ArticleInterventional pain medicine2025
Evidence of non-response bias in patient reported outcome measurement information system surveys.
Article in Interventional pain medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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.
Who cites it
6 citing papers in PubMed.
- Beyond one-time PROMs: high-frequency single-item mobile ePROM tracking of postoperative recovery in spine surgery-a prospective feasibility study.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Article
- Understanding determinants of patient-reported outcome measure non-response among transgender and gender diverse individuals: an intersectional multilevel analysis of sociodemographic and structural vulnerabilities.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2026Observational
- Harnessing patient health data to benefit individuals and advance research: a focus on rheumatoid arthritis - a narrative review.BMJ digital health & AI · 2026Review
- Adherence to Electronic Patient-Reported Outcome Measures: A Null-Results Review of Measure-Related Effects on Response Rates in Routine Care.Patient preference and adherence · 2026Review
- Self-reported temporomandibular disorder pain in a multi-ethnic, Southeast Asian population: prevalence and health impact.BMC oral health · 2025Article
- Brief report: Relationships of frailty and age with nonresponse to patient reported outcome measures.Advances in patient-reported outcomes · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Patient-reported outcome measurement instrument surveys (PROMIS) have been increasingly used to assess clinical outcomes following a variety of medical procedures. Despite their value in evaluating patient functional status, response rates to these surveys remain low. Understanding differences in demographics between responders and non-responders to PROMIS may be beneficial to improving generalizability and response rates. Objective: The primary aim of this study was to compare demographic characteristics between patients who respond to PROMIS surveys and those who do not, hypothesizing no significant differences between these groups. Methods: Adult new patient visits from 2018 to 2022 in Department of Physical Medicine & Rehabilitation outpatient clinics at a single academic medical center were analyzed. Patients completed PROMIS surveys (physical function, pain interference, and depression) on iPads at each clinic visit. Demographic variables such as gender, race, BMI, smoking status, employment status, marital status, and Area Deprivation Index (ADI) were collected. Univariate and multivariate analyses were conducted to assess for variables associated with an increased likelihood of responding to PROMIS surveys. Results: A total of 29,830 patients were included in this study. Of the total patient cohort, 8331 (27.9 %) responded to the PROMIS surveys. Significant demographic differences were found between responders and non-responders. Patients in the least deprived ADI quartile were more likely to respond compared to those in the most deprived quartile (33.5 % vs 23.7 %, p < 0.001). Employed patients, white patients, non-smokers and married individuals were more likely to respond. On multivariate analysis, unemployment (OR 0.71, p = 0.006), increased BMI (OR 0.93, p = 0.014), and higher ADI (OR 0.94, p = 0.003) were significantly associated with lower response rates. Conclusions: PROMIS response rates are influenced by patient demographics, with lower response rates observed in unemployed, non-white, and socioeconomically deprived populations. These findings highlight the need for targeted interventions to increase response rates and ensure equitable data collection in PROMIS surveys to enhancing the generalizability of clinical decisions made using PROMIS data.
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