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Record W3116537455 · doi:10.1101/2020.12.21.20248686

Knowledge, Attitudes, and Practices of People living with SCI towards COVID-19 and their Psychological State during In-patient Rehabilitation in Bangladesh

2020· preprint· en· W3116537455 on OpenAlexaff
Mohammad Anwar Hossain, K M Amran Hossain, Mohamed Sakel, Karen Saunders, Rafey Faruqui, Mohammad Sohrab Hossain, Zakir Uddin, Manzur Kader, Lori Maria Walton, Md. Obaidul Haque, Rubayet Shafin, Iqbal Kabir Jahid

Bibliographic record

VenuemedRxiv · 2020
Typepreprint
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineRehabilitationAnxietyTraumatologyDepression (economics)Cross-sectional studyPhysical therapySpinal cord injuryOrthopedic surgeryPsychiatrySpinal cord

Abstract

fetched live from OpenAlex

Abstract Study Design A prospective cross-sectional survey. Objective The study aimed to examine the Knowledge, Attitudes, and Practices (KAP) of people living with Spinal cord injury (SCI) towards COVID-19 and their psychological status during in-patient rehabilitation in Bangladesh. Setting The Centre for the Rehabilitation of the Paralyzed (CRP) and the National Institute of Traumatology and Orthopedic Rehabilitation (NITOR), two tertiary level hospitals in Dhaka, Bangladesh. Methods From July to September 2020, a prospective, cross-sectional survey of SCI subjects, 13-78 years of age, carried out in two SCI rehab centers in Bangladesh. Data has been collected by face to face interview through a pretested, and language validated questionnaire on KAP and Depression, Anxiety, Stress (DASS). Ethical approval and trial registration obtained prospectively. As all the patients were previously living with Spinal cord injury (SCI), therefore, all the patients admitted/ attend SCI rehab centers were considered as SCI positive samples. Results A total of 207 people with SCI responded, 87%were male, and 13% were female with mean age34.18±12.9 years. 33.8% was tetraplegic and 66.2% was paraplegic and 63.8% of them were diagnosed ASIA-A, with motor score 45.38±19.5, sensory score 97.2±52, SpO2 95.07±3.3, and Vo2max 35.7±3.7mL/kg/min. 178 people had at least one health issue. Overall knowledge score was 8.59±2.3 out of 12, depression 11.18±8, anxiety 7.72±5.1, and stress was 9.32±6.7 from a total of 21 scores each. There was a correlation between Knowledge and DASS with age (P<.05); and Knowledge with gender (P<.05), and education (P<.01). Binary logistic regression found a higher association of Knowledge and DASS with gender ( OR 6.6, 6.6, .95, 6.6; P<.01); and young age ( OR .418, P<.01), illiterate ( OR 3.81, P<.01), and rural people ( OR .48, P<.05) with knowledge. A linear relation was noted between depression and anxiety scores ( r .45, P<.01) and stress scores ( r .58, P<.01). A positive attitude was reported for the majority of subjects. SCI Persons reported they and the caregiver followed health advisory in consulting health professionals (65.7%), isolation (63.8%), droplet precaution (87.4%), and hygiene (90.3%). Conclusions During in-patient rehabilitation in Bangladesh, the majority of SCI reported that they had communicated with health professionals and practiced behaviors that would reduce transmission and risk of COVID-19.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.073
GPT teacher head0.429
Teacher spread0.356 · 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 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
Published2020
Admission routes1
Has abstractyes

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