Cited by 24Patient-Provider Communication in HealthcareHealth Literacy and Information AccessibilityTelemedicine and Telehealth Implementation

Evaluation of a virtual dialogue method for breast cancer patient education

Harless, William G., Zier, Marcia A., Harless, Michael G., Duncan, Robert C., Braun, Mary Ann, Willey, Shawna, Isaacs, Claudine, Warren, Robert D.·2009·Patient Education and Counseling

Abstract

Objective Virtual dialogue--a voice-activated, interactive computer model that enables a user to have an individual virtual conversation with a real person--was evaluated as a method to educate women about breast cancer. Virtual dialogues with breast cancer experts were developed and used in a field study by women with and without the disease to assess the method's effectiveness.Methods In a clinical setting, subjects engaged in one-on-one virtual dialogues with an oncologist and a breast surgeon, and completed automated pre-post instruments developed to measure the feasibility of the method, and subjects' knowledge gain and acceptance of the method.Results Seventy women, 39 with breast cancer and 31 without the disease, participated. The data demonstrated the feasibility and acceptance of the method, and significant learning gain across all subjects.Conclusion Virtual dialogues with knowledgeable health professionals can be a new and effective method for educating women about breast cancer.Practice implications Virtual dialogues may systematically comfort patients while providing them with comprehensive and reliable basic information about breast cancer. The method may also give health care providers more time to address their patients' specific concerns.

Integrity signals

Registry

Crossref · 10.1016/j.pec.2009.02.006

Cites

19 of 19 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Harless, W. G., Zier, M. A., Harless, M. G., Duncan, R. C., Braun, M. A., Willey, S., Isaacs, C., & Warren, R. D.
Affiliations
  • Interactive Drama (United States) (US)
  • University of Miami (US)
  • George Mason University (US)
  • Georgetown University Medical Center (US)
Corresponding author
Zier, Marcia A.
Venue
Patient Education and Counseling
Publisher
Elsevier BV
Published
2009-08
Volume
76
Issue
2
Pages
189-195
ISSN
0738-3991 (ISSN-L)
OpenAlex
W1994626129
Cited by
24
References
19
Citations by year
2025: 2 · 2024: 1 · 2023: 1 · 2022: 3 · 2021: 1 · 2020: 1 · 2019: 2 · 2017: 1 · 2016: 1 · 2015: 1 · 2014: 4 · 2013: 2 · 2012: 1
FWCI
2.42
Type
journal article
Language
en
Open access
closed
Locations
  • Patient Education and Counseling (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • National Institutes of Health (5r44nr005103-03, 1r43nr005103-01)
  • National Institute of Nursing Research (1R44NR05103, 1R43NR05103)
Topics
  • Health Sciences › Health Professions › General Health Professions › Patient-Provider Communication in Healthcare
  • Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
Keywords
online discourse, breast cancer, patient education, interactive computer model, knowledge improvement, feasibility, acceptability, breast cancer patients, oncologists, breast surgeons, patient-provider communication
MeSH terms
Adult, Aged, Aged, 80 and over, Artificial Intelligence, Breast Neoplasms, Communication, Computer Simulation, Feasibility Studies, Female, Humans, Middle Aged, Patient Education as Topic, Physician-Patient Relations, Surveys and Questionnaires, User-Computer Interface, Internet, Speech Recognition Software

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review