Dental researchers and healthcare quality teams need more than complaint counts to understand why patients lose trust. Qualitative analysis of patient complaints reveals the meanings behind dissatisfaction, including concerns about access, communication, clinical treatment, and professional conduct. A November 12, 2026, study in PLOS One synthesized qualitative evidence from 19 studies and identified four connected domains of concern. This article explains the study’s method and findings, then shows how AI-enabled qualitative research can help teams analyze complaint narratives at scale while preserving human interpretation. The goal is not to replace clinical judgment. The goal is to make patient voices easier to organize, compare, and translate into quality-improvement decisions.
Key Takeaways
According to the November 12, 2026, PLOS One study, “Patient complaints in dentistry: A qualitative meta-synthesis”, qualitative analysis of patient complaints found that dental dissatisfaction reflects four connected concerns: impeded access, unsatisfactory communication, deficient clinical treatment, and unethical or unprofessional conduct.
The study shows that patient complaints can reveal threats to trust, autonomy, relational security, and professional accountability, making complaint narratives useful evidence for person-centered dental care and organizational learning.
- The researchers identified 857 studies and included 19 studies after screening, according to the November 12, 2026, PLOS One publication.
- The November 12, 2026, synthesis found deficient clinical treatment in all 19 included studies, representing 100% of the evidence base.
- The November 12, 2026, synthesis found unethical and unprofessional conduct in 17 of 19 studies, representing 89% of the evidence base.
- The researchers searched six health databases in September 2024 and updated the search on August 26, 2026, according to the study methods.
- One patient quoted in the PLOS One study summarized an access problem as: “you never get through… I tried to make an appointment, phone kept ringing out.”
How Qualitative Analysis of Patient Complaints Worked
The November 12, 2026, PLOS One study used a qualitative meta-synthesis to integrate findings from previously published qualitative research rather than simply counting complaint categories.
The researchers followed the six-step approach of Sandelowski and Barroso, used Hoon’s higher-order case framework, and reported the synthesis according to PRISMA guidance for qualitative evidence synthesis. The researchers used reflexive thematic analysis to identify recurring patterns of meaning across studies.
The research team searched MEDLINE, PsycINFO, PubMed, Scopus, Web of Science, and CINAHL. The researchers included peer-reviewed English-language studies about formally documented patient complaints in dentistry, including qualitative components of mixed-method studies.
The researchers imported the full-text findings into Atlas.ti 25, coded qualitative results inductively, and used both semantic coding and latent coding. Semantic coding captured what patients explicitly described, while latent coding interpreted underlying relational and ethical meanings.
The authors stated that the synthesis was intended to move “beyond describing the prevalence or categories of complaints towards an interpretive account of what patients’ complaints signify.” The study also cautioned that the findings are an interpretive account of 19 studies, not population-level estimates of dental complaint frequency.
Dentistry Complaint Findings at a Glance
| Date or measure | Finding | Value | Research implication |
|---|---|---|---|
| November 12, 2026 | Studies identified | 857 | AI-assisted screening can help researchers organize a large initial evidence set. |
| November 12, 2026 | Studies included in the synthesis | 19 | A smaller, appraised corpus supported interpretive cross-study analysis. |
| September 2024 | Initial database search | Six databases searched | A structured search created the evidence base for the synthesis. |
| August 26, 2026 | Search update | One updated search | Evidence synthesis can incorporate newly available research before analysis. |
| November 12, 2026 | Deficient clinical treatment | 19 of 19 studies, 100% | Clinical quality was the most consistently reported concern in the included literature. |
| November 12, 2026 | Unethical and unprofessional conduct | 17 of 19 studies, 89% | Professional integrity and accountability were recurring concerns across the evidence base. |
What the Four Complaint Themes Mean for Dental Researchers
How did patients describe impeded access to dental care?
The November 12, 2026, PLOS One synthesis found that patients described impeded access through appointment difficulties, unanswered telephones, long waits, inaccessible premises, and treatment costs.
The study interprets access complaints as possible signals that patients’ time, needs, and ability to obtain care are not being adequately valued. One patient quoted in the study said, “the dentistry is way too slow, ” describing a 10:00 appointment that began at 12:30 or 1:00.
What did the study find about communication and attitudes?
The November 12, 2026, study found that patients complained about unclear explanations, technical language, poor listening, limited empathy, and rude or dismissive interactions.
One patient quoted in the study said, “the sort of person who got you into the surgery, said ‘Hi’, got the drill out and started almost straightaway.” For qualitative researchers, these accounts show why complaint analysis should examine interactional meaning, not only the event recorded in a complaint database.
Why was deficient clinical treatment the strongest theme?
The November 12, 2026, PLOS One synthesis found deficient clinical treatment in all 19 included studies, including concerns about treatment quality, pain, treatment planning, aftercare, infection control, and safety.
The authors reported that complaints often combined technical outcomes with experiences of communication, respect, and responsiveness. This finding supports coding clinical complaints alongside emotional, relational, and organizational dimensions.
What did patients mean by unethical or unprofessional conduct?
The November 12, 2026, study grouped concerns about informed consent, risk disclosure, dishonesty, unequal treatment, poor accountability, fraud, negligence, and medication or treatment errors under unethical and unprofessional conduct.
The study found this theme in 17 of 19 studies, or 89% of the included evidence base. The authors interpreted these complaints as possible signs that professional integrity and trustworthiness had been compromised.
How Evidano Helps With AI-Enabled Dental Complaint Research
Problem: Complaint narratives are difficult to synthesize
Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze patient interviews, complaint narratives, open-ended surveys, and research documents.
Researchers can upload complaint documents and use thematic analysis to identify recurring concerns such as access, communication, clinical treatment, safety, and professional conduct. Researchers can review the generated themes against source passages rather than relying on complaint counts alone.
Evidano’s qualitative research features support thematic, content, frequency, and cross-segment analyses for document-based research.
Problem: Themes may differ across complaint sources
Solution: Cross-segment analysis can compare themes across online reviews, regulatory complaints, litigation narratives, clinic locations, patient groups, or time periods.
The November 12, 2026, PLOS One study showed why comparison matters: deficient clinical treatment appeared across complaint-source subgroups, while access and professional-conduct themes varied by source. A cross-segment workflow can help researchers distinguish recurring concerns from source-specific patterns.
Problem: Researchers need to verify AI-generated interpretations
Solution: Evidano’s AI chat over documents and analyses lets research teams ask targeted questions and trace interpretations back to the uploaded evidence.
Researchers can use document-grounded questions such as “Which excerpts describe unclear cost communication? ” or “How does access differ between public and private care complaints? ” Human researchers should make the final methodological and ethical judgments.
Problem: Complaint data may contain sensitive patient information
Solution: Evidano supports PII redaction during transcription workflows, and its security model encrypts data and does not use customer data to train third-party models.
Dental researchers should still apply institutional ethics requirements, data-minimization practices, and appropriate anonymization before analyzing patient narratives.
FAQ: Qualitative Analysis of Patient Complaints
What is qualitative analysis of patient complaints?
+
Qualitative analysis of patient complaints is the systematic interpretation of narrative data to identify meanings, experiences, patterns, and underlying concerns.
The November 12, 2026, PLOS One study used reflexive thematic analysis to interpret complaints across 19 dentistry studies, rather than treating complaints only as numerical categories.
What were the four main themes in the dentistry complaint study?
+
The four themes were impeded access to dental care, unsatisfactory communication and attitudes, deficient clinical treatment, and unethical or unprofessional conduct.
The November 12, 2026, study interpreted the four themes as connected threats to trust, patient agency, relational security, and professional obligations.
How many studies were included in the qualitative dentistry review?
+
The review included 19 studies from an initial set of 857 studies.
According to the November 12, 2026, PLOS One publication, the researchers searched six health databases and updated the search on August 26, 2026.
Can AI analyze dental patient complaints?
+
AI can help organize, code, compare, and summarize dental patient complaints, but qualified researchers should validate interpretations and retain responsibility for conclusions.
An AI-enabled workflow can accelerate thematic and cross-segment analysis while preserving source excerpts for human review.
What is the main limitation of the dentistry meta-synthesis?
+
The main limitation is that the synthesis provides an interpretive account of 19 heterogeneous studies, not population-level estimates of complaint prevalence.
The November 12, 2026, study also limited inclusion to English-language publications and noted variation in methodology, reporting quality, healthcare systems, and complaint sources.
Conclusion and Next Steps for Dental Experience Research
The November 12, 2026, PLOS One study shows that dental complaints can reveal more than dissatisfaction with an isolated procedure. Qualitative analysis of patient complaints connects access, communication, clinical quality, safety, and professional integrity to the wider patient-practitioner relationship.
For dental researchers and healthcare quality teams, AI-enabled qualitative research can make large complaint collections easier to code, compare, and interpret while keeping patient narratives visible. Evidano supports this workflow with thematic analysis, cross-segment analysis, document-grounded AI chat, and privacy-conscious data handling.
Use Evidano for qualitative research to turn complaint narratives and other patient feedback into structured evidence for quality improvement. Try Evidano for free and explore your data through an AI-enabled research workflow.
Topics
- qualitative analysis of patient complaints
- qualitative analysis in dentistry
- AI thematic analysis healthcare
- dental patient experience research
Keep reading
- Commentary on NewsWhat Complaints Reveal: Qualitative Analysis in DentistryLearn what qualitative analysis of patient complaints reveals about trust, access, communication, and dental care, then turn themes into action with Evidano.
- Commentary on NewsQualitative Analysis of Patient ComplaintsLearn what qualitative analysis of patient complaints reveals about dental care, trust, and service quality, and see how AI speeds thematic research. Try Evidano today.
- Commentary on NewsFour Signals: Qualitative Analysis of Patient ComplaintsTurn patient complaints into quality insight with qualitative analysis of patient complaints, four themes, and AI workflows. Explore the 2026 dental study.