Regardless of how risks are framed, patients seem hesitant to use topical steroids for atopic dermatitis
Notice bibliographique
Résumé
Dear Editor, Topical corticosteroids are highly effective in treating atopic dermatitis (AD); however, patients often fear their potential adverse events.1 This fear may be exacerbated by risk aversion. Risk aversion is the tendency to avoid unknown risks in favour of more certain, but less advantageous outcomes.2 Previous studies suggest that how physicians frame the risks and benefits of a treatment can have an impact on patients’ decision making; if physicians framed actinic keratosis as a precancerous condition instead of a condition that could spontaneously resolve without becoming cancerous, patients preferred treatment.3 Because the word ‘cancer’ may elicit strong emotions, we focused on a lower‐risk dermatological condition to understand the nature of framing better. Physicians often present the benefits alongside the risks of treatment. Risk aversion may lead patients to consider the risk of treatment more heavily than the potential benefits. To assess the effect of ‘framing’, we assessed whether patients with a history of AD were more willing to take a topical corticosteroid treatment when the treatment benefits were rephrased as the risk of not taking treatment. The study was approved by the Wake Forest School of Medicine institutional review board. Informed consent was obtained verbally and assumed based on patient survey completion. A total of 613 participants with a diagnosis of AD and aged 18 years or older were recruited in clinic and divided into three subgroups (Table 1). Within each subgroup, participants were randomized to a script that discussed either the risk of the topical steroid vs. risk of not experiencing eczema improvement or the risk of topical steroid vs. benefit of eczema improvement. Participants used a 10‐point Likert scale (from 1, ‘not willing’ to 10, ‘completely willing’), to rate their willingness to take a treatment described as a topical corticosteroid (Table 1). Scores were treated as ordinal data and evaluated with the Mann–Whitney U‐test. Median willingness to take a treatment based on ‘risk vs. benefit’ and ‘risk vs. risk’ presentation Subgroup 1a: control group (risk vs. benefit); subgroup 1b: intervention group (risk vs. risk). Median willingness to take a treatment based on ‘risk vs. benefit’ and ‘risk vs. risk’ presentation Subgroup 1a: control group (risk vs. benefit); subgroup 1b: intervention group (risk vs. risk). There were no significant differences between the subgroup's baseline characteristics. Participants were 38·4 ± 7·5 years on average, 56% were women and 49% were of white, 12% African American, 4% Hispanic, 28% Asian and 7% were of another ethnicity. Participants reported having eczema for 13·9 ± 4·9 years on average and 99% of participants had attained a high‐school diploma or higher education. Participants in subgroup 1 were more likely to take a treatment when presented with risk of treatment vs. risk of nontreatment (P = 0·041). Participants in subgroups 2 and 3 were as willing to take a treatment for AD whether they were presented with a potential risk of treatment contrasted to its potential benefit, or a potential risk of treatment contrasted to its potential risk of no treatment (Table 1). While the use of risk aversion is well‐studied in behavioural economics, its practice within medicine is nascent.4 Although previous studies suggest that physicians’ framing has an impact on patients’ decision‐making process, our data suggests that framing of risks and benefits was not a predominant factor affecting patients with AD's consideration of treatment.3 Nevertheless, subgroup 1 participants were more willing to take a treatment when presented with risk of treatment vs. risk of nontreatment, which may support the critical importance of word choice and sentence structure in framing. One explanation that may support our findings may be the low‐risk–low‐benefit characteristic of the presented treatment. Since the stakes of risks of both nontreatment and treatment in this study were relatively low, the effect of framing may have been minimal. ‘Order effect’ may also explain our findings. The presentation order of risks and benefits affects participants’ willingness to take a new treatment, especially for low‐risk decisions.5 Another explanation may be that the different wording between the scripts may have affected a participant's view of risk and therefore willingness. Additionally, as different presenters asked survey questions, social cues such as facial expressions or inflection, could have affected participants’ decision making. Physicians should consider asking patients what factors influence their decisions concerning treatment options. While the presentation of ‘risk vs. risk’ or ‘risk vs. benefit’ does not seem to influence the use of a corticosteroid in AD, further exploration of other behavioural economic principles within dermatology may help improve patient adherence and patient outcomes. Funding sources: none. Conflicts of interest: S.R.F. has received research, speaking and/or consulting support from a variety of companies including Galderma, GSK/Stiefel, Almirall, Leo Pharma, Baxter, Boehringer Ingelheim, Mylan, Celgene, Pfizer, Valeant, Taro, Abbvie, Cosmederm, Anacor, Astellas, Janssen, Lilly, Merck, Merz, Novartis, Regeneron, Sanofi, Novan, Parion, Qurient, National Biological Corporation, Caremark, Advance Medical, Sun Pharma, Suncare Research, Informa, UpToDate and National Psoriasis Foundation. He is founder and majority owner of www.DrScore.com and founder and part owner of Causa Research, a company dedicated to enhancing patients’ adherence to treatment.
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 | 0,003 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,037 | 0,024 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,005 |
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 ».