Evidence map›Paper›PMID 35573577›Full record

ArticleCureus2022

What Are Patients Saying About Minimally Invasive Spine Surgeons Online: A Sentiment Analysis of 2,235 Physician Review Website Reviews.

Justin Tang, Christopher A White, Varun Arvind, Samuel Cho, Jun S Kim, Jeremy Steinberger

Abstract read
In one paragraph

Article in Cureus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

6 authors.

Justin TangOrthopedic Surgery, Icahn School of Medicine at Mount Sinai, New York, USA.
Christopher A WhiteOrthopedic Surgery, Icahn School of Medicine at Mount Sinai, New York, USA.
Varun ArvindOrthopedic Surgery, Icahn School of Medicine at Mount Sinai, New York, USA.
Samuel ChoOrthopedic Surgery, Icahn School of Medicine at Mount Sinai, New York, USA.
Jun S KimOrthopedic Surgery, Icahn School of Medicine at Mount Sinai, New York, USA.
Jeremy SteinbergerNeurological Surgery, Mount Sinai Health System, New York, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective Physician review websites are becoming increasingly popular for patients to find and review healthcare providers. The goal of this study was to utilize quantitative analyses to understand trends in ratings and written comments on physician review websites for Society of Minimally Invasive Spine Surgery (SMISS) members. Methods This is a cross-sectional study. The reviews of SMISS surgeons were obtained from healthgrades.com, and sentiment analysis was used to obtain compound scores of each physicians' reviews. SMISS surgeons who were international or had fewer than three written reviews, often consisting of residents and fellows, were excluded. Inferential statistics were utilized, and word frequency analysis reported the phrases used to characterize reviews. Results One hundred sixty-nine surgeons met the inclusion criteria. 98.6% were males and the mean age was 51.7 years old. A total of 2,235 written reviews were analyzed. Younger surgeons were significantly more likely to receive higher star ratings (p<0.01). Positive behavioral characteristics, such as "kind" and "bedside manner," conferred significantly improved odds of receiving positive reviews (p<0.01). Ancillary "staff" conferred a 2x greater odds of receiving a positive review whereas a comment on "wait" times halved a surgeon's odds (p<0.01). Sentences describing pain drove down the odds of positive reviews whereas those describing pain relief produced greater odds of positive reviews (p<0.01). Conclusion Physicians who were younger, personable, provided sufficient pain relief, and who worked in favorable offices received the most positive reviews. This study informs SMISS members on the traits deemed important by patients who ultimately review surgeons online.

Indexed as

minimally invasivenatural language processingonline reviewspatient satisfactionsentiment analysis

Identifiers

PMID35573577
PMCPMC9106264

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Registered trials

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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.