Evidence map›Paper›PMID 38700933›Full record

ArticleJournal of participatory medicine2024

Investigating Patient Satisfaction Through Web-Based Reviews of Norwegian Dentists: Quantitative Study Using the Meaning Extraction Method.

Maria Larsen, Gro Eirin Holde, Jan-Are Kolset Johnsen

Abstract read
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Article in Journal of participatory medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Maria LarsenDepartment of Clinical Dentistry, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway.ORCID https://orcid.org/0009-0008-9359-6611
Gro Eirin HoldeDepartment of Clinical Dentistry, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway.ORCID https://orcid.org/0000-0001-9849-8780
Jan-Are Kolset JohnsenDepartment of Clinical Dentistry, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway.ORCID https://orcid.org/0000-0001-6976-6192

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChallenging encounters in health care professions, including in dentistry, are relatively common. Challenging encounters can be defined as stressful or emotional situations involving patients that could impact both treatment outcomes and patients' experiences. Through written web-based reviews, patients can share their experiences with health care providers, and these posts can be a useful source for investigating patient satisfaction and their experiences of challenging encounters.

objectiveThis study aims to identify dominant themes from patient-written, web-based reviews of dentists and investigate how these themes are related to patient satisfaction with dental treatment.

methodsThe study data consisted of 11,764 reviews written by dental patients, which included 1- to 5-star ratings on overall satisfaction and free-text comments. The free-text comments were analyzed using Linguistic Inquiry and Word Count software, and the meaning extraction method was used to group words into thematic categories. These themes were used as variables in a multilevel logistic regression analysis to predict patient satisfaction.

resultsEight themes emerged from the analyses, of which 6 (75%)-explanation (odds ratio [OR] 2.56, 95% CI 2.16-3.04; P<.001), assurance (OR 3.61, 95% CI 2.57-5.06; P<.001), performance assessment (OR 2.17, 95% CI 1.84-2.55; P<.001), professional advice (OR 1.81, 95% CI 1.55-2.13; P<.001), facilities (OR 1.78, 95% CI 1.08-2.91; P=.02), and recommendation (OR 1.31, 95% CI 1.12-1.53; P<.001)-increased the odds of high patient satisfaction. The remaining themes (2/8, 25%)-consequences of treatment need (OR 0.24, 95% CI 0.20-0.29; P<.001) and patient-centered care (OR 0.62, 95% CI 0.52-0.74; P<.001)-reduced the odds of high patient satisfaction.

conclusionsThe meaning extraction method is an interesting approach to explore patients' written accounts of encounters with dental health professionals. The experiences described by patients provide insight into key elements related to patient satisfaction that can be used in the education of dental health professionals and to improve the provision of dental health services.

Indexed as

challenging encountersinternet useLinguistic Inquiry and Word CountLIWCpatient preferencepatient satisfactionpopulation surveillancepreventive dentistry

Identifiers

PMID38700933
PMCPMC11102035

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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.