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Record W4306255154 · doi:10.1016/j.ssmmh.2022.100163

“Systems trauma”: A qualitative study of work-related distress among service providers to people experiencing homelessness in Canada

2022· article· en· W4306255154 on OpenAlexafffundabout
Nick Kerman, John Ecker, Emmy Tiderington, Amanda Aykanian, Vicky Stergiopoulos, Sean A. Kidd

Bibliographic record

VenueSSM - Mental Health · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of TorontoYork UniversityCentre for Addiction and Mental Health
FundersCanadian Institutes of Health Research
KeywordsMental healthService providerMental distressWorkforceDistressNursingQualitative researchContext (archaeology)PsychologyMedicineService (business)Public relationsPsychiatryBusinessSociologyPolitical scienceClinical psychologyMarketing

Abstract

fetched live from OpenAlex

Service provision to people experiencing homelessness is challenging and stressful work. Yet, there is a dearth of evidence on how the work experiences of service providers contribute to mental health distress and wellness. This qualitative study examined the contributing factors to workplace mental health among service providers to people experiencing homelessness in Canada, with the aim of establishing a causal theory for how work-related challenges cause distress. In-depth interviews were conducted with 40 service providers working in the homeless service, supportive housing, and harm reduction sectors across Canada. Data were analyzed using a grounded theory-informed approach. The workplace mental health of service providers was centred on the concept of “systems trauma,” which refers to the structural and systemic factors that exacerbate the difficulty of service providers’ work, putting them at-risk of work-related mental health distress. “Systems trauma” had multifaceted causes and consequences, as did the organizational- and individual-level factors that protected service providers against its impacts. Overall, the findings highlight how the same sociopolitical context that negatively affects people experiencing homelessness also shapes the workplace mental health of service providers. Supports for managing moral distress, policy and public initiatives to improve the valuation of work with people experiencing homelessness, dedicated funding for workforce development, and further investment in primary and secondary prevention of homelessness are recommended to promote workplace mental health.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.041
GPT teacher head0.408
Teacher spread0.368 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations25
Published2022
Admission routes3
Has abstractyes

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