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Record W6903389908 · doi:10.11575/prism/dspace/41030

Examining the experiences of pediatric mental health care providers during the early stage of the COVID-19 pandemic

2023· other· en· W6903389908 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Calgary · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthFocus groupPublic healthNonprobability samplingService providerPandemicQualitative research

Abstract

fetched live from OpenAlex

Abstract Background The COVID-19 pandemic fundamentally impacted the way that mental health services were provided. In order to prevent the spread of infection, many new public health precautions, including mandated use of masks, quarantine and isolation, and closures of many in-person activities, were implemented. Public health mandates made it necessary for mental health services to immediately shift their mode of delivery, creating increased confusion and stress for mental health providers. The objective of this study is to understand the impact of pandemics on the clinical and personal lives of mental health providers working with children during the early months of the COVID-19 pandemic, March -June 2020. Methods Mental health providers (n = 98) were recruited using purposive sampling from a public health service in Canada. Using qualitative methods, semi-structured focus groups were conducted to understand the experiences of mental health service providers during the beginning of the COVID-19 pandemic. Results Data from the focus groups were analysed and three main themes emerged: (1) shift to virtual delivery and working from home; (2) concerns about working in person; (3) exhaustion and stress from working through the pandemic. Discussion This study gave voice to mental health providers as they provided continuity of care throughout the uncertain early months of the pandemic. The results provide insight into the impact times of crisis have on mental health providers, as well as provide practical considerations for the future in terms of supervision and feedback mechanisms to validate experiences.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score0.983

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.029
GPT teacher head0.250
Teacher spread0.220 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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