What Complaints Reveal: Qualitative Analysis in Dentistry

According to the PLOS One study, "Patient complaints in dentistry: A qualitative meta-synthesis", qualitative analysis of patient complaints identified four connected concerns: impeded access, unsatisfactory communication and attitudes, deficient clinical treatment, and unethical or unprofessional conduct.

The study shows that dental complaints can reveal breakdowns in trust, patient agency, relational security, and professional obligations, not only dissatisfaction with a technical treatment outcome.

• The study searched 857 records and included 19 qualitative studies, with the review published on November 12, 2026.
• The study found deficient clinical treatment in all 19 included studies, representing 100% of the qualitative evidence base.
• The study found unethical and unprofessional conduct in 17 of 19 studies, representing 89% of the included studies.
• The study reported that 11 of the 19 included studies were published from 2015 onward and that the evidence came from multiple countries and complaint sources.
• The authors concluded that complaints are important signals of the relational and systemic conditions needed for trustworthy, person-centered dental care.

The 2026 PLOS One study used a qualitative meta-synthesis to interpret meanings across previously published qualitative findings rather than calculate population-level complaint rates.

Snyman, Postma, and Van Staden searched MEDLINE, PsycINFO, PubMed, Scopus, Web of Science, and CINAHL in September 2024, then updated the search on August 26, 2026. The researchers screened 857 records, reviewed 29 full texts, and included 19 studies.

The authors followed the six-step approach of Sandelowski and Barroso, used reflexive thematic analysis, and treated the included studies as a higher-order case. One reviewer coded qualitative findings in Atlas.ti 25, while a second reviewer independently reviewed and questioned the coding outputs.

The authors restricted the synthesis dataset to qualitative findings, including interpreted themes and participant quotations, while excluding descriptive statistics and quantitative complaint categories. The method therefore focused on what complaints meant to patients, rather than simply how often complaint categories appeared.

The authors stated that the synthesis was intended to move beyond describing complaint prevalence and categories toward an interpretive account of shared meaning across different dental settings.

Dental quality teams should treat complaint narratives as qualitative evidence about access, communication, clinical safety, and professional integrity, according to the 2026 PLOS One meta-synthesis.

The study found that all four themes appeared together in 11 of the 19 included studies. That overlap matters because a complaint about a clinical outcome may also involve unclear consent, poor aftercare, dismissive communication, or difficulty obtaining follow-up care.

The authors wrote that complaints may be understood as "signals of broader systemic and relational functioning." This interpretation encourages healthcare organizations to examine the conditions that produced a complaint, not only the isolated event described in a complaint form.

The study also found that complaint themes varied by source. Deficient clinical treatment appeared across online complaints, regulatory complaints, and litigation-related claims, while impeded access was absent from the litigation subgroup. The authors cautioned that the absence may reflect the legal framing of litigation data rather than the absence of access concerns.

For researchers, the practical priority is to preserve patient language while building a consistent coding framework. Teams can compare themes by clinic, complaint source, patient segment, treatment pathway, or time period, but researchers should distinguish AI-supported pattern discovery from final ethical and clinical interpretation.

The 2026 PLOS One meta-synthesis shows that qualitative analysis of patient complaints can reveal more than isolated dissatisfaction: it can expose recurring weaknesses in access, communication, clinical care, and professional conduct.

For dental researchers and healthcare quality teams, AI-enabled qualitative research can reduce the manual burden of organizing complaint narratives while preserving a path back to patient language and source evidence.

Evidano helps teams analyze documents and survey responses, compare segments, visualize themes, and ask questions across a controlled qualitative evidence base. Try Evidano for free to begin analyzing patient feedback and complaint data.