Feasibility of a tablet computer based food record for self-assessment of nutritional intake in geriatric rehabilitation patients: a pilot study (Preprint)
Notice bibliographique
Résumé
Abstract Background Nutritional status is an influential factor for functional status and rehabilitation outcomes in patients undergoing geriatric rehabilitation. Although there is evidence for the potential of eHealth interventions in patients undergoing geriatric rehabilitation in general, the evidence for eHealth interventions with a 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. Objective Therefore, the aim of this study was to verify whether it is feasible for patients undergoing geriatric rehabilitation to independently use a tablet computer−based food record (e-food record) 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 patients undergoing geriatric rehabilitation. Methods This prospective pilot study investigated the general feasibility of an e-food record in older adults (≥70 y) in a geriatric rehabilitation center in Germany. It was tested whether the e-food record could be independently used by the participants over 3 days. Furthermore, the usability of the e-food record was assessed by the System Usability Scale (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 24-hour recall for the same time period, and the mean difference was calculated as follows: the value of the 24-hour recall minus the value of the e-food record. As the study was characterized as a pilot, the data analysis was descriptive. Results Seventeen out of 25 patients (n=6, 35.3% female, mean age 79.5, SD 3.7 y) maintained the e-food record independently over the study period. The mean System Usability Scale score of the e-food record was 76.0 (SD 11.3) points. Datasets of 9 out of 17 participants (n=5, 55.6% female, mean age 78.2, SD 2.9 y) were analyzed in terms of nutritional data. Mean differences in energy, protein, and fluid intake by the 24-hour recall compared to the e-food record were 4.9 (SD 10.2) kcal/kg body weight (bw), 0.1 (SD 0.3) g/kg bw, and 4.9 (SD 9.4) g/kg bw, respectively. Conclusions The use of an e-food record is generally feasible for patients undergoing geriatric rehabilitation characterized by low technical experience, high mean age, and a high rate of functional impairment. Lower intake levels were observed for the e-food record compared to the 24-hour 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.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».