Understanding the Lived Experience of North American Dental Patients With a Single-Tooth Implant in the Upper Front Region of the Mouth: Protocol for a Qualitative Study (Preprint)
Bibliographic record
Abstract
BACKGROUND Assessment of the subjective experiences of individuals with maxillary anterior (ie, the upper front region of the mouth) single-tooth implants is limited mainly to quantitative measurements of satisfaction with appearance. Interestingly, there is unexplained variability in the relationship between satisfaction and appearance. OBJECTIVE This qualitative study protocol aims to explore and better understand the satisfaction with appearance and function in a Canadian population with maxillary anterior single-tooth implants treated at a postgraduate university clinic. Thus, we aim to obtain diversity among participants relating to the identification of esthetically pleasing and displeasing cases from a clinician perspective. METHODS A qualitative research design using interpretative phenomenology analysis (IPA) will provide an adaptable inductive research approach. The participants will be recruited, and consent documents, photographs, digital intraoral scans, and self-administered questionnaire responses will be obtained from them. The transcribed verbatim data from audio-recorded, in-depth, semistructured, one-to-one interviews of the participants will be managed, coded, and analyzed thematically with computer-assisted qualitative data analysis software. The IPA will consider the COnsolidated criteria for REporting Qualitative (COREQ) guidelines when applicable. RESULTS For the qualitative interview, we plan to include at least eight patients to conduct up to 1.5 hours of open-ended interviews with each participant aided by an interview guide. Ethical approval was granted by the University of British Columbia Behavioral Research Ethics Board (H19-00107) in May 2019. Two American dental foundations funded this study. CONCLUSIONS The analysis in this study will elucidate the aspects (including their value) that influence participant satisfaction at different dental implant treatment stages. This will be the first qualitative study on this group of the population to explore and obtain a better understanding of their satisfaction with appearance and function, as well as any other patient-reported outcome measures that could be identified. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/25767
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.039 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.033 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".