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DEC-12 “The Hardest Decision I Ever Had”: Parent Decision Making About Tnf-Alpha Inhibitor Treatment

2011· article· en· W3005867289 on OpenAlex
Ellen A. Lipstein, Daniel J. Lovell, Lee A. Denson, David W. Moser, Shehzad A. Saeed, Cassandra M. Dodds, Maria T. Britto

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Bioresource Management · 2011
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical studies and practices
Canadian institutionsnot available
Fundersnot available
KeywordsAlpha (finance)MedicineComputer scienceNursing

Abstract

fetched live from OpenAlex

Purpose: Parents’ treatment decisions in pediatric chronic disease are often complicated by tradeoffs between disease and treatment risks, as well as the difficulty of proxy decision making. The objective of this study was to describe the information and process parents use to make treatment decisions for their children with chronic conditions; using decisions about TNF-α inhibitor (TNFαi) treatment, which has risks of immunosuppression and malignancy, as a model.\nMethod: We conducted semi-structured interviews with parents of children with Crohn’s Disease (CD) (n = 14) or Juvenile Idiopathic Arthritis (JIA) (n = 20) who had experience deciding about TNFαi treatment. Participants had made a decision within the prior year, been referred to the study BECause of difficulty in decision making or were in the process of making the decision. Interview questions, developed based on existing pediatric decision-making literature and the Ottawa Decision Support Framework, were focused on information used to make decisions, factors that influenced decision making and the decision timeline. We used thematic analysis for all coding and analysis. Coding structure was developed through multidisciplinary team review of the initial interviews. Two coders then coded the remaining interviews, compared coding, and resolved disagreements through discussion. Data were analyzed by thematic grouping and compared between CD and JIA.\nResult: For nearly all parents, the decision about TNFαi treatment was the most challenging medical decision they had made. However, parents of children with CD experienced more, and ongoing, stress and anxiety related to the decision. In both groups, parents sought information from multiple sources including health care providers, the internet and social contacts. They looked for information related to treatment effectiveness, side-effects and individuals’ experiences with such treatment. In CD, where the decision often occurred over weeks to months, information was most often used to help make the decision. In contrast, in JIA the decision was often made in a single clinic appointment and information was then used to confirm the parent’s choice.\nConclusion: Even after a decision has been made, some parents are left with persistent information needs, long-lasting concerns and worry related to TNFαi treatment for their child. Providing parents with structured support, including treatment-specific information, during TNFαi decision making may lead to improved decision quality, decreased psychosocial distress and, ultimately, improved outcomes for their children

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.934
Threshold uncertainty score0.601

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.089
GPT teacher head0.359
Teacher spread0.270 · 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