Measuring Chronic Pain Impact

Principal Investigator(s):  View help for Principal Investigator(s) Patricia Herman, RAND Corporation. RAND Health; Ron Hays, UCLA

Version:  View help for Version V1

Name File Type Size Last Modified
Knowledge Panel Back Pain 6 Month Follow up TC saved.pdf application/pdf 603.1 KB 02/27/2024 03:14:PM
Knowledge Panel Back Pain Baseline Wave 2022 Project Report.pdf application/pdf 817 KB 08/18/2022 09:51:AM
MTurk_KP_LongFormat_CodeBook_Cleaned_2024-02-17.xlsx application/vnd.openxmlformats-officedocument.spreadsheetml.sheet 30.1 KB 02/27/2024 03:08:PM
MTurk_KP_LongFormat_CodeBook_Rmarkdown.html text/html 32.1 MB 02/27/2024 03:11:PM
Survey of General Health 3 month Follow Up.pdf application/pdf 920.8 KB 02/17/2024 08:07:PM
Survey of General Health 6 month Follow Up.pdf application/pdf 980.5 KB 08/18/2022 09:51:AM
Survey of General Health Baseline.pdf application/pdf 1.1 MB 07/07/2023 01:55:PM
chronic_pain_baseline_only.csv text/csv 1.3 MB 02/17/2024 07:43:PM
chronic_pain_longitudinal.csv text/csv 13.2 MB 02/17/2024 08:06:PM
pain.study.long2.RData application/x-rlang-transport 3.2 MB 02/27/2024 03:16:PM

Project Citation: 

Herman, Patricia, and Hays, Ron. Measuring Chronic Pain Impact. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2024-02-27. https://doi.org/10.3886/E198049V1

Project Description

Summary:  View help for Summary Millions of research dollars have been spent on studies of the effectiveness of interventions for chronic pain, and there is now a growing list of nonpharmacologic therapies being recommended, especially for patients with chronic low back pain. However, to extract the full value of this research investment, including the answer to the question ‘which therapy is most effective?’, we must be able to directly compare results across studies; a task which is hampered by two things: the use of different outcome measures and the lack of a stratification scheme which would allow the case mix of baseline samples to be balanced. This project addresses these challenges by developing crosswalks and/or links between the PROMIS-29 and the legacy measures commonly used in these studies, and by further developing and creating cut-points for a proposed chronic pain impact stratification scheme.          
Funding Sources:  View help for Funding Sources National Center for Complementary & Integrative Health of the National Institutes of Health (R01AT010402)

Scope of Project

Subject Terms:  View help for Subject Terms Chronic Pain; Low Back Pain; Pain Measurement; Outcome Assessment; Health Care; Surveys and Questionnaires
Geographic Coverage:  View help for Geographic Coverage United States
Time Period(s):  View help for Time Period(s) 8/31/2021 – 11/2/2021 (MTurk Sample); 9/22/2022 – 10/1/2022 (Knowledge Panel Sample)
Universe:  View help for Universe Persons 18 years of age or older living in the United States.
Data Type(s):  View help for Data Type(s) survey data

Methodology

Response Rate:  View help for Response Rate 50% for the MTurk sample
57% for the Knowledge panel sample
Sampling:  View help for Sampling Amazon’s Mechanical Turk (MTurk) sample is a convenience sample from adults age 18 or older.

Knowledge Panel sample is a probability-based sample with the target to represent non-institutionalized adults age 18 and older who reside in the United States.
Collection Mode(s):  View help for Collection Mode(s) mixed mode; web-based survey
Scales:  View help for Scales
  • Oswestry Disability Index (ODI)
  • Roland-Morris Disability Questionnaire (RMDQ)  
  • Örebro Musculoskeletal Pain Questionnaire (OMPQ)
  • Subgroups for Targeted Treatment (STarT) Back screening tool 
  • Graded Chronic Pain Scale (GCPS)
  • Pain intensity, interference with Enjoyment of life, and interference with General activity (PEG) scale
  • Impact Stratification Score (ISS) 
  • Patient-Reported Outcomes Measurement Information System (PROMIS®)-29 +2 (two items to assess cognitive function) 
  • PROMIS-based preference score (PROPr) 
  • PROMIS Global Physical Health
  • PROMIS Global Mental Health 
Weights:  View help for Weights
The data includes weights (variable 'screener_weight') to account for any differential nonresponse. An iterative proportional fitting (raking) procedure was used to weight the sample to match the 2022 March Supplement of the Current Population Survey (CPS). In the final step, calculated weights are examined to identify and, if necessary, trim outliers at the extreme upper and lower tails of the weight distribution. The resulting weights are then scaled to aggregate to the total sample size of all eligible respondents.
Unit(s) of Observation:  View help for Unit(s) of Observation Individuals

Related Publications

Download this project

Published Versions

V1 [2024-02-27]

Export Metadata

Dublin Core

DDI 2.5

Report a Problem

Found a serious problem with the data, such as disclosure risk or copyrighted content? Let us know.

This material is distributed exactly as it arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigator(s) if further information is desired.