ADHD and career sustainability: a sustainable career ecosystem perspective
Bibliographic record
Abstract
Purpose We explore the perceptions of career sustainability of individuals with attention-deficit/hyperactivity disorder (ADHD) in the United States, taking a sustainable career ecosystem perspective that considers multiple sustainability indicators and different interdependent actors. Design/methodology/approach We conducted semi-structured interviews with 31 participants and analyzed the data using a template approach that allows combining deductive and inductive analysis. Findings We identify how ADHD impacts different aspects of sustainable careers, namely time, person-related factors and indicators (i.e. happiness, productivity and health). Moreover, our findings identify empirical support for two additional indicators (financial security and growth mindset) as proposed by sustainable career ecosystem theory. We suggest a disproportionate impact of ADHD on the indicators, specifically, productivity, due to contextual workplace barriers. We also identify key actors at the local ecosystem level (e.g. family members, teachers, neighbors, friends, co-workers and therapists) that play an important role in individual careers within the ecosystem, particularly regarding diagnosis and support. Originality/value We provide empirical insights that support the recently developed sustainable career ecosystem theory and suggest a differential impact of ADHD on the indicators.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".