Decision-making for Parents of Children With Medical Complexities: Activity Theory Analysis
Bibliographic record
Abstract
BACKGROUND: Shared decision-making (SDM), a collaborative approach to reach decisional agreement, has been advocated as an ideal model of decision-making in the medical encounter. Frameworks for SDM have been developed largely from the clinical context of a competent adult patient facing a single medical problem, presented with multiple treatment options informed by a solid base of evidence. It is difficult to apply this model to the pediatric setting and children with medical complexity (CMC), specifically since parents of CMC often face a myriad of interconnected decisions with minimal evidence available on the multiple complex and co-existing chronic conditions. Thus, solutions that are developed based on the traditional model of SDM may not improve SDM practices for CMCs and may be a factor contributing to the low rate of SDM practiced with CMCs. OBJECTIVE: The goal of our study was to address the gaps in the current approach to SDM for CMC by better understanding the decision-making activity among parents of CMCs and exploring what comprises their decision-making activity. METHODS: We interviewed 12 participants using semistructured interviews based on activity theory. Participants identified as either a parent of a CMC or a CMC over the age of 18 years. Qualitative framework analysis and an activity theory framework were employed to understand the complexity of the decision-making process in context. RESULTS: Parents of CMCs in our study made decisions based on a mental model of their child's illness, informed by the activities of problem-solving, seeking understanding, obtaining tests and treatment, and caregiving. These findings suggest that the basis for parental choice and values, which are used in the decision-making activity, was developed by including activities that build concrete understanding and capture evidence to support their decisions. CONCLUSIONS: Our interviews with parents of CMCs suggest that we can address both the aims of each individual activity and the related outcomes (both intended and unintended) by viewing the decision-making activity as a combination of caregiving, problem-solving, and seeking activities. Clinicians could consider using this lens to focus decision-making discussions on integrating the child's unique situation, the insights parents gain through their decision-making activity, and their clinical knowledge to enhance the understanding between parents and health care providers, beyond the narrow concept of parental values.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".