Evidence map›Paper›PMID 36726482›Full record

ArticleJournal of multidisciplinary healthcare2023

Investigation on Nurses' Willingness to "Internet + Nursing Service" and Analysis of Influencing Factors.

Fei Tian, Zuyang Xi, Ling Ai, Xiaojing Zhou, Zhaohui Zhang, Jinglan Liu, Yuanyuan Mi, Shengmin Gui, Chaxiang Li, Min Liu

Abstract read
In one paragraph

Article in Journal of multidisciplinary healthcare, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Fei Tian *The First College of Clinical Medical Science, China Three Gorges University, Teaching and Research Section of Clinical Nursing, Yichang, People's Republic of China.
Zuyang Xi *The First College of Clinical Medical Science, China Three Gorges University, Teaching and Research Section of Clinical Nursing, Yichang, People's Republic of China.
Ling AiNursing Department, China Xingshan County People's Hospital, Xingshan, People's Republic of China.
Xiaojing ZhouThe First College of Clinical Medical Science, China Three Gorges University, Teaching and Research Section of Clinical Nursing, Yichang, People's Republic of China.
Zhaohui Zhang *The First College of Clinical Medical Science, China Three Gorges University, Teaching and Research Section of Clinical Nursing, Yichang, People's Republic of China.
Jinglan LiuThe First College of Clinical Medical Science, China Three Gorges University, Teaching and Research Section of Clinical Nursing, Yichang, People's Republic of China.
Yuanyuan MiDepartment of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
Shengmin GuiThe First College of Clinical Medical Science, China Three Gorges University, Teaching and Research Section of Clinical Nursing, Yichang, People's Republic of China.
Chaxiang LiThe First College of Clinical Medical Science, China Three Gorges University, Teaching and Research Section of Clinical Nursing, Yichang, People's Republic of China.
Min LiuThe First College of Clinical Medical Science, China Three Gorges University, Teaching and Research Section of Clinical Nursing, Yichang, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To investigate the willingness of nurses in Yichang to participate in "Internet plus nursing services" and analyze the influencing factors in order to provide reference for the implementation of "Internet plus nursing services". Methods: Using the "Internet plus Nursing Service" questionnaire, a cross-sectional survey was conducted among 1447 nurses in Yichang by convenience sampling from July to September in 2022, and the related influencing factors were analyzed. The questionnaire was composed of two parts: the demographic characteristics and the questionnaire of nurses' willingness to participate in "Internet plus nursing service", including 4 dimensions: awareness, promoting factors, concern factors and training needs. Likert 5-point scoring method was used for scoring. Binary logistic regression was used to screen the variables, and the ROC curve and Nomogram risk prediction model were drawn. Results: A total of 1233 valid questionnaires were collected. It shows that 76.07% of nurses in Yichang are willing to participate in "Internet plus nursing services". Among them, education background, specialist nurses, awareness, promotion factors, concerns and training needs are the independent influencing factors (all P < 0.05). The area under the ROC curve (AUC) of the prediction model is 0.802, and the consistency index (c-index) of nomogram is 0.800. The average absolute error of internal calibration is 0.014, and the model has good accuracy and discrimination. Conclusion: Nurses in Yichang have a high willingness to participate in "Internet plus nursing services", a low awareness of the program and a high demand for relevant professional training. It is suggested that the government and hospitals should strengthen the publicity of "Internet plus nursing services", improve relevant laws and regulations and strengthen the construction of specialist nurses' team, so as to provide a good practice environment for nurses' door-to-door service.

Indexed as

influencing factorsinternet plus nursing serviceswillingness

Identifiers

PMID36726482
PMCPMC9885965

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.