Gender Effects on the Impact of Colorectal Cancer Risk Calculators on Screening Intentions: Experimental Study
Notice bibliographique
Résumé
BACKGROUND: According to a 2020 study by the American Cancer Society, colorectal cancer (CRC) represents the third leading cause of cancer both in incidence and death in the United States. Nonetheless, CRC screening remains lower than that for other high-risk cancers such as breast and cervical cancer. Risk calculators are increasingly being used to promote cancer awareness and improve compliance with CRC screening tests. However, research concerning the effects of CRC risk calculators on the intention to undergo CRC screening has been limited. Moreover, some studies have found the impacts of CRC risk calculators to be inconsistent, reporting that receiving personalized assessments from such calculators lowers people's risk perception. OBJECTIVE: The objective of this study is to examine the effect of using CRC risk calculators on individuals' intentions to undergo CRC screening. In addition, this study aims to examine the mechanisms through which using CRC risk calculators might influence individuals' intentions to undergo CRC screening. Specifically, this study focuses on the role of perceived susceptibility to CRC as a potential mechanism mediating the effect of using CRC risk calculators. Finally, this study examines how the effect of using CRC risk calculators on individuals' intentions to undergo CRC screening may vary by gender. METHODS: We recruited a total of 128 participants through Amazon Mechanical Turk who live in the United States, have health insurance, and are in the age group of 45 to 85 years. All participants answered questions needed as input for the CRC risk calculator but were randomly assigned to treatment (CRC risk calculator results immediately received) and control (CRC risk calculator results made available after the experiment ended) groups. The participants in both groups answered a series of questions regarding demographics, perceived susceptibility to CRC, and their intention to get screened. RESULTS: We found that using CRC risk calculators (ie, answering questions needed as input and receiving calculator results) has a positive effect on intentions to undergo CRC screening, but only for men. For women, using CRC risk calculators has a negative effect on their perceived susceptibility to CRC, which in turn reduces the intention to sign up for CRC screening. Additional simple slope and subgroup analyses confirm that the effect of perceived susceptibility on CRC screening intention is moderated by gender. CONCLUSIONS: This study shows that using CRC risk calculators can increase individuals' intentions to undergo CRC screening, but only for men. For women, using CRC risk calculators can reduce their intentions to undergo CRC screening, as it reduces their perceived susceptibility to CRC. Given these mixed results, although CRC risk calculators can be a useful source of information on one's CRC risk, patients should be discouraged from relying solely on them to inform decisions regarding CRC screening.
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 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 | 0,004 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| 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 | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,022 | 0,002 |
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 ».