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Record W4308712491 · doi:10.3390/ijerph192214739

Mental Fatigue, Activities of Daily Living, Sick Leave and Functional Status among Patients with Long COVID: A Cross-Sectional Study

2022· article· en· W4308712491 on OpenAlexaboutno aff
Trine Brøns Nielsen, Steffen Leth, Mathilde Pedersen, Helle Dahl Harbo, Claus Vinther Nielsen, Cecilia Hee Laursen, Berit Schiøttz‐Christensen, Lisa Gregersen Oestergaard

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2022
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsnot available
Fundersnot available
KeywordsActivities of daily livingSick leaveCross-sectional studyRehabilitationMedicineCoronavirus disease 2019 (COVID-19)Occupational therapyDanishPhysical therapyMental healthPsychologyPsychiatryDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Studies suggest that persistent symptoms after COVID-19 (long COVID) influence functioning and activities of daily living (ADL). However, it is still uncertain how and to what extent. This study aimed to describe patient-reported mental fatigue, ADL problems, ADL ability, sick leave and functional status among patients with long COVID. In this cross-sectional study, 448 patients, ≥18 years old and referred to occupational therapy at a Danish Post-COVID-19 Clinic, were included. Mental fatigue was measured by the Mental Fatigue Scale, ADL problems and ability were measured by the Canadian Occupational Performance Measure, sick leave was self-reported and functional status was evaluated by the Post-COVID-19 Functional Status Scale. Mean age was 46.8 years, 73% of the patients were female, and 75% suffered from moderate to severe mental fatigue. The majority reported difficulties performing productive and leisure activities. The median performance and satisfaction scores were 4.8 and 3, respectively. In total, 56% of the patients were on sick leave, and 94% were referred to rehabilitation. A decrease in functional status was found between pre-COVID-19 and assessment. Conclusively, the patients were highly affected in their everyday life and had distinct rehabilitation needs. Future research is needed to address causalities and rehabilitation for this patient group.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.050
GPT teacher head0.383
Teacher spread0.333 · 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 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".

Quick stats

Citations49
Published2022
Admission routes1
Has abstractyes

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