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A Perfect Storm: Unintended Effects of Homeschooling on Parents’ Mental Health and Cannabis Use Behaviors During the Pandemic

2021· article· en· W4236908959 on OpenAlexaboutno aff
Mariam M. Elgendi, S. Hélène Deacon, Lindsey M. Rodriguez, Fiona King, Simon Sherry, Allan Abbass, Sandra Meier, Raquel Nogueira‐Arjona, Amanda Hagen, Sherry H. Stewart

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Education Studies and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsAnxietyPandemicMental healthPsychologyDepression (economics)OptimismFeelingCannabisClinical psychologyCoronavirus disease 2019 (COVID-19)PsychiatryMedicineSocial psychology

Abstract

fetched live from OpenAlex

The COVID-19 pandemic resulted in families self-isolating under incredible stress. Viral containment strategies included school closures with parents left to homeschool their children with few supports from the educational system. Recent data show that those with children at home were more likely to drink heavily during the pandemic (Rodriguez et al., in press). Gaps remain, however, in understanding whether these effects are due to the stresses of homeschooling and whether they extend to cannabis use. Seven-hundred-and-sixty Canadian romantic couples (total N=1520 participants; mean age = 57 years; 50% women) who were self-isolating together during the month of April 2020 were recruited through Qualtrics Panel Surveys. Measures were completed retrospectively in early July 2020; participants were asked to report on their feelings and behavior in April 2020 during lockdown. They completed the GAD-7 (Spitzer et al., 2006) and the PHQ-9 (Kronke et al., 2001) to assess anxiety and depression, brief versions of four subscales of the COVID-19 Stress Scales (Taylor et al., 2020) to assess stress around the pandemic, and the Life Orientation Test – Revised (Chiesi et al., 2013) to assess optimism. They completed a measure of role strain (Statistics Canada, 2015) and a measure of conflict with their partner (Murray et al., 2003). They also completed a validated measure of cannabis use frequency and quantity (Cuttler et al., 2017), as well as two validated items from the Brief Cannabis Motives Measures (Bartel et al., 2020) to assess cannabis use to cope with depression and anxiety, respectively. All measures were completed for a 30-day timeframe during the month of April. Participants also reported on whether they were homeschooling one or more children in Grade 1-12 during the month of April. Data was analyzed with a one-way (homeschooling group) Analysis of Covariance (ANCOVA) controlling for group differences in age; a Bonferroni-correction was applied to account for multiple tests. Compared to those who did not homeschool (n=1116), those who did homeschool (n=404) experienced significantly more depression (p=.001), more COVID-19-related stress around socioeconomic consequences (p<.001) and traumatic stress (p<.001), and less optimism (p=.002). And those who homeschooled experienced more role strain between their home and work responsibilities (p<.001) and more conflict both toward and from their partner (p’s<.001) than those who did not homeschool. Those who homeschooled also used cannabis significantly more frequently in the month of April than those who did not homeschool (p=.003). Compared to cannabis users who did not homeschool (n=122), cannabis users who did homeschool (n=61) reported more frequent cannabis use to cope with both depression and anxiety (p’s = .003). These findings suggest that unintended consequences of our societal viral containment strategies include more depression, pessimism, role strain, inter-parental conflict, and certain COVID-related stresses, and extend to more frequent cannabis use to cope with negative affect, among parents required to homeschool during the pandemic. These unintended mental health and substance misuse consequences for parents need to be considered when planning for an educational strategy in the fall and for any future waves of the pandemic.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.293
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.022
GPT teacher head0.316
Teacher spread0.294 · 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 designObservational
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
Published2021
Admission routes1
Has abstractyes

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