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Record W4221018940 · doi:10.1111/jan.15204

The <scp> <b>TARGET</b> </scp> Nurses' health cohort study protocol: <i>T</i> owards <i>a r</i> evolution in <i>ge</i> tting nurses' health <i>t</i> icked

2022· article· en· W4221018940 on OpenAlexaff
Xiaoyan Lv, Yingjuan Cao, Yuxin Li, Yunhong Liu, Rong Li, Xiangyun Guan, Li Li, Junli Li, Shucheng Si, Fuzhong Xue, Xiaokang Ji, Junqiang Zhao, Kim Lam Soh, Patricia M. Davidson

Bibliographic record

VenueJournal of Advanced Nursing · 2022
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineFamily medicinePublic healthCohortNursingChinaCohort studyHealth careGerontology

Abstract

fetched live from OpenAlex

AIM: To evaluate the health status of nurses in China and explore the impact of work-related stress, work environment and lifestyle factors on their health outcomes. DESIGN: The Chinese Nurses' Health Study is a multicentred, prospective cohort study. METHODS: We plan to recruit approximately 80,000 registered nurses aged between 18 and 65 years. Eligible nurses will be introduced to complete a series of web-based questionnaires after obtaining their informed consent. Follow-up questionnaires will be completed at 2-year interval to continuously track subsequent exposures. Health-related indicators will be obtained through self-reporting by nurses and the provincial and national registry platforms such as National Central Cancer Registry. The funding was approved in July 2020 and Research Ethics Committee approval was granted in February 2021. DISCUSSION: The study is the first multicentred prospective cohort study that aims to assess the impact of work-related stress, work environment and lifestyle factors on the health of Chinese nurses. The results of the Chinese Nurses' Health Cohort Study will potentially draw a picture of the current situation of general health and well-being among nurses in China and their health risks. This will be critical in recommending locally tailored strategic preventive measures and policies to reduce health and well-being threats for nurses and potentially general public, thereby promoting the quality of healthcare in China and globally. IMPACT: This study will help to understand the health status and working environment characteristics of Chinese nurses, and provide valuable epidemiological evidence for improving working environment and promoting well-being. The results of this study are potentially of great significance for formulating targeted nursing strategies to promote the nurses' health, nursing quality and patient safety in China and even around the world. CLINICAL TRIAL REGISTRATION NUMBER AND NAME OF TRIAL REGISTER: ChiCTR.org (ID:ChiCTR2100043202), The Nurses' Health Cohort Study of Shandong.

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)0.017
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0090.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.006
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 head0.016
GPT teacher head0.405
Teacher spread0.390 · 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

Citations12
Published2022
Admission routes1
Has abstractyes

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