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Record W4310993179 · doi:10.31234/osf.io/h2vn7

A qualitative forum analysis of fathers’ stressors and support seeking behaviour during the COVID-19 pandemic

2022· preprint· en· W4310993179 on OpenAlexafffund
Emily E. Cameron, Kaeley M. Simpson, John-Michael Bowes, Shayna Pierce, Kailey Elena Penner, Alanna Beyak, Irlanda Gomez, Kristin Reynolds, Leslie E. Roos

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsUniversity of WinnipegChildren's Hospital Research Institute of ManitobaUniversity of Manitoba
FundersResearch Manitoba
KeywordsDistancingPandemicCoronavirus disease 2019 (COVID-19)PsychologyInterpersonal communicationPeer supportSocial supportMental healthStressorSocial distancePublic healthPsychological resilienceSocial psychologyNursingMedicineClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Fathers experienced high rates of mental health concerns during the COVID-19 pandemic. Social support is crucial to mitigate these problems; however, access to and quality of support were impacted by public health guidelines to increase physical distancing. Online forums offer an avenue for peer connection and support. Yet, minimal research has examined forum use during COVID-19 to describe the experiences, perceived stressors, and resource need of fathers during the pandemic. This study qualitatively analyzed fathers’ experiences through a Framework Analytic Approach of reddit’s sub-forum r/daddit. Posts (N=299) and comments (N=2597) between July and October 2020 were analyzed. Findings highlighted five main themes (with subthemes): forum use, family functioning, psychological and health factors, interpersonal functioning, and COVID-19. First and foremost, fathers used the online forum to provide support and advice to other fathers. Main themes are discussed in terms of informing the development of services to support father and family wellbeing.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0050.003
Scholarly communication0.0020.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.091
GPT teacher head0.428
Teacher spread0.338 · 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 source (direct Gemma or distilled Codex), 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".

Quick stats

Citations0
Published2022
Admission routes2
Has abstractyes

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