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Record W6982633975

An investigation into the prevalence of Musculoskeletal Disorders (MSDS) within trades’ in high rise property development and the effects of age

2019· other· en· W6982633975 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMiddlesex University Research Repository (Middlesex University Of London) · 2019
Typeother
Languageen
FieldSocial Sciences
TopicHigher Education Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOccupational safety and healthMusculoskeletal disorderWork (physics)Human factors and ergonomicsRisk factorInjury preventionBack painWorkloadStatutory lawAbsenteeismWorking age
DOInot available

Abstract

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Background
\nThe term musculoskeletal disorders (MSDs) covers any injury, damage or disorder of the joints or other tissues in the upper/lower limbs or the back (HSE 2019) Wang (2017) stated that the rate of Workplace MSDs in construction remained higher than in all industries combined; the median days away from work increased from 8 days in 1992 to 13 days in 2014 and that construction workers continue to face a higher risk of MSDs. In the UK the HSE (HSE 2018) have identified a prevalence rate of 2310/100000 workers and 2410/100000 who are skilled trade workers with 469,000 Workers suffering from work-related musculoskeletal disorders (new or long-standing) in 2017/18. The loss of 6.6 million days accounts for 24% of all working days lost due to work-related ill health in the UK.
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\nThe Arthritis and Musculoskeletal Alliance (ARMA 2019) state that the physically demanding work 
\nHelps contribute to the annual cost within the sector of £646m per year. With the UK removing the statutory retirement age, this creates health and safety challenges for older workers and those for whom they work (Barrett &Sargeant 2015).
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\nOkunribido & Wynn (2010) state that age is not an independent risk factor for work-related MSD. Older workers are more susceptible to work-related MSD than younger workers because of decreased functional capacity. Bridger (2008) reports that by the age of 6 the male spinal compression tolerance limit has reduced by 63%.
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\nWithin the built environment in the UK there has been a change in construction methods required to support the increase in high rise, often for residential buildings. This change includes more modular work such as the installation of pre fitted kitchens and bathroom requiring dry lining and less traditional skills such as plastering, bricklaying and joinery.
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\nWith the aim to create a process to help create a sustainable workforce it is best to be able to intervene before a period of absence initially occurs. This means having the tools and a process being able to monitor and engage with the workforce. 
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\nMethod – A small ‘task and finish’ project between one of the UKs largest construction contractors and the University of Greenwich was set up. This study considered also trades required in modern modular techniques rather than previous work based upon traditional trades as well as age. We also identified the most prevalent languages on site and translated the questionnaire into 5 other languages to improve worker engagement. 
\nFollowing meetings with the group Director for Health, Safety and Wellbeing contacts with a suitable site were made. Following a discussion with local management the specific work groups were identified together with the languages spoken on site. It was agreed to use body mapping Thomas et.al. (2018) on an individual basis – looking for specific tingling in fingers that could be associated with hand tools, pain that would go away after a period of rest and persistent pain 
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\nIf workers in a particular job pool share health problems then patterns may emerge using bodymapping that are task related (Hazards, 1998) suggesting that it can
\n•\tEstablish suitability of the individual to work
\n•\tBe an aid to the risk assessment process.
\n•\tPrioritize and support ergonomic improvements 
\n•\tCompare ill health from different work groups
\nKeith and Brophy (2004) suggest that using this technique, together with statistical analysis, it is possible to identify and support associations and establish causal links. Findings can be compared with the literature available and together can be used until hazards are managed to an acceptable level (Mujica, 1992).
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\nThis was supplemented with questions around age, experience, role and recent absence associated with MSDs. This was agreed in advance and included assurances regarding data protection provisions. The contractor made contract with sub-contractors and it was agreed to provide feedback to sub-contractors to feedback to the workforce. 
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\nStaff completed surveys on site on 5 days between the 29th April and 8th May 2019. Researchers were escorted around site by a member of the Primary Contractors ‘Contract Management Team. This was to help enable the researchers to find staff and to ensure researcher safety on site. Approximately 600 people were on site, the survey was looking for 40% participation from the workforce. 
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\nGroups were spoken to whilst in the second half of their shift.
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\nResults
\nIn total 202 staff participated in the survey, around a dozen staff refused and two who participated would not divulge their age. 199 were male and 3 were female. The survey identified 10 nationalities were identified, 24 Trades and Jobs and 41 companies/sub-contractors. Aside from the employees of the main contractor the majority of the remaining staff considered themselves self employed.
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\nWe were unable to obtain both Polish and Russian translations in time for the survey. Of the 202 participants 134 reported that they had pain at that time (66%). The average age was 39 with the lowest age 17 and highest 71. The average length of service in the construction sector was 13.3 years.
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\n27 respondents were supervisors/management with 48% indicating current self-reported pain. 175 were operators with 69% indicating self-reported pain.97 respondents were native English speakers with 70 (72%) reporting self-reported pain. 69 respondents were Rumanian with 67% reporting they were experiencing pain . 12 respondents were Bulgarian with 75% reporting they were experiencing pain. Strangely 19 non English respondents (Ukrainian, Russian speaking Latvians and Poles) only 37% indicated they were experiencing pain. 
\n
\nWhen considering self-reported pain within different trades , 71% of dry liners/labourers were experiencing pain. 70% of Ground workers/Landscapers were experiencing pain, 52% of plumbers were experiencing pain and 100% of Electricians and general labourers are experiencing pain.
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\nIt was noted that amongst the non UK native staff that some nationalities were uncomfortable taking part until their ‘team leader’ had taken part or was happy with the results.
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\nResponses for individual body map charts were transposed on to both activity and age related sheets to compare the different effects of MSDs between cohorts. This work is expected to be completed by the 31st July together with full findings, discussion and recommendations.
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\nReferences
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\nArma, 2019, Musculoskeletal Conditions in the Construction Industry -Report of Roundtable 25 February 2019 - Arthritis and Musculoskeletal Alliance, online. Available at http://arma.uk.net/wp-content/uploads/2019/05/Construction-Roundtable_2019.pdf Accessed 31/05/19
\nBarrett, B. and Sargeant, M., 2015. Working in the UK without a default retirement age: health, safety, and the oldest workers. Industrial law journal, 44(1), pp.75-100.
\nBridger, R., 2008. Introduction to ergonomics. Crc Press.
\nHazards. (1998). Body of evidence-Body mapping can unearth the health hazards in your workplace. Hazards 61 January–March 1998 (online). Available from www.hazards.org/diyresearch/bodymapping.pdf (Accessed 15 March 2012).
\nHSE, 2019, Musculoskeletal disorders, online Available at https://www.hse.gov.uk/MSD/, Accessed 31.05.19.
\nHSE 2018 Work related musculoskeletal disorders in Great Britain (WRMSDs) 2018, ,online. Available at https://www.hse.gov.uk/statistics/causdis/msd.pdf., Accessed 31/05/19 
\nKeith, M.M., & Brophy, J.T. (2004). Participatory mapping of occupational hazards and disease among asbestos-exposed workers from a foundry and insulation complex in Canada. International Journal of Occupational and Environmental Health, 10(2), 144–153.
\nMujica, J. (1992). Coloring the hazards: Risk maps research and education to fight health hazards. American Journal of Industrial Medicine, 22(5), 767–770.
\nOkunribido, O., & Wynn, T (2010) Ageing and work-related Musculoskeletal disorders, online, Available at https://www.hse.gov.uk/research/rrpdf/rr799.pdf Accessed 27/01/18
\nThomas, D., Hare, B. and Cameron, I., 2018. Using body mapping as part of the risk assessment process–a case study. Policy and Practice in Health and Safety, 16(2), pp.224-240.
\nWang, 2017, Work-related musculoskeletal disorders among construction workers in the United States from 1992 to 2014 online, Available at https://oem.bmj.com/content/74/5/374 Accessed

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.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.354
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.011
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
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 head0.017
GPT teacher head0.279
Teacher spread0.262 · 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