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Record W4404642521 · doi:10.1186/s13063-024-08622-8

Behavioral risk assessment of work-related musculoskeletal disorders among workers of petrochemical industries: protocol of a mixed method study

2024· article· en· W4404642521 on OpenAlexaboutno aff
Zohreh Moradi, Sedigheh Sadat Tavafian, Fazlollah Ahmadi, Omran Ahmadi

Bibliographic record

VenueTrials · 2024
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
FundersFakultet Medicinskih Nauka, Univerziteta U KragujevcuTarbiat Modares University
KeywordsAbsenteeismMedicineMusculoskeletal disorderIntervention (counseling)Work-related musculoskeletal disordersResearch designQualitative researchWork (physics)Human factors and ergonomicsEnvironmental healthOccupational safety and healthPhysical therapyNursingPoison controlPsychologyEngineering

Abstract

fetched live from OpenAlex

BACKGROUND: Musculoskeletal disorders (MSDs) are one of the most common occupational diseases and the main cause of disability worldwide. Work-related musculoskeletal disorders (WMSDs) are one of the common health risks and the most important cause of absenteeism due to disability in various industries, including the petrochemical industry, in developed and developing countries. These disorders have important social economic, and significant financial consequences due to direct and hidden costs. Health behaviors play a role in both creating and preventing musculoskeletal disorders in employees. Therefore, by identifying the influencing factors on these behaviors, it is possible to strengthen and improve the preventive behaviors of musculoskeletal disorders through educational intervention programs. This study aims to assess the behavioral risk of work-related musculoskeletal disorders, and design and implement an educational intervention to teach effective behaviors in the prevention of musculoskeletal disorders in petrochemical industry workers. METHODS: This study is a mixed-method study implemented in four stages involving the qualitative study, the design and evaluation of an instrument, the design of an experimental randomized clinical trial, and the psychometric evaluation of the instrument and the evaluation of the program. The research community consists of employees working in the petrochemical industry. The volume of samples in the qualitative study with the purposeful sampling method, in the instrument design stage based on the available sampling method, and also in the experimental study, the samples are employees suffering from work-related musculoskeletal disorders, who were selected based on a simple random method from among the employees of the petrochemical industry. Then they will be divided into intervention and control groups. The instruments of this research include a demographic questionnaire, a researcher-made questionnaire for measuring behavior, and two auxiliary instruments including the visual analog scale (VAS) and the Quebec Disability Scale. Evaluation is done in 4 stages: pre-test, immediately, 3, and 6 months after the intervention of both groups. The obtained data will be analyzed using SPSS software. DISCUSSION: Musculoskeletal disorders related (WMSDs) to work can harm employees' health in various industries, including the petrochemical industry. This study attempts to evaluate the behavioral risk of work-related musculoskeletal disorders among petrochemical industry workers and design and implement an appropriate educational intervention program. TRIAL REGISTRATION: Iranian Registry of Clinical Trial (IRCT20240321061346N1). Registered on 2024-04-10. Ethics Status: Ethics code: IR.MODARES.REC.1402.251.

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)0.041
metaresearch head score (Gemma)0.022
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: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.041
Threshold uncertainty score0.216

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0410.022
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0040.003
Science and technology studies0.0040.002
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0200.003

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 head0.053
GPT teacher head0.463
Teacher spread0.410 · 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
GenreProtocol

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
Published2024
Admission routes1
Has abstractyes

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