MétaCan
Menu
← Back to cohort
Record W7053214975

Treatment Preferences of Adult Patients with Attention-Deficit/Hyperactivity Disorder – A Discrete Choice Experiment

2024· article· en· W7053214975 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsFeelingAnxietyLogistic regressionNauseaPreferenceYoung adultSample (material)Discrete choice
DOInot available

Abstract

fetched live from OpenAlex

Jeff Schein,1 Martin Cloutier,2 Marjolaine Gauthier-Loiselle,2 Maryaline Catillon,3 Yan Meng,4 Beatrice Libchaber,2 Fanny Jiang,2 Ann Childress5 1Otsuka Pharmaceutical Development & Commercialization, Inc, Princeton, NJ, USA; 2Analysis Group, Inc, Montréal, QC, Canada; 3Analysis Group, Inc, New York, NY, USA; 4Analysis Group, Inc, London, UK; 5Center for Psychiatry and Behavioral Medicine, Las Vegas, NV, USACorrespondence: Maryaline Catillon, Analysis Group, Inc, 151 West 42nd Street, 23rd Floor, New York, NY, 10036, USA, Tel +1 857 222 6863, Email maryaline.catillon@analysisgroup.comBackground: Understanding patient preferences for treatments may facilitate shared decision-making. This study assessed adult patient preferences for attention-deficit/hyperactivity disorder (ADHD) treatments in a sample of 600 patients in the United States (US).Methods: A web-based discrete choice experiment (DCE) survey was conducted among treated adults with ADHD. Participants were recruited from Dynata’s US panel (06/22/2023-07/06/2023). Attributes and levels, identified based on clinical inputs and published data, included efficacy and safety. Participants’ preferences were estimated using conditional logistic regression. Willingness to trade-off and attributes’ relative importance were calculated. Overall preferences for treatment profiles approximating centanafadine, lisdexamfetamine, atomoxetine, and viloxazine were estimated using adjusted total utilities. Results were stratified by current treatment status. Sensitivity analyses including participants who passed validity tests were conducted.Results: Among the 600 participants (mean age 37.9 years; 66.2% female; 50.8% treated), all attributes had a statistically significant impact on preferences for ADHD treatments (p < 0.001); the most important attribute was improvement in ADHD symptoms (36%), followed by risks of nausea (25%), insomnia (20%), anxiety (8%), dry mouth (6%), and feeling jittery (5%). Together, safety attributes accounted for > 60% of relative importance in decision-making. Participants were willing to forgo 0.59, 0.57, 0.49, 0.32, and 0.17 percentage points of symptom improvement to achieve one-percentage-point reduced risk of insomnia, nausea, anxiety, feeling jittery, and dry mouth, respectively. Centanafadine profile had consistently higher adjusted total utilities than its comparators. Similar results were obtained in the subgroup and sensitivity analyses.Conclusion: Efficacy was the most important attribute for patients when making treatment decision, but taken together, AEs had greater relative importance than efficacy alone. Accordingly, a profile resembling that of centanafadine would be preferred by an average patient compared to key competitors due to its favorable safety profile. These findings may help improve treatment decision-making, enhance treatment satisfaction, and foster adherence.Keywords: ADHD, decision-making, discrete choice experiment, patient-centered care, patient satisfaction, patient preference, utility

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.096
GPT teacher head0.491
Teacher spread0.394 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueDOAJ (DOAJ: Directory of Open Access Journals)→Same topicMagnetic confinement fusion research→French-language works237,207→