Examining the experiences of post-ABI and neurological condition sequalae and workplace disclosure.
Bibliographic record
Abstract
This thesis portfolio is comprised of three parts, a systematic literature review, an empirical thesis, and appendices. Part 1 contains a systematic literature review, aiming to explore the experiences of individuals disclosing Multiple Sclerosis (MS) in the workplace. All qualitative data in this area was reviewed and the results of 10 studies were incorporated through a narrative synthesis. Four main themes were generated; Disclosure of MS, Transition in Identity, Group Reactions to the Individual following Disclosure and Locus of Change and Emotional Impact. These results have implications for ongoing support for individuals following an MS diagnosis. Part 2 contains the empirical study, which aims to understand the properties of the Brain Injury Fatigue Scale (BIFS). This study was comprised of two main aims which contribute to a larger ongoing study, firstly to identify the underlying factor structure within the BIFS and secondly to explore the moderating effects of brain injury on the relationship between fatigue and anxiety, depression, age and gender. The exploratory factor analysis uncovered a two-factor structure, with the main factor of ‘general fatigue’ explaining the majority of variance within the scale. A secondary factor of ‘cognitive and emotional impacts of fatigue’ was also identified. Additionally, positive correlations were found between fatigue and age, anxiety and depression. Within this, brain injury was shown to moderate the relationship between anxiety and fatigue. These results inform the ongoing debate around the dimensional nature of fatigue and have implications for fatigue interventions for individuals having sustained a brain injury. Part 3 contains the appendices. The attached appendices provide supporting documentation for the systematic literature review and the empirical study. Additionally, the appendices contain an epistemological statement and reflective statement written by the chief investigator.
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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 | 0.020 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".