Feasibility of a tablet computer based food record for self-assessment of nutritional intake in geriatric rehabilitation patients: a pilot study (Preprint)
Bibliographic record
Abstract
<sec> <title>BACKGROUND</title> Nutritional status is an influencing factor for functional status and rehabilitation outcome in geriatric rehabilitation patients. Although there is evidence for the potential of eHealth interventions in geriatric rehabilitation patients in general, the evidence for eHealth interventions with focus on nutrition is scarce. In other target groups with older people, eHealth applications to support nutrition, such as computer-based food records, have been used successfully. </sec> <sec> <title>OBJECTIVE</title> Therefore, the aim of this study was to verify if it is feasible for geriatric rehabilitation patients to independently use a tablet computer based food record (e-food record) in order to document their food and beverage intake. The e-food record was developed in advance and tailored to the age- and disease-specific needs of geriatric rehabilitation patients. </sec> <sec> <title>METHODS</title> This prospective pilot study investigated the general feasibility of an e-food record in older adults (≥ 70 years) in a geriatric rehabilitation center in Germany. It was tested whether the e-food record could be independently used by the participants over three days. Furthermore, the usability of the e-food record was assessed by the System Usability Scale (SUS, 0-100 points) after usage. To compare nutritional data, the participants recorded their consumption of food and beverages by the e-food record and by a 24h recall for the same time period and mean difference was calculated as follows: value of 24h recall minus value of e-food record. As the study was characterized as pilot the data analysis was descriptive. </sec> <sec> <title>RESULTS</title> 17 out of 25 patients (35.3 % female, mean age 79.5 ± 3.7 years) kept the e-food record independently over the study period. Mean SUS score of the e-food record was 76.0 ± 11.3 points. Data sets of nine participants (mean age 78.2 ± 2.9 years, 55.6 % female) were analyzed in terms of nutritional data. Mean difference in energy, protein and fluid intake by the 24h recall compared to the e-food record were 4.9 ± 10.2 kcal per kg body weight (bw), 0.1 ± 0.3 g per kg bw and 4.9 ± 9.4 g per kg bw respectively. </sec> <sec> <title>CONCLUSIONS</title> The use of an e-food record is generally feasible for geriatric rehabilitation patients characterized by low technical experience, high mean age and high rate of functional impairment. Underreporting was observed for the e-food record compared to the 24h recall with regard to energy, protein and fluid intake. Aspects for further development of the e-food record were identified to enable evaluation on a larger sample. Following successful evaluation, the e-food record could be used within nutrition therapy in the future to increase the efficiency of the nutritional therapy process. </sec> <sec> <title>CLINICALTRIAL</title> German Clinical Trials Register; Number: DRKS 00014370; http://www.bfarm.de/DE/Das-BfArM/Aufgaben/Deutsches-Register-Klinischer-Studien/_node.html </sec>
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".