Evidence map›Paper›PMID 41858795›Full record

ArticleJournal of pain research2026

Pricing, Popularity, and Customer Satisfaction in Online Pain-Relief Products: An AI-Powered Analysis.

Oranicha Jumreornvong, Piyawat Kantagowit, Runchana Parnicharoende, R Jason Yong, Giuliano Lo Bianco, Qing Zhao Ruan, Jamal Hasoon, Matthew Chung, Michael E Schatman, Generoso Rullo and 3 more

Abstract read
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In one paragraph

Article in Journal of pain research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Oranicha Jumreornvong *Department of Human Performance and Rehabilitation, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Piyawat Kantagowit *Department of Surgery, NYU Grossman School of Medicine, New York, NY, USA.ORCID 0000-0002-7890-8356
Runchana Parnicharoende *Department of Rehabilitation Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
R Jason YongDepartment of Anesthesiology, Perioperative, and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Giuliano Lo BiancoAnesthesiology and Pain Department, Foundation G. Giglio, Cefalù, Palermo, Italy.ORCID 0000-0003-2705-1548
Qing Zhao RuanWarren Alpert Medical School, Brown University, Providence, RI, USA.
Jamal HasoonDepartment of Anesthesia, Critical Care, and Pain Medicine, UTHealth McGovern Medical School, Houston, TX, USA.
Matthew ChungDepartment of Pain Medicine, Division of Anesthesia, Critical Care and Pain Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.ORCID 0000-0002-0931-8643
Michael E SchatmanDepartment of Anesthesiology, Perioperative Care, and Pain Medicine, NYU Grossman School of Medicine, New York, NY, USA.ORCID 0000-0002-1019-0413
Generoso RulloDepartment of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN, USA.ORCID 0009-0003-3281-3815
Paul J ChristoDivision of Pain Medicine, Department of Anesthesiology and Critical Care Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Mohammed IssaDepartment of Anesthesiology, Perioperative, and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Christopher L RobinsonDivision of Pain Medicine, Department of Anesthesiology and Critical Care Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.ORCID 0000-0002-6276-9056

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To examine how product popularity and pricing are associated with customer satisfaction across pain-relief device types on online e-commerce platforms. Methods: A cross-sectional study was conducted to analyze pain-relief products from Amazon and Best Buy. Data were collected via automated web scraping, verified, and categorized into 10 device types. Key variables including product names, prices, customer ratings, and review volumes were assessed in multivariable regression models. Results: A total of 378 distinct pain-relief products were analyzed. The median customer ratings for pain-relief devices varied significantly by type, ranging from 3.2 to 4.5 (p < 0.001). TENS units and cold/heat therapy packs achieved the highest median ratings of 4.5 (4.3-4.6). In contrast, hand/arm massagers received the lowest median rating of 3.2 (2.2-4.2). Pricing differences across device types were significant (p < 0.001), with neck stretchers being the least expensive (median: $29.99) and hand/arm massagers being the most expensive (median: $249.50). Discussion: Although price and the number of reviews were not significant predictors of customer ratings in multivariable regression models, significant interactions were observed between price and device type for hand/arm massagers (p < 0.001) and massage guns (p = 0.006). Additionally, significant interactions between the number of reviews and device type were observed for hand/arm massagers (p = 0.004). Conclusion: Although pricing and review quantity were not significant predictors of satisfaction for most devices, they did interact with specific categories such as hand/arm massagers and massage guns. These findings indicate that customer satisfaction is driven more by device-specific characteristics than by price or review volume.

Indexed as

artificial intelligencecustomer satisfactionpain-relief

Identifiers

PMID41858795
PMCPMC12998646

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.