Patient Engagement Via Crowdsourcing

Chronic Low Back Pain Clinical Trial

— PECS  

Official title:

Feasibility of Crowdsourcing for Eliciting Patient Experiences of Chronic Pain

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT03264521
• Other study ID #: 1R21AT009124-01
• Status: Completed
• Start date: January 23, 2017
• Est. completion date: May 30, 2018

Study information

• Verified date: February 2021
• Source: RAND
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The study aims to advance pain research by exploring feasibility of crowdsourcing patient pain data via Amazon Mechanical Turk, the largest and most studied crowdsourcing platform in the U.S. We will leverage an existing NIH/NCCIH grant as a comparison data (RAND Center of Excellence in Research on CAM; CERC) to conduct a feasibility study of new methods for gathering and analyzing data on chronic pain and engaging pain patients in health policy.

Description:

The study aims to advance the pain research by exploring the crowdsourcing approach for eliciting and analyzing the way in which individuals experience and understand chronic pain. Investigators will leverage an existing NIH/NCCIH grant (RAND Center of Excellence in Research on CAM; CERC) to conduct a feasibility study of new methods for gathering and analyzing data on chronic pain and engaging pain patients in health policy processes through three specific aims:

Aim 1 (Inclusion): Gain access to chronic pain patients using crowdsourcing platform Amazon Mechanical Turk (MTurk). This aim explores whether crowdsourcing provides a credible method for patient inclusion. People with low back pain will be accessed via the crowdsourcing platform MTurk and asked to take health surveys that were also administered to a national clinical sample of chiropractic patients within a RAND study. Equivalency of validated, self-reported measures of low back pain obtained from crowdsourced versus "gold standard" data from the RAND study will be assessed. Similarities and differences between demographics and other pain and function variables between crowdsourced and RAND data will be analyzed. Subsamples of crowdsourced data will be analyzed to assess reliability of the extent to which data yields the same results across repeated crowdsourced samples.

Aim 2 (Participation): Engage chronic pain patients in inclusion criteria setting for national pain treatment programs. This aim will intends to facilitate patient participation in NIH criteria-setting for program inclusion. Crowdsourced patients will assist with qualitative coding of data responses to the question, "What does chronic pain mean to you?" Investigators will explore whether crowdsourcing provides a valid method by which coding may be conducted, first measuring reliability across crowd samples, second testing the accuracy of participant coding as compared with expert coders at RAND Corporation. A method of assessing face validity will be tested as participants may create additional codes and give feedback by rating the importance of each dimension.

Aim 3: Assess efficiency and quality of crowdsourced data as compared to CERC data. Investigators will draw quantitative comparisons of cost (labor/incentives), time, data quality (amount of text, missing data) across online crowdsourced and CERC study samples.

The proposed study utilizes the resources of an existing NIH grant by exploring the feasibility of using innovative online methods for eliciting patient perspectives on chronic pain and for engaging patients in analyses procedures. The study provides an opportunity to determine whether patient chronic pain experiences and perspectives can be gathered through crowdsourcing using Amazon Mechanical Turk (MTurk), in a valid, replicable, and resource efficient way. Although focused on chronic low back pain, the study findings will have broad implications for patient engagement more generally. If the crowdsourcing methods produce data that is comparable to "gold standard" methods used in the RAND Study entitled, "Center of Excellence in Research on Chiropractic" (RAND/CERC Study), this new experimental system has the potential to provide low-cost and time-efficient methods to advance democratically-oriented research, evaluation, policy and ultimately patient-centered clinical care.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 8193
• Est. completion date: May 30, 2018
• Est. primary completion date: December 22, 2017
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 21 Years and older

Eligibility

Inclusion Criteria:

• At least 3 months of low back pain or self-reported chronic low back pain

• Utilized chiropractic care for treating back pain

Exclusion Criteria:

• Under 21 years of age

• No open legal or workers compensation case related to condition

• No diagnosis from provider of medical condition, so must be non-specific low back pain.

Related Conditions & MeSH terms

• Chronic Low Back Pain
• Low Back Pain

Intervention

Other:
• Surveys
Web surveys about experiences with chronic low back pain, demographics, coding qualitative text.

Locations

Country	Name	City	State
United States	RAND Corporation	Santa Monica	California

Sponsors (2)

Lead Sponsor	Collaborator
RAND	Claremont Graduate University

Country where clinical trial is conducted

United States, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	ODI Score	Oswestry Disability Index: Validated low back pain function scale (0-100)	day 1
Primary	PROMIS-29	Patient-Reported Outcomes Measurement Information System, 29 items, Version 2: Validated, self-reported measure of global, physical, mental, and social health for adults in the general population and those living with a chronic condition.	day 1
Primary	Average Pain NRS (0-10)	Numeric Rating Scale for pain intensity: Average pain in past seven days (0-10)	day 1
Primary	Worst Pain NRS (0-10)	Numeric Rating Scale for pain intensity: worse pain in past seven days (0-10)	day 1
Secondary	Demographics	Gender, Age, Race/Ethnicity, Education, Income, Employment Status,	day 1