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Enregistrement W4404081510 · doi:10.2196/63281

Health-Related Messages About Herbs, Spices, and Other Botanicals Appearing in Print Issues and Websites of Legacy Media: Content Analysis and Evaluation

2024· article· en· W4404081510 sur OpenAlexvenueno aff
Ann Gaba, Richard C. Bennett

Notice bibliographique

RevueJMIR Formative Research · 2024
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiquePhytochemistry and biological activity of medicinal plants
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPreprintPrint mediaAdvertisingInternet privacyContent analysisTraditional medicineWorld Wide WebMedicineComputer scienceBusinessSociologySocial science

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Legacy media are publications that existed before the internet. Many of these have migrated to a web format, either replacing or in parallel to their print issues. Readers place an economic value on access to the information presented as they pay for subscriptions and place a higher degree of trust in their content. Much has been written about inaccurate and misleading health information in social media; however, the content and accuracy of information contained in legacy media has not been examined in detail. Discussion of herbs, spices, and other botanicals has been absent from this context. OBJECTIVE: The objectives of this study were to (1) identify the health associations of botanical products mentioned in legacy media targeted to a range of demographic groups and (2) evaluate these health associations for accuracy against published scientific studies. METHODS: In total, 10 popular magazines targeting a range of gender, race/ethnicity, and sexual orientation demographic groups were selected for analysis. Relevant content was extracted and coded over 1 year. Associations between specific botanical products and health factors were identified. For the most frequent botanical-health application associations, a PubMed search was conducted to identify reviews corresponding to each item's indicated applications. Where no systematic reviews were available, single research studies were sought. RESULTS: A total of 237 unique botanical products were identified. There were 128 mentions of these in the print issues and 1215 on the websites. In total, 18 health applications were identified and used to categorize the indicated uses for the various products individually and as general categories. The most frequently mentioned applications were skin care, with 913 mentions, immunity enhancement, with 705 mentions, gastrointestinal health and probiotics, with 184 mentions, and cognitive function (stress and mental health), with 106 mentions. Comparison to published literature evaluating the efficacy of these functions identified positive support for aloe vera, argan oil, chamomile, jojoba oil, lavender, rosemary, and tea tree oil in skin care. Berries, ginger, turmeric, and green tea had the strongest evidence for a role in immunity enhancement. Ginger and oats were supported as having a role in gastrointestinal health. Finally, berries, lavender, ashwagandha, and cannabidiol were supported as having a role in managing stress. Other frequently mentioned items such as aloe vera, ashwagandha, or mushrooms for immunity were less strongly supported. CONCLUSIONS: Comparison of the most prevalent associations between botanical products and health applications to published literature indicates that, overall, these associations were consistent with current scientific reports about the health applications of botanical products. While some products had a greater degree of research support than others, truly egregious falsehoods were absent. Therefore, legacy media may be considered a credible source of information to readers about these topics.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,869
Score d'incertitude au seuil0,155

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,138
Tête enseignante GPT0,414
Écart entre enseignants0,276 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2024
Routes d'admission1
Résumé présentoui

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