Evidence map›Paper›PMID 30463840›Full record

ArticleJMIR cancer2018

Assessing Preference Shift and Effects on Patient Knowledge and Decisional Conflict: Cross-Sectional Study of an Interactive Prostate-Specific Antigen Test Patient Decision Aid.

Peter Scalia, Glyn Elwyn, Jan Kremer, Marjan Faber, Marie-Anne Durand

Abstract read
In one paragraph

Article in JMIR cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Systematic Development of Patient Decision Aids: An Update from the IPDAS Collaboration.Medical decision making : an international journal of the Society for Medical Decision Making · 2021
    Article
  3. The association between patients' preferred treatment after the use of a patient decision aid and their choice of eventual treatment.Health expectations : an international journal of public participation in health care and health policy · 2020
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Peter ScaliaThe Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College, Lebanon, NH, United States.ORCID http://orcid.org/0000-0002-5050-435X
Glyn ElwynThe Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College, Lebanon, NH, United States.ORCID http://orcid.org/0000-0002-0917-6286
Jan KremerRadboud Institute for Health Sciences, Scientific Institute for Quality of Healthcare, Radboud university medical center, Nijmegen, Netherlands.ORCID http://orcid.org/0000-0002-0495-0201
Marjan FaberRadboud Institute for Health Sciences, Scientific Institute for Quality of Healthcare, Radboud university medical center, Nijmegen, Netherlands.ORCID http://orcid.org/0000-0001-6491-7035
Marie-Anne DurandThe Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College, Lebanon, NH, United States.ORCID http://orcid.org/0000-0002-1127-9348

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRandomized trials of Web-based decision aids for prostate-specific antigen (PSA) testing indicate that these interventions improve knowledge and reduce decisional conflict. However, we do not know about these tools' impact on people who spontaneously use a PSA testing patient decision aid on the internet.

objectiveThe objectives of this study were to (1) determine the impact of the Web-based PSA Option Grid patient decision aid on preference shift, knowledge, and decisional conflict; (2) identify which frequently asked questions (FAQs) are associated with preference shift; and (3) explore the possible relationships between these outcomes.

methodsData were collected between January 1, 2016, and December 30, 2017. Users who accessed the Web-based, interactive PSA Option Grid were provided with 3 options: have a PSA test, no PSA test, or unsure. Users first declared their initial preference and then completed 5 knowledge questions and a 4-item (yes or no) validated decisional conflict scale (Sure of myself, Understand information, Risk-benefit ratio, Encouragement; SURE). Next, users were presented with 10 FAQs and asked to identify their preference for each question based on the information provided. At the end, users declared their final preference and completed the same knowledge and decisional conflict questions. Paired sample t tests were employed to compare before and after knowledge and decisional conflict scores. A multinomial regression analysis was performed to determine which FAQs were associated with a shift in screening preference.

resultsOf all the people who accessed the PSA Option Grid, 39.8% (186/467) completed the interactive journey and associated surveys. After excluding 22 female users, we analyzed 164 responses. At completion, users shifted their preference to "not having the PSA test" (43/164, 26.2%, vs 117/164, 71.3%; P<.001), had higher levels of knowledge (112/164, 68.3%, vs 146/164, 89.0%; P<.001), and lower decisional conflict (94/164, 57.3%, vs 18/164, 11.0%; P<.001). There were 3 FAQs associated with preference shift: "What does the test involve?" "If my PSA level is high, what are the chances that I have prostate cancer?" and "What are the risks?" We did not find any relationship between knowledge, decisional conflict, and preference shift.

conclusionsUnprompted use of the interactive PSA Option Grid leads to preference shift, increased knowledge, and reduced decisional conflict, which confirms the ability of these tools to influence decision making, even when used outside clinical encounters.

Indexed as

conflictdecision aidsdecision makingpatient preferenceprostate screeningprostate-specific antigen

Identifiers

PMID30463840
PMCPMC6282011

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.