What Complaints Reveal: Qualitative Analysis in Dentistry

According to the PLoS One study published on November 12, 2026, qualitative analysis of patient complaints in dentistry identified four connected concerns: impeded access, unsatisfactory communication and attitudes, deficient clinical treatment, and unethical or unprofessional conduct.

The study interprets dental complaints as possible signals of weakened trust, patient agency, relational security, and professional obligations, while cautioning that the findings are interpretive rather than population-level estimates.

• The researchers identified 857 studies in searches conducted through September 2024 and updated on August 26, 2026, but included 19 studies after screening.
• Deficient clinical treatment appeared in 19 of 19 included studies, or 100%, according to the study’s meta-summary published on November 12, 2026.
• Unethical and unprofessional conduct appeared in 17 of 19 included studies, or 89%, according to the study’s meta-summary published on November 12, 2026.
• The included evidence covered online reviews, regulatory complaints, litigation claims, and mixed-method research across multiple countries, according to the study published on November 12, 2026.
• One patient quoted in the study summarized a communication failure this way: “I have to ask a lot to get to know what I have to do.”

The 2026 PLoS One study used qualitative meta-synthesis to reinterpret findings from earlier qualitative research rather than simply count complaint categories. The authors followed the six-step approach of Sandelowski and Barroso, treated the included studies as a higher-order case, and reported the synthesis using PRISMA guidance.

The researchers searched MEDLINE, PsycINFO, PubMed, Scopus, Web of Science, and CINAHL in September 2024, then updated the search on August 26, 2026. According to the study, 857 records were identified, 29 articles underwent full-text review, and 19 studies met the inclusion criteria.

The authors used reflexive thematic analysis to code qualitative findings, including participant quotations and author-interpreted themes. The analysis combined semantic coding of explicit complaints with latent coding of underlying relational and ethical meanings.

The study’s authors limited the analysis to qualitative findings and excluded descriptive statistics, numerical summaries, and quantitative complaint categories from the coding dataset. The study therefore provides an interpretive account of meaning, not a prevalence estimate for all dental complaints.

The researchers wrote that complaints “may be understood as signals of broader systemic and relational functioning.” This interpretation connects individual experiences with organizational responsiveness, continuity of care, communication, clinical safety, and professional accountability.

Dental quality teams can use qualitative analysis of patient complaints to investigate how operational failures and relationship failures interact. The 2026 PLoS One study links appointment access, unclear communication, clinical deficiencies, and unprofessional conduct to broader concerns about trust and person-centered care.

Complaint analysis should preserve patient meaning instead of reducing every narrative to a single administrative category. The study reports that patients described long waits, appointment cancellations, unclear costs, poor explanations, lack of empathy, inadequate aftercare, and perceived clinical errors as connected experiences rather than isolated events.

Cross-segment comparison can reveal where complaint patterns differ by source. According to the study published on November 12, 2026, deficient clinical treatment appeared across online, regulatory, and litigation subgroups, while access concerns were absent from the litigation subgroup. The authors interpret that absence as potentially reflecting the legal framing of litigation data rather than the absence of access problems.

AI-enabled qualitative research can support this work by organizing complaint documents, highlighting recurring concepts, comparing public and private settings, and retrieving representative quotations for human review. Researchers should treat AI-generated themes as analytic support and maintain human oversight over interpretation, ethics, context, and reporting.

Because the source study concerns healthcare experiences and ethical relationships, AI-assisted analysis should be research-focused and non-diagnostic. Complaint themes can inform quality improvement, but they should not be used alone to determine clinical negligence or individual professional fault.

The 2026 PLoS One meta-synthesis shows why qualitative analysis of patient complaints matters to dentistry: complaints can express interconnected concerns about access, communication, clinical care, and professional integrity.

The study’s 19 included articles and four-domain framework give dental researchers and quality teams a practical structure for analyzing complaint narratives without reducing them to frequency counts alone.

AI-enabled qualitative research can make this work more manageable by helping teams synthesize documents, compare complaint segments, retrieve supporting quotations, and visualize relationships among codes, while researchers retain responsibility for interpretation and ethical use.

Teams that want to analyze dental complaints, patient interviews, or open-ended survey data can Try Evidano for free.