Evaluating the Impact of the National Health Service Digital Academy on Participants’ Perceptions of Their Identity as Leaders of Digital Health Change: Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: The key to the digital leveling-up strategy of the National Health Service is the development of a digitally proficient leadership. The National Health Service Digital Academy (NHSDA) Digital Health Leadership program was designed to support emerging digital leaders to acquire the necessary skills to facilitate transformation. This study examined the influence of the program on professional identity formation as a means of creating a more proficient digital health leadership. OBJECTIVE: This study aims to examine the impact of the NHSDA program on participants' perceptions of themselves as digital health leaders. METHODS: We recruited 41 participants from 2 cohorts of the 2-year NHSDA program in this mixed methods study, all of whom had completed it >6 months before the study. The participants were initially invited to complete a web-based scoping questionnaire. This involved both quantitative and qualitative responses to prompts. Frequencies of responses were aggregated, while free-text comments from the questionnaire were analyzed inductively. The content of the 30 highest-scoring dissertations was also reviewed by 2 independent authors. A total of 14 semistructured interviews were then conducted with a subset of the cohort. These focused on individuals' perceptions of digital leadership and the influence of the course on the attainment of skills. In total, 3 in-depth focus groups were then conducted with participants to examine shared perceptions of professional identity as digital health leaders. The transcripts from the interviews and focus groups were aligned with a previously published examination of leadership as a framework. RESULTS: Of the 41 participants, 42% (17/41) were in clinical roles, 34% (14/41) were in program delivery or management roles, 20% (8/41) were in data science roles, and 5% (2/41) were in "other" roles. Interviews and focus groups highlighted that the course influenced 8 domains of professional identity: commitment to the profession, critical thinking, goal orientation, mentoring, perception of the profession, socialization, reflection, and self-efficacy. The dissertation of the practice model, in which candidates undertake digital projects within their organizations supported by faculty, largely impacted metacognitive skill acquisition and goal orientation. However, the program also affected participants' values and direction within the wider digital health community. According to the questionnaire, after graduation, 59% (24/41) of the participants changed roles in search of more prominence within digital leadership, with 46% (11/24) reporting that the course was a strong determinant of this change. CONCLUSIONS: A digital leadership course aimed at providing attendees with the necessary attributes to guide transformation can have a significant impact on professional identity formation. This can create a sense of belonging to a wider health leadership structure and facilitate the attainment of organizational and national digital targets. This effect is diminished by a lack of locoregional support for professional development.
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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 | 0.053 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".