Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Nov 11, 2019
Date Accepted: Mar 23, 2020

The final, peer-reviewed published version of this preprint can be found here:

Exploring the Vast Choice of Question Prompt Lists Available to Health Consumers via Google: Environmental Scan

Tracy MC, Shepherd HL, Patel P, Trevena LJ

Exploring the Vast Choice of Question Prompt Lists Available to Health Consumers via Google: Environmental Scan

J Med Internet Res 2020;22(5):e17002

DOI: 10.2196/17002

PMID: 32469321

PMCID: 7293062

Spoilt for choice: An environmental scan of question prompt lists available via Google

  • Marguerite Clare Tracy; 
  • Heather L Shepherd; 
  • Pinika Patel; 
  • Lyndal Jane Trevena

ABSTRACT

Background:

There is increasing interest in shared decision making (SDM) in Australia. Question prompt lists (QPLs) support question asking by patients, a key part of SDM. QPLs have been studied in a variety of settings, and increasingly the internet provides a source of suggested questions for patients. Environmental scans have been shown to be useful in assessing the availability and quality of online SDM tools.

Objective:

To assess the number, clinical application, accessibility and readability of QPLs available to users via Google.com.au

Methods:

Our environmental scan used search terms derived from literature and reputable websites to search for QPLs available via Google.com.au. Following removal of duplicates from the 4000 URLs and 22 reputable sites, inclusion and exclusion criteria were applied to create a list of unique QPLs. QPLs were further assessed for list length, proxy measures of quality such as a date of review, and evidence of doctor endorsement. Readability of a sample on QPL instructions and the QPLs themselves was assessed using Flesch Reading Ease (FRE) and Flesch-Kincaid Grade Level (FK) scores.

Results:

Our environmental scan identified 173 unique QPLs available to users. Lists ranged in length from one question to over 200. Just over half (57%) had a listed date of creation or update and 24% had evidence of authorship or source. FK grade levels for instructions was higher than for the QPLs (Grade 8 cf. grade 5). There was a one and half grade difference between QPLs from reputable sites compared with other sites (4.1 cf. 5.6).

Conclusions:

People seeking questions to ask their doctor using Google.com.au encounter a vast number of questions lists which they can use to prepare for consultations with their doctors. Markers of the quality or usefulness of various types of online QPLs, surrogate or direct, have not yet been established which makes it difficult to assess the value of the abundance of lists. Doctor endorsement of question asking has previously been shown to be an important factor in the effectiveness of QPLs (Sansoni et al. 2014), but information regarding this is not readily available online. Whether these diverse question prompt lists are endorsed by medical practitioners warrants further investigation.


 Citation

Please cite as:

Tracy MC, Shepherd HL, Patel P, Trevena LJ

Exploring the Vast Choice of Question Prompt Lists Available to Health Consumers via Google: Environmental Scan

J Med Internet Res 2020;22(5):e17002

DOI: 10.2196/17002

PMID: 32469321

PMCID: 7293062

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.