Utility of 3D modelling of the patient's living environment as perceived by occupational therapists
Bibliographic record
Abstract
INTRODUCTION: Visiting a patient's living environment is important for occupational therapists, albeit costly and time consuming. MapIt is a mobile app producing a 3D representation of a home with the possibility of taking measurements. The purpose of this study was to explore the utility of a 3D representation of a patient's home for the clinical practice of occupational therapists. METHODS: Case study in which the unit of analysis was the utility of MapIt as defined by ISO 9241-11:2018 and as perceived by occupational therapists in four different occupational therapy clinical settings (Canada). Onsite observations with 10 occupational therapists (and their patients) were triangulated with data from interviews, diaries, and logbooks. Inductive thematic condensation led to emerging conclusions for each clinical setting, fuelling the next case data collection and analysis. Inter-case analysis was corroborated by additional occupational therapists, through crowdsourcing and expert review. RESULTS: Occupational therapists' clinical reasoning was supported by the MapIt app, enhancing and streamlining their work and inducing adjustments to treatment plans. Occupational therapists saw and measured the patient's environment remotely, to better match person-environment-occupation and promote occupational engagement. MapIt's 3D representations were judged useful to communicate between occupational therapists and stakeholders, to educate, allow continuity, optimise resources, minimise the patient's time on a waitlist for homecare, and save time for everyone. DISCUSSION: MapIt allowed occupational therapists who performed home visits to bring a little of the patients' home to their office, whereas occupational therapists without access to the home could see it and take measurements. MapIt's utility was confirmed for practice in clinical settings and for better continuity of care between settings. CONCLUSION: MapIt makes it possible for occupational therapists to 'walk around' the patient's home remotely, but the possibility of measuring environmental elements is a 3D model's true added value over currently used photos or short videos.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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 teacher head, 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".