ArticleJournal of orthopaedics2024
Role of patient specific 3D printed models in patient confidence, understanding and satisfaction of care in Singapore.
Article in Journal of orthopaedics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- Imaging-based 3D-printed anatomical models for preoperative planning in hepatopancreatobiliary surgery: a single-center pilot study, cost analysis, and systematic review.La Radiologia medica · 2026Pooled it
- Using 3D-printing technology for patient education: a review of the literature.3D printing in medicine · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Patient specific 3D models have been widely used for pre-op planning and intra-op guidance in orthopaedic surgery. These models however are not often used in pre-operative doctor-patient communication. This study evaluates the roles of customized 3D models in improving patient understanding, confidence, and satisfaction of patient care when they were used during preoperative counselling. Materials and methods: A prospective survey was conducted on 33 orthopaedic trauma patients who were required to rate on a scale of 1-5, the effectiveness of patient specific 3D models in: 1) improving patient's understanding and, 2) helping patients cope with the condition, 3) boosting patients' confidence in the treatment and 4) in the surgeon; and on a scale of 0-10, their overall satisfaction. Subgroup analysis was done to compare ratings of patients by age and by education levels. Results: Over 90% patients rated agree or strongly agree on customised 3D models' effectiveness in improving understanding of injury and boosting confidence in treatments and surgeons. 87% patients agreed or strongly agreed that the models enhanced patient self-efficacy. No significant correlation was identified between age and patients' perceived effectiveness of customised 3D models in improving patient care. Ratings on four areas evaluated by pre-secondary and post-secondary groups were comparable. Post-secondary group had significantly higher satisfaction level than the pre-secondary group. Conclusion: Customized 3D models help patients visualise complex pathology to facilitate patients' understanding of their condition and treatment, resulting in improved self-efficacy, confidence, and overall satisfaction. The use of patient specific 3D models in pre-operative counselling allows greater patient involvement therefore prompting patient-centred healthcare. Age does not influence patients' perceived effectiveness of customised 3D models in improving patient care. Patients with higher education level are likely to experience higher satisfaction level due to their willingness to take responsibility for their care.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.