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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Oct 16, 2019
Open Peer Review Period: Oct 2, 2019 - Nov 14, 2019
Date Accepted: Mar 22, 2020
Date Submitted to PubMed: Apr 29, 2020
(closed for review but you can still tweet)

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

Electronic Data Capture Versus Conventional Data Collection Methods in Clinical Pain Studies: Systematic Review and Meta-Analysis

Jibb LA, Khan JS, Seth P, Lalloo C, Mulrooney L, Nicholson K, Nowak DA, Kaur H, Chee-A-Tow A, Foster J, Stinson JN

Electronic Data Capture Versus Conventional Data Collection Methods in Clinical Pain Studies: Systematic Review and Meta-Analysis

J Med Internet Res 2020;22(6):e16480

DOI: 10.2196/16480

PMID: 32348259

PMCID: 7351264

Electronic data capture versus conventional data collection methods in clinical pain studies: a systematic review and meta-analysis

  • Lindsay A. Jibb; 
  • James S. Khan; 
  • Puneet Seth; 
  • Chitra Lalloo; 
  • Lauren Mulrooney; 
  • Kathryn Nicholson; 
  • Dominik A. Nowak; 
  • Harneel Kaur; 
  • Alyssandra Chee-A-Tow; 
  • Joel Foster; 
  • Jennifer N Stinson

ABSTRACT

Background:

The most commonly used means to assess pain is through patient self-reported questionnaires. These questionnaires have traditionally been completed using paper-and-pencil, telephone, or in-person methods, which may result in the introduction of several reporting biases and data entry errors into the collected data. Electronic data capture methods represent a potential way to validly, reliably and feasibly collect pain-related data from patients in both clinical and research settings.

Objective:

The aim of this study was to conduct a systematic review and meta-analysis to compare electronic and conventional pain-related data collection methods with respect to pain score equivalence, data completeness, ease of use, efficiency, and acceptability between methods.

Methods:

We searched MEDLINE, Embase, and Cochrane CENTRAL from database inception until January 2018. We included all peer-reviewed studies that compared electronic (any modality) and conventional (paper-, telephone-, or in-person-based) patient-reported pain data capture methods if the comparison focused on: pain score equivalence, data completeness, ease of use, efficiency, or acceptability. We used random-effects models to combine score equivalence data across the studies that reported correlations or measures of agreement between electronic and conventional pain assessment methods.

Results:

A total of 45 studies were included in this systematic review, of which 20 were included in the meta-analysis component. Overall, pain scores reported electronically were congruent with those reported using conventional modalities and the majority of studies (86.1%) reporting on this outcome demonstrated this relationship. The weighted summary correlation coefficient of pain score equivalence from our meta-analysis was 0.94 (95% CI 0.90–0.96). Study reports of data completeness, patient- or provider-reported ease of use, and efficiency generally indicated that electronic data capture methods were equivalent or superior to conventional methods. Most (62.1%) studies that directly surveyed patients reported that the electronic format was the preferred data collection method.

Conclusions:

Electronic pain-related data capture methods are comparable to conventional methods in terms of score equivalence, data completeness, ease, efficiency and acceptability and, if the appropriate psychometric evaluations are in place, are a feasible means to collect pain data in clinical and research settings.


 Citation

Please cite as:

Jibb LA, Khan JS, Seth P, Lalloo C, Mulrooney L, Nicholson K, Nowak DA, Kaur H, Chee-A-Tow A, Foster J, Stinson JN

Electronic Data Capture Versus Conventional Data Collection Methods in Clinical Pain Studies: Systematic Review and Meta-Analysis

J Med Internet Res 2020;22(6):e16480

DOI: 10.2196/16480

PMID: 32348259

PMCID: 7351264

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