Development of a Mobile App to Monitor the Effectiveness of a Hydrolyzed Cartilage Matrix Supplement on Joint Discomfort: Real-World Study
Notice bibliographique
Résumé
BACKGROUND: Joint discomfort is a widespread and growing problem in active adults. The rising interest in preventative nutrition has increased the demand for supplements reducing joint discomfort. Protocols assessing the effect of a nutritional intervention on health commonly involve a series of face-to-face meetings between participants and study staff that can weigh on resources, participant availabilities, and even increase dropout rates. Digital tools are increasingly added to protocols to facilitate study conduct, but fully digitally run studies are still scarce. With the increasing interest in real-world studies, the development of health apps for mobile devices to monitor study outcomes is of great importance. OBJECTIVE: The purpose of this real-world study was to develop a specific mobile app, Ingredients for Life, to conduct a 100% digital study testing the effectiveness of a hydrolyzed cartilage matrix (HCM) supplement on joint discomfort in a heterogeneous group of healthy, active consumers. METHODS: The Ingredients for Life mobile app using a visual analog scale was specifically developed to monitor the variation in joint pain after exercise by the study participants. A total of 201 healthy and physically active women and men (18-72 years old) with joint pain completed the study over a period of 16 weeks. Participants were randomly allocated to the study groups and did not receive any dietary or lifestyle advice. Each participant indicated one area of joint pain and logged the type and duration of their weekly activities. They received blinded study supplements and took a daily regimen of 1 g of HCM (HCM group) or 1 g of maltodextrin (placebo group) for 12 weeks while weekly logging joint pain scores in the app. This was followed by a 4-week washout period during which participants continued reporting their joint pain scores (until the end of week 16). RESULTS: Joint pain was reduced within 3 weeks of taking a low dosage of HCM (1 g/day), regardless of gender, age group, and activity intensity when compared with the placebo group. After stopping supplementation, joint pain scores gradually increased but still remained significantly lower than those of the placebo group after 4 weeks of washout. The low dropout rate (<6% of participants, mainly in the placebo group) demonstrates that the digital study was well received by the study population. CONCLUSIONS: The digital tool allowed us to measure a heterogeneous group of active adults in a real-world setting (without any lifestyle intervention), thus promoting inclusivity and diversity. With low dropout rates, it demonstrates that mobile apps can generate qualitative, quantifiable, real-world data showcasing supplement effectiveness. The study confirmed that the oral intake of a low dose (1 g/day) of HCM led to a significant reduction of joint pain from 3 weeks after starting supplementation.
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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 | 0,003 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| 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 ».