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Record W4400975322 · doi:10.2196/59900

The Impact of Digital Technology on the Physical Health of Older Workers: Protocol for a Scoping Review

2024· review· en· W4400975322 on OpenAlexvenueno aff
Jeroen Spijker, Hande Barlın, Diana Alecsandra Grad, Yang Gu, Aija Kļaviņa, Nilüfer Korkmaz Yaylagül, Gunilla Kulla, Eda Orhun, Anna Ševčíková, Brigid Unim, Cristina Maria Tofan

Bibliographic record

VenueJMIR Research Protocols · 2024
Typereview
Languageen
FieldPsychology
TopicTechnostress in Professional Settings
Canadian institutionsnot available
FundersHøgskulen på Vestlandet
KeywordsProtocol (science)Digital healthMedicineGerontologyPsychologyHealth careAlternative medicinePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Digital technologies have penetrated most workplaces. However, it is unclear how such digital technologies affect the physical health of older workers. OBJECTIVE: This scoping review aims to examine and summarize the evidence from scientific literature concerning the impact of digital technology on the physical health of older workers. METHODS: This scoping review will be conducted following recommendations outlined by Levac et al and will adhere to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews) guidelines for reporting. Peer-reviewed papers written in English will be searched in the following databases: MEDLINE, Cochrane, ProQuest, Web of Science, Scopus, APA PsycInfo, and ERIH PLUS. The web-based systematic review platform Covidence will be used to create a data extraction template. It will cover the following items: study and participant characteristics, health measures, digital tool characteristics and usage, and research findings. Following the Population, Concept, and Context (PCC) framework, our review will focus on studies involving older workers aged 50 years or older, any form of digital technology (including teleworking and the use of digital tools at work), and how digital technologies affect physical health (such as vision loss, musculoskeletal disorders, and migraines). Studies that focus only on mental health will be excluded. Study selection based on title and abstract screening (first stage), full-text review (second stage), and data extraction (third stage) will be performed by a group of researchers, whereby each paper will be reviewed by at least 2 people. Any conflict regarding the inclusion or exclusion of a study and the data extraction will be resolved by discussion between the researchers who evaluated the papers; a third researcher will be involved if consensus is not reached. RESULTS: A preliminary search of MEDLINE, Epistemonikos, Cochrane, PROSPERO, and JBI Evidence Synthesis was conducted, and no current or ongoing systematic reviews or scoping reviews on the topic were identified. The results of the study are expected in April 2025. CONCLUSIONS: Our scoping review will seek to provide an overview of the available evidence and identify research gaps regarding the effect of digital technology and the use of digital tools in the work environment on the physical health of older workers. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/59900.

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)0.090
metaresearch head score (Gemma)0.078
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.106
Threshold uncertainty score0.476

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0900.078
Meta-epidemiology (narrow)0.0060.007
Meta-epidemiology (broad)0.0120.016
Bibliometrics0.0150.012
Science and technology studies0.0060.005
Scholarly communication0.0070.010
Open science0.0050.008
Research integrity0.0090.009
Insufficient payload (model declined to judge)0.1060.019

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 head0.500
GPT teacher head0.732
Teacher spread0.233 · 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 designSystematic review
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

Citations4
Published2024
Admission routes1
Has abstractyes

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