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Enregistrement W2974388509 · doi:10.1177/2327857919081029

Health Behavior Nudging Through Health Information Exposure and Information Search

2019· article· en· W2974388509 sur OpenAlexaff
Jessie Chin, Ece Üreten, Catherine M. Burns

Notice bibliographique

RevueProceedings of the International Symposium on Human Factors and Ergonomics in Health Care · 2019
Typearticle
Langueen
DomaineHealth Professions
ThématiqueHealth Literacy and Information Accessibility
Établissements canadiensUniversity of Waterloo
Organismes subventionnairesnon disponible
Mots-clésPsychologyHealth informationPublic healthThe InternetHealth Information National Trends SurveyInformation behaviorHealth behaviorApplied psychologySocial psychologyEnvironmental healthMedicineHealth careComputer scienceWorld Wide WebNursingPolitical science

Résumé

récupéré en direct d'OpenAlex

As the Internet has become one of the dominant sources of health information, online health information plays an important role for patients to acquire health knowledge and regulate their health behavior (European Commission, 2014). Researchers suggested different ways to nudge public health behavior through environments and policies (Marteau et al., 2011); few studies had explored the potential to use online health information environment to nudge health behavior. While there was established evidence showing the individual differences in online health information search behavior across the lifespan (e.g., Chin et al., 2009; Sharit et al., 2008), the current study was to examine the nudging effects on health behavior through online health information exposure and search. An online mixed-factor-design experiment was conducted on 136 adults across the lifespan (Mean age=49.79, SD=16.00). We examined two kinds of nudging routes, (1) health information exposure (manipulated by the experimenters), and (2) health information search (decided by the participants), on two kinds of health behaviors varying in the costs of taking these health behaviors. Target health behaviors included, (1) self-related health behavior: participants were asked to take a break for doing a stretch (low cost) or a walk (high cost) after long sitting; (2) self-unrelated health behavior: participants were asked to have researchers to donate to the rare disease association through writing down the date (low cost) or a 100-word endorsement article (high cost). In the experiment, each participant was assigned to read four topics (3 articles under each topic) and answer the questions after each health topic. The questions varied in difficulties, which participants could decide to answer the questions based on their own knowledge, their memory from reading, or searching the answers online. To manipulate health information exposure, half of the participants were assigned to read the online articles related to the target health behaviors (such as the harms of long sitting and the target rare disease). Participants were not disclosed about the study goals at the beginning. They were not told that the study goal was to examine whether they took the target health behaviors or not, but to examine how adults learn from online health information. To measure the actions of target health behaviors, for the self-related health behavior, after roughly 40 minutes of the study, participants were requested to take a break for 10 minutes. For the self-unrelated health behavior, at the end of the study, participants were asked whether they would like to show their support to a rare disease association. The manipulations in the costs of health behaviors were assigned in counterbalanced order. Logistic regressions were used to examine the effects of nudging routes and costs of actions on two kinds of target health behaviors. Results suggested that mere information exposure did not affect the likelihood to take the target health behaviors regardless of its relatedness to self-interests or costs of actions. Further, for self-related health behavior, adults were more likely to take actions after a more deliberate engagement with the information - through information search. For health behavior that was unrelated to self-interests, participants were more likely to take actions after they searched the information about this rare disease and only when the costs of actions were low. This study has shown the potentials and limitations of health nudging in different health behaviors, and has its implications on designing effective health nudging strategies on different health behaviors.

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)0,002
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: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,055
Score d'incertitude au seuil0,691

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,004
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
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 Opus0,037
Tête enseignante GPT0,389
Écart entre enseignants0,352 · 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

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

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