The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Equivalence of electronic and paper administration of patient-reported outcome measures: a systematic review and meta-analysis of studies conducted between 2007 and 2013
Open accessAbstract
Objective: To conduct a systematic review and meta-analysis of the equivalence between electronic and paper administration of patient reported outcome measures (PROMs) in studies conducted subsequent to those included in Gwaltney et al’s 2008 review. Methods: A systematic literature review of PROM equivalence studies conducted between 2007 and 2013 identified 1,997 records from which 72 studies met pre-defined inclusion/exclusion criteria. PRO data from each study were extracted, in terms of both correlation coefficients (ICCs, Spearman and Pearson correlations, Kappa statistics) and mean differences (standardized by the standard deviation, SD, and the response scale range). Pooled estimates of correlation and mean difference were estimated. The modifying effects of mode of administration, year of publication, study design, time interval between administrations, mean age of participants and publication type were examined. Results: Four hundred thirty-five individual correlations were extracted, these correlations being highly variable (I2 = 93.8) but showing generally good equivalence, with ICCs ranging from 0.65 to 0.99 and the pooled correlation coefficient being 0.88 (95 % CI 0.87 to 0.88). Standardised mean differences for 307 studies were small and less variable (I2 = 33.5) with a pooled standardised mean difference of 0.037 (95 % CI 0.031 to 0.042). Average administration mode/platform-specific correlations from 56 studies (61 estimates) had a pooled estimate of 0.88 (95 % CI 0.86 to 0.90) and were still highly variable (I2 = 92.1). Similarly, average platform-specific ICCs from 39 studies (42 estimates) had a pooled estimate of 0.90 (95 % CI 0.88 to 0.92) with an I2 of 91.5. After excluding 20 studies with outlying correlation coefficients (≥3SD from the mean), the I2 was 54.4, with the equivalence still high, the overall pooled correlation coefficient being 0.88 (95 % CI 0.87 to 0.88). Agreement was found to be greater in more recent studies (p < 0.001), in randomized studies compared with non-randomised studies (p < 0.001), in studies with a shorter interval (<1 day) (p < 0.001), and in respondents of mean age 28 to 55 compared with those either younger or older (p < 0.001). In terms of mode/platform, paper vs Interactive Voice Response System (IVRS) comparisons had the lowest pooled agreement and paper vs tablet/touch screen the highest (p < 0.001). Conclusion: The present study supports the conclusion of Gwaltney’s previous meta-analysis showing that PROMs administered on paper are quantitatively comparable with measures administered on an electronic device. It also confirms the ISPOR Taskforce´s conclusion that quantitative equivalence studies are not required for migrations with minor change only. This finding should be reassuring to investigators, regulators and sponsors using questionnaires on electronic devicesafter migration using best practices. Although there is data indicating that migrations with moderate changes produce equivalent instrument versions, hence do not require quantitative equivalence studies, additional work is necessary to establish this. Furthermore, there is the need to standardize migration practices and reporting practices (i.e. include copies of tested instrument versions and screenshots) so that clear recommendations regarding equivalence testing can be made in the future.raising questions about the necessity of conducting equivalence testing moving forward.
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Intraclass correlations: Uses in assessing rater reliability.
Shrout, P. E., & Fleiss, J. L. (1979) · Psychological Bulletin · doi:10.1037/0033-2909.86.2.420 · Cited by 24,532
von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., Vandenbroucke, J. P., & Initiative, F. T. S. (2007) · PLoS Medicine · doi:10.1371/journal.pmed.0040296 · Cited by 23,020
von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., Vandenbroucke, J. P., & Initiative, F. T. S. (2007) · Annals of Internal Medicine · doi:10.7326/0003-4819-147-8-200710160-00010 · Cited by 17,796
Forming inferences about some intraclass correlation coefficients.
McGraw, K. O., & Wong, S. P. (1996) · Psychological Methods · doi:10.1037/1082-989x.1.1.30 · Cited by 6,903
U.S. Department of Health and Human Services FDA Center for Drug Evaluation and Research, U.S. Department of Health and Human Services FDA Center for Biologics Evaluation and Research, & U.S. Department of Health and Human Services FDA Center for Devices and Radiological Health (2006) · Health and Quality of Life Outcomes · doi:10.1186/1477-7525-4-79 · Cited by 2,856
von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., & Vandenbroucke, J. P. (2007) · Preventive Medicine · doi:10.1016/j.ypmed.2007.08.012 · Cited by 2,698
Patient non-compliance with paper diaries
Stone, A. A., Shiffman, S., Schwartz, J. E., Broderick, J. E., & Hufford, M. R. (2002) · BMJ · doi:10.1136/bmj.324.7347.1193 · Cited by 810
Gwaltney, C. J., Shields, A. L., & Shiffman, S. (2008) · Value in Health · doi:10.1111/j.1524-4733.2007.00231.x · Cited by 623
Carlbring, P., Brunt, S., Bohman, S., Austin, D., Richards, J., Öst, L.-G., & Andersson, G. (2007) · Computers in Human Behavior · doi:10.1016/j.chb.2005.05.002 · Cited by 319 · cited 1×
“[27] 2007 Web/PC C Y N 494 Panic disorder 37.”
BackgroundHolländare, F., Andersson, G., & Engström, I. (2010) · Journal of Medical Internet Research · doi:10.2196/jmir.1392 · Cited by 179
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Benefits and Disadvantages of Electronic Patient-reported Outcome Measures: Systematic Review
Meirte, J., Hellemans, N., Anthonissen, M., Denteneer, L., Maertens, K., Moortgat, P., & Van Daele, U. (2020) · JMIR Perioperative Medicine · doi:10.2196/15588 · Cited by 308
Quality of life assessment instruments for adults: a systematic review of population-based studies
Pequeno, N. P. F., Cabral, N. L. D. A., Marchioni, D. M., Lima, S. C. V. C., & Lyra, C. D. O. (2020) · Health and Quality of Life Outcomes · doi:10.1186/s12955-020-01347-7 · Cited by 252
Miloff, A., Lindner, P., Dafgård, P., Deak, S., Garke, M., Hamilton, W., Heinsoo, J., Kristoffersson, G., Rafi, J., Sindemark, K., et al. (2019) · Behaviour Research and Therapy · doi:10.1016/j.brat.2019.04.004 · Cited by 155
Urban safety: A re-reading of the sense of unsafety through individual and ecological dimensions
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Metadata
- Authors
- Muehlhausen, W., Doll, H., Quadri, N., Fordham, B., O’Donohoe, P., Dogar, N., & Wild, D. J.
- Venue
- Health and Quality of Life Outcomes
- Published
- 2015-10-07
- Volume
- 13
- Issue
- 1
- Pages
- 167-167
- ISSN
- 1477-7525 (ISSN-L)
- OpenAlex
- W2170056569
- Cited by
- 248
- References
- 12
- FWCI
- 10.21
- Type
- journal article
- Language
- en
- Open access
- gold
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- Muehlhausen, W., Doll, H., Quadri, N., Fordham, B., O’Donohoe, P., Dogar, N., & Wild, D. J. (2015). Equivalence of electronic and paper administration of patient-reported outcome measures: a systematic review and meta-analysis of studies conducted between 2007 and 2013. Health and Quality of Life Outcomes. https://doi.org/10.1186/s12955-015-0362-x
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