrypted, retained for 5 years per institutional policy. De-identified participant-level data available upon reasonable request after publication.

No formal pilot study is conducted. Instead, the first 20 participants will be prospectively monitored for protocol feasibility (mean completion time, drop-out rate, item-level missing data) as an embedded running pilot.

Typ studie

Pozorovací

Zápis (Odhadovaný)

180

Kontakty a umístění

Tato část poskytuje kontaktní údaje pro ty, kteří studii provádějí, a informace o tom, kde se tato studie provádí.

Studijní kontakt

Studijní místa

  • Kypr
      • Kyrenia, Kypr
        • University of Kyrenia, Dr. Suat Gunsel Hospital - Orthopedic Outpatient Clinic
        • Kontakt:
        • Vrchní vyšetřovatel:
          • Utku Gurhan, MD
      • Nicosia, Kypr
        • Near East University Hospital - Orthopedic Outpatient Clinic

Kritéria účasti

Výzkumníci hledají lidi, kteří odpovídají určitému popisu, kterému se říká kritéria způsobilosti. Některé příklady těchto kritérií jsou celkový zdravotní stav osoby nebo předchozí léčba.

Kritéria způsobilosti

Věk způsobilý ke studiu

  • Dospělý
  • Starší dospělý

Přijímá zdravé dobrovolníky

Ne

Metoda odběru vzorků

Vzorek nepravděpodobnosti

Studijní populace

Consecutive adult patients (18 years and older) presenting to the participating orthopedic outpatient clinics during the recruitment window who consent to participate. No specific orthopedic diagnosis is required.

Popis

Inclusion Criteria:

  • Age 18 years or older
  • Presenting to an orthopedic outpatient clinic for any consultation
  • Able to read and respond to a Turkish-language questionnaire
  • Provides informed consent

Exclusion Criteria:

  • Inability to complete a self-report questionnaire (e.g., severe cognitive impairment, language barrier)
  • Re-presentation within the same recruitment window (each patient is enrolled only once)
  • Refusal of consent for either T0 or T1

Studijní plán

Tato část poskytuje podrobnosti o studijním plánu, včetně toho, jak je studie navržena a co studie měří.

Jak je studie koncipována?

Detaily designu

Co je měření studie?

Primární výstupní opatření

Měření výsledku
Popis opatření
Časové okno
Mean within-patient change in self-reported trust in artificial intelligence-derived health information, measured by a study-specific 5-point Likert item (T0.11) and a study-specific 3-level categorical change item (T1.4).
Časové okno: Baseline (within 15 minutes pre-consultation in the orthopaedic outpatient waiting room) and immediately after the consultation (within 15 minutes of consultation exit, same-day index visit).
Trust in AI-derived health information is assessed pre-consultation by a study-specific single-item 5-point Likert scale (item T0.11: "How much do you trust the AI's answer?"; anchors 1 = not at all, 5 = completely), administered only to patients who reported pre-consultation AI use (item T0.9 = Yes). Post-consultation, trust change is reassessed by a study-specific 3-level categorical item (item T1.4: increased trust / unchanged / decreased trust). For paired analysis, the post-consultation score is derived by mapping T1.4 categories to integer shifts (+1 / 0 / -1, with floor 1 and ceiling 5) relative to T0.11. Unit of measure: Likert score points on a 1-5 scale (continuous derived score) and proportion of patients per 3-level category. Primary analysis: paired Wilcoxon signed-rank test on the derived continuous score; sensitivity analysis: McNemar test on the 3-level categorical change.
Baseline (within 15 minutes pre-consultation in the orthopaedic outpatient waiting room) and immediately after the consultation (within 15 minutes of consultation exit, same-day index visit).
Patient-physician concordance on artificial intelligence-versus-physician medical advice agreement, measured by Cohen's kappa coefficient between a study-specific 4-category patient item (T1.2) and a study-specific 5-point physician-rated AI medical accu
Časové okno: Immediately after the consultation (within 15 minutes of consultation exit), for both patient (T1.2) and physician (H2) forms; same-day index visit.
Concordance is assessed by Cohen's kappa coefficient comparing patient-reported AI-physician concordance (item T1.2: fully concordant / partially concordant / discordant / physician did not address; dichotomized to concordant vs. non-concordant) and physician-reported AI medical accuracy (item H2: 5-point Likert anchored 1 = entirely incorrect to 5 = entirely correct; dichotomized at ≥ 3 as concordant). Unit of measure: kappa coefficient (range -1 to +1) with 95% confidence interval, and percentage of dyads classified as concordant on each instrument.
Immediately after the consultation (within 15 minutes of consultation exit), for both patient (T1.2) and physician (H2) forms; same-day index visit.

Sekundární výstupní opatření

Měření výsledku
Popis opatření
Časové okno
Mean within-patient change in self-reported anxiety, measured by an 11-point 0-to-10 visual analogue scale anchored 0 = no anxiety and 10 = worst possible anxiety (items T0.14 baseline, T1.5 post-consultation).
Časové okno: Baseline (within 15 minutes pre-consultation) and immediately after the consultation (within 15 minutes of consultation exit), same-day index visit.
Anxiety is measured pre-consultation (item T0.14) and post-consultation (item T1.5) using the same 0-to-10 visual analogue scale. Within-patient change is calculated as T1.5 minus T0.14. Unit of measure: scale points (range -10 to +10). Analysis: paired t-test with Wilcoxon signed-rank as sensitivity analysis; Cohen's d effect size reported.
Baseline (within 15 minutes pre-consultation) and immediately after the consultation (within 15 minutes of consultation exit), same-day index visit.
Percentage of enrolled patients reporting pre-consultation artificial intelligence use for the current orthopaedic complaint, measured by a study-specific single-item yes/no question (T0.9).
Časové okno: Baseline (within 15 minutes pre-consultation, same-day index visit).
Proportion of enrolled patients responding "Yes" to item T0.9 ("Before today's appointment, did you ask an AI chatbot a question about this health concern?"). Unit of measure: percentage of participants, reported with exact (Clopper-Pearson) 95% confidence interval.
Baseline (within 15 minutes pre-consultation, same-day index visit).
Percentage of pre-consultation artificial-intelligence users whose physician independently confirmed that AI was raised during the consultation, measured by a study-specific yes/no physician item (H1).
Časové okno: Baseline (T0.9, pre-consultation) and immediately after the consultation (H1, within 15 minutes of consultation exit), same-day index visit.
Among patients responding "Yes" to T0.9, the proportion in whom the treating physician independently reported "Yes" to item H1 ("Did the patient raise AI during this consultation?"). Unit of measure: percentage of patients with exact 95% confidence interval.
Baseline (T0.9, pre-consultation) and immediately after the consultation (H1, within 15 minutes of consultation exit), same-day index visit.
Percentage of consultations in which the physician reported that the artificial-intelligence discussion shortened, did not change, or prolonged the encounter, measured by a study-specific 3-category physician item (H3).
Časové okno: Immediately after the consultation (within 15 minutes of consultation exit), same-day index visit.
Among consultations in which the patient raised AI (H1 = Yes), the physician's categorical rating of effect on consultation duration (H3: "shortened" / "no change" / "prolonged"). Unit of measure: percentage of consultations per category (descriptive).
Immediately after the consultation (within 15 minutes of consultation exit), same-day index visit.
Mean patient rating of how prior artificial-intelligence use facilitated the consultation, measured by a study-specific 5-point Likert item (T1.4b: 1 = much more difficult, 5 = much easier).
Časové okno: Immediately after the consultation (within 15 minutes of consultation exit), same-day index visit.
Among patients with T0.9 = Yes, patient-reported facilitation by prior AI use (item T1.4b). Unit of measure: Likert score points (mean with standard deviation), and percentage of participants endorsing scores ≥ 4.
Immediately after the consultation (within 15 minutes of consultation exit), same-day index visit.
Mean patient-reported future intention to use and to recommend artificial intelligence for health information, measured by two study-specific 5-point Likert items (T1.7 future use; T1.8 recommendation to a friend).
Časové okno: Immediately after the consultation (within 15 minutes of consultation exit), same-day index visit.
Future-use intention (item T1.7: 1 = definitely will not, 5 = definitely will) and recommendation intention (item T1.8: 1 = definitely will not, 5 = definitely will). Unit of measure: Likert score points (mean with standard deviation), and percentage of participants endorsing scores ≥ 4 on each item.
Immediately after the consultation (within 15 minutes of consultation exit), same-day index visit.

Další výstupní opatření

Měření výsledku
Popis opatření
Časové okno
Exploratory association between categorical post-consultation trust change and demographic predictors, estimated by multinomial logistic regression with the study-specific 3-level trust change item (T1.4) as the outcome and age band, sex, education level
Časové okno: Through study completion, an average of 12 months from first enrolment.
Multinomial logistic regression model: outcome = T1.4 (decreased / unchanged / increased trust, reference category = unchanged); predictors = age band (5-level), sex (3-level), education (5-level), employment status, weekly internet-use frequency. Unit of measure: adjusted odds ratios with 95% confidence intervals.
Through study completion, an average of 12 months from first enrolment.
Internal consistency of a four-item artificial-intelligence trust subscale, measured by Cronbach's alpha across items T0.11 (baseline trust), T1.4 (post-consultation trust change, linearly recoded), T1.7 (future-use intention), and T1.8 (recommendation
Časové okno: Through study completion, an average of 12 months from first enrolment.
Cronbach's alpha is estimated on the final analytic sample using the four trust-related Likert items listed. Unit of measure: alpha coefficient (range 0 to 1) with bootstrap 95% confidence interval.
Through study completion, an average of 12 months from first enrolment.

Spolupracovníci a vyšetřovatelé

Zde najdete lidi a organizace zapojené do této studie.

Sponzor

Utku Gürhan

Vyšetřovatelé

  • Vrchní vyšetřovatel: Utku Gurhan, MD, University of Kyrenia

Publikace a užitečné odkazy

Osoba odpovědná za zadávání informací o studiu tyto publikace poskytuje dobrovolně. Mohou se týkat čehokoli, co souvisí se studiem.

Obecné publikace

Termíny studijních záznamů

Tato data sledují průběh záznamů studie a předkládání souhrnných výsledků na ClinicalTrials.gov. Záznamy ze studií a hlášené výsledky jsou před zveřejněním na veřejné webové stránce přezkoumány Národní lékařskou knihovnou (NLM), aby se ujistily, že splňují specifické standardy kontroly kvality.

Hlavní termíny studia

Začátek studia (Odhadovaný)

1. června 2026

Primární dokončení (Odhadovaný)

1. listopadu 2026

Dokončení studie (Odhadovaný)

1. ledna 2027

Termíny zápisu do studia

První předloženo

18. května 2026

První předloženo, které splnilo kritéria kontroly kvality

1. června 2026

První zveřejněno (Aktuální)

8. června 2026

Aktualizace studijních záznamů

Poslední zveřejněná aktualizace (Aktuální)

8. června 2026

Odeslaná poslední aktualizace, která splnila kritéria kontroly kvality

1. června 2026

Naposledy ověřeno

1. června 2026

Více informací

Termíny související s touto studií

Klíčová slova

Další identifikační čísla studie

  • ORTHO-OP-GPT-2026

Plán pro data jednotlivých účastníků (IPD)

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