Patients experience and satisfaction with immediate loading of implant-supported overdentures - A qualitative study
Bibliographic record
Abstract
OBJECTIVES: To explore the perspectives and experiences of edentate individuals in regard to the immediate-loading protocol of an implant-supported overdenture. METHODS: A qualitative approach and interpretive description methodology was used. Seventeen edentate individuals (mean age: 61.9 ± 6.6 years) who received implant-supported overdentures through an immediate-loading protocol participated. Audio-recorded, semi-structured, in-depth interviews, each with a 60-90-minute duration, were conducted by two trained interviewers. The interview guide was developed based on Perneger's Detailed Model. Qualitative data were analyzed using a thematic approach including interview debriefing, transcript coding, data display, inductive thematic analysis, and interpretation. RESULTS: Three main themes emerged from the interviews: patient awareness and engagement with treatment, experience-shaped expectations, and immediate gratification. All patients expressed satisfaction with the treatment. Providing detailed information, good communication, and accessibility of the dental care provider had a significant impact on patient satisfaction with prosthetic care. Patients highlighted that the high cost of implant therapy was the major barrier to receiving this treatment in the private sector and perceived dental insurance coverage as a facilitator of this process. CONCLUSIONS: Study findings conclude that patient awareness about immediate-loading protocol improved their treatment engagement, and patient satisfaction with the treatment outcomes was higher than anticipated. The satisfaction was primarily related to prosthesis stability, receiving the prosthesis the same day, and low cost of treatment. Patients' positive experience and satisfaction with the immediate-loading protocol indicate that this treatment modality should be considered in treatment planning for edentate individuals. CLINICAL SIGNIFICANCE: The perceptions and experiences of edentulous patients gathered in this study highlight their satisfaction with immediate loading for implant-supported overdentures. This therapeutic modality can be considered a viable option in treatment planning for edentulous individuals.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".