Evidence map›Paper›PMID 27763525›Full record

ReviewInternational journal of environmental research and public health2016

The Need for a Definition of Big Data for Nursing Science: A Case Study of Disaster Preparedness.

Ho Ting Wong, Vico Chung Lim Chiang, Kup Sze Choi, Alice Yuen Loke

Open access · goldAbstract readReview
In one paragraph

Review in International journal of environmental research and public health, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 12% of its field
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

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.

  1. AI applications in disaster governance with health approach: A scoping review.Archives of public health = Archives belges de sante publique · 2025
    Pooled it
  2. Article
  3. Nursing Intervention Practices for Smoking Cessation: A Large Survey in Hong Kong.International journal of environmental research and public health · 2018
    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

4 authors at 1 institution in 3 countries.

Ho Ting WongDisaster Nursing Task Force, School of Nursing, the Hong Kong Polytechnic University, Hong Kong, China. frankwong@connect.hku.hk.
Vico Chung Lim ChiangDisaster Nursing Task Force, School of Nursing, the Hong Kong Polytechnic University, Hong Kong, China. vico.chiang@polyu.edu.hk.
Kup Sze ChoiSchool of Nursing, the Hong Kong Polytechnic University, Hong Kong, China. thomasks.choi@polyu.edu.hk.
Alice Yuen LokeDisaster Nursing Task Force, School of Nursing, the Hong Kong Polytechnic University, Hong Kong, China. alice.yuen.loke@polyu.edu.hk.
Hong Kong Polytechnic University · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid development of technology has made enormous volumes of data available and achievable anytime and anywhere around the world. Data scientists call this change a data era and have introduced the term "Big Data", which has drawn the attention of nursing scholars. Nevertheless, the concept of Big Data is quite fuzzy and there is no agreement on its definition among researchers of different disciplines. Without a clear consensus on this issue, nursing scholars who are relatively new to the concept may consider Big Data to be merely a dataset of a bigger size. Having a suitable definition for nurse researchers in their context of research and practice is essential for the advancement of nursing research. In view of the need for a better understanding on what Big Data is, the aim in this paper is to explore and discuss the concept. Furthermore, an example of a Big Data research study on disaster nursing preparedness involving six million patient records is used for discussion. The example demonstrates that a Big Data analysis can be conducted from many more perspectives than would be possible in traditional sampling, and is superior to traditional sampling. Experience gained from the process of using Big Data in this study will shed light on future opportunities for conducting evidence-based nursing research to achieve competence in disaster nursing.

Indexed as

Disaster PlanningForecastingHumansNurse's RoleNursingNursing ResearchBig Datadisaster preparednessresearch method

Identifiers

PMID27763525
PMCPMC5086754
OpenAlexW2537233511

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.