ArticleBMC nursing2025
The influence of strategic foresight on quality of healthcare services in the presence of artificial intelligence solutions in Jordan.
Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Development and psychometric evaluation of the artificial intelligence attitude scale for nurses.BMC nursing · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHealthcare organizations are distinguished by intricate systems that undergo continual modifications and unpredictability. This greatly hinders the ability to estimate the exact consequences of any changes accurately. Therefore, scholars prove that strategic foresight enables leaders to anticipate future challenges and possibilities. The utilization of artificial intelligence (AI) in management is on the rise, mostly because of its ability to provide intelligent services, reduce medical errors, and improve operational efficiency. PURPOSE: To examine the impact of strategic foresight on the quality of healthcare services provided by Jordanian nurses in the context of AI solutions in governmental hospitals.
methodA cross-sectional descriptive correlational analysis was conducted. A convenience sampling approach was used in the four selected Jordanian governmental hospitals. The study's target population consisted of nurses. Over three weeks between January and February 2024, 240 self-reported questionnaires were received using a five-point Likert scale, with a response rate of 88.9%. The completed surveys were suitable for analysis using AMOS SPSS v. 26 and SPSS.
resultsSimple linear regression and (Pearson's r) test results showed that (R = .279, R square = 0.078) between strategic foresight and the quality of healthcare services. (R = .543, R square = 0.295) between strategic foresight and the adoption of AI-based solutions. And (R = .432, R square = 0.187) between adopting AI-based solutions and the quality of healthcare services. That reveals a statistically significant, positive correlation coefficient relationship between the variables. In the presence of the mediator, the direct relationship between strategic foresight and healthcare service quality was not statistically significant (b = 0.063, p = .398). The path analysis test indicates a linear relationship between the variables sequentially, and the AI-based solutions completely mediate the relationship between strategic foresight and the quality of healthcare services.
conclusionsA positive and significant correlation between the variables suggests that a simulation-proposed model for a healthcare quality forecasting system, which the researcher built and included in the study recommendations, has to be designed. Therefore, AI-based forecasting systems should incorporate health service quality parameters to facilitate high efficiency and prompt patient demand fulfillment.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.