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Enregistrement W7019068790

Evaluation For Buying and Eating Fruits and Vegetables Among Teens and Moms Exposed to the Fruits & Veggies (FNV) Campaign in California and Virginia, 2015-2017

2017· report· en· W7019068790 sur OpenAlexaboutno aff

Notice bibliographique

RevueVTechWorks (Virginia Tech) · 2017
Typereport
Langueen
DomaineMedicine
ThématiqueConsumer Attitudes and Food Labeling
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésQuarter (Canadian coin)Consumption (sociology)Logo (programming language)Test (biology)Data collection
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

In 2015, the PHA launched the branded FNV (Fruits & Veggies) Campaign in California and Virginia to increase sales and consumption of fruits and vegetables among millennial moms (21-34 years) and Generation Z teens (15-20 years). This study summarizes trends in U.S. fruit and vegetable consumption behaviors. We also describe the survey results that examined the familiarity of the FNV Campaign among Generation Z teens and Millennial moms in the two lead cities or test locations—Fresno in the Central Valley region of California and the Hampton Roads region of southeastern Virginia.
\nMethods: A 35-item Qualtrics survey was administered either in person or online to Millennial moms and Generation Z teens in the two lead cities (n= 1604; Fresno, California: n= 746; Hampton Roads, Virginia: n=858) between February 1, 2017 and June 31, 2017. Data were analyzed using SPSS version 24 for Windows (IBM Corporation, USA, 2016). We analyzed differences in cognitive, affective, and behavioral outcomes by each test location. Differences within each city were compared between those who were familiar versus unfamiliar with the FNV Campaign. 
\nResults: About a quarter (25%) of respondents in each lead city (25.2% in Fresno, California and 25.8% in Hampton Roads, Virginia) were familiar with the FNV Campaign. In Hampton Roads, Virginia, a larger percentage of respondents reported having seen the FNV logo, while in Fresno, California, respondents reported an equal distribution between seeing the logo online or in the community, or just having heard of FNV. Apples, bananas and carrots were the most commonly recognized foods by participants surveyed who recalled seeing the FNV Campaign. There were no statistically significant differences between respondents familiar with the FNV Campaign and their awareness of previous campaigns that encouraged fruits and vegetables (e.g., Five a Day and Fruits and Veggies—More Matters). Respondents familiar with the FNV Campaign were not more knowledgeable about U.S. government-recommended servings of fruits and vegetables (e.g., 4.5 cup equivalents/day), compared to those who were unfamiliar with FNV Campaign. Respon¬dents in both test locations were significantly more likely to agree that they found it hard to purchase fruits and vegetables in their neighborhood and that eating fruits and vegetables affected their health. In Fresno, California but not Hampton Roads, Virginia, respondents familiar with FNV were significantly more confident in their ability to purchase but not prepare fruits and vegetables.
\nThere were statistically significant differences between respondents in Fresno, California who were familiar with the FNV Campaign. These respondents reported more daily servings of 100% vegetable juice, dark-green leafy vegetables and orange-colored vegetables compared to those who were unfamiliar with FNV, although the latter differences were not significant. No differences were observed between respondents who were familiar or unfamiliar with the FNV Campaign in Hampton Roads, Virginia. We found no differences in the fruit and vegetable purchasing behaviors of those familiar versus unfamiliar with the FNV Campaign in either test location. Large supermarkets and farmers’ markets were the two most common locations where respondents’ reported always or mostly shopping for food.
\nConclusions: While a quarter of respondents interviewed were familiar with the FNV brand, more work is needed to influence the target populations’ awareness about the FNV Campaign. There is also a need to understand how to use IMC to promote actionable and memorable messages to encourage target groups to purchase and consume more fruits and vegetables regularly that align with the DGA. We offer six recommendations to inform future research, evaluation and marketing of the FNV Campaign.

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)0,005
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
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 enseignants0,707
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0050,003
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0010,000
Communication savante0,0010,000
Science ouverte0,0000,001
Intégrité de la recherche0,0010,001
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 Opus0,076
Tête enseignante GPT0,363
Écart entre enseignants0,286 · 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.

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

Citations0
Publié2017
Routes d'admission1
Résumé présentoui

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