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Record W4223997169 · doi:10.1177/17446295211062381

Stress Levels and Coping Strategies of Families of Adults With Intellectual Disability and Challenging Behaviours During the COVID-19 Pandemic in Qatar

2022· article· en· W4223997169 on OpenAlexaff
Mohamed El Tahir, Bushra Elhusein, Hassan Elamin, Hesham Rustom, Shuja Reagu, Hanan Bedhiaf, Salwa Abdirahman, Majid Alabdulla

Bibliographic record

VenueJournal of Intellectual Disabilities · 2022
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsCoping (psychology)PsychologyPandemicCoronavirus disease 2019 (COVID-19)Perceived Stress ScaleClinical psychologyIntellectual disabilityBlameSocial supportCross-sectional studyPsychiatryMedicineStress (linguistics)DiseaseSocial psychologyInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

This study investigated the perceived stress levels and coping strategies of caregivers of adults with intellectual disability and challenging behaviours during the COVID-19 pandemic in Qatar. A cross-sectional survey was conducted from June 7 to September 7, 2020 for caregivers of adults diagnosed with intellectual disability and challenging behaviours. Perceived stress levels and coping strategies were assessed using the Perceived Stress Scale and Brief Coping Orientation to Problems Experienced inventory. Results showed moderate to high perceived stress levels in most caregivers (69%). The most frequent coping strategy was religion, followed by acceptance and active coping. Substance use and self-blame were less frequently used. The study revealed that emotional support, informational support and venting coping strategies were significant predictors of perceived stress levels. Restrictions on physical activity and social mobility caused by pandemic-related lockdowns have placed tremendous pressure on caregivers. Appropriate supportive measures should be implemented for the caregivers.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.517
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.075
GPT teacher head0.350
Teacher spread0.275 · 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

Citations14
Published2022
Admission routes1
Has abstractyes

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