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Record W7077274874 · doi:10.25316/ir-20441

What Clinical Practitioners Need from Leadership to Promote Resilience and Mitigate Risks to Counsellors in a Post-Secondary Environment

2025· dissertation· en· W7077274874 on OpenAlexaboutno aff

Bibliographic record

VenueVIUSpace (Vancouver Island University Library) · 2025
Typedissertation
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsThematic analysisMental healthLeadership styleCompassion fatiguePsychological resilienceTransactional leadershipNarrativeShared leadershipServant leadershipLeadership studies

Abstract

fetched live from OpenAlex

This dissertation examines what clinical practitioners need from leadership to foster resilience and mitigate risks like burnout, compassion fatigue, and vicarious trauma in post-secondary counselling environments. As student mental health demands surge—especially post-COVID—counsellors are stretched thin, managing increasingly complex cases with limited institutional support. While these professionals are trained to provide care, they often lack the same level of care from their workplaces, leaving them vulnerable to emotional exhaustion, disengagement, and burnout. Despite their essential contributions, counsellors face systemic barriers, inadequate institutional support, and leadership gaps that exacerbate workplace stress. This study amplifies the voices of post-secondary counsellors and clinical leaders from various Canadian institutions using a qualitative, phenomenological approach with narrative inquiry. Twelve participants—eight counsellors and four clinical leaders—shared their experiences, shedding light on the structural and leadership gaps that impact their well-being. Thematic analysis, supported by NVivo, revealed key trends: a lack of trauma-informed leadership, unsustainable caseloads, unrealistic institutional expectations, and limited opportunities for professional growth. Findings highlight that effective leadership is not just about policies—it’s about people. When leaders prioritize counsellor well-being, staff retention improves, service quality strengthens, and students receive better care. The research underscores the need for leadership models beyond traditional frameworks, incorporating trauma-informed, feminist, and servant leadership approaches that create psychologically safe workplaces. Recommendations include reducing caseloads, implementing structured peer support, offering flexible work options, and embedding professional development into institutional priorities. The study also introduces the Counsellor-Centered Leadership Assessment Model (CCLAM), a tool designed to help institutions evaluate

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.596
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.233
Teacher spread0.212 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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