Evidence map›Paper›PMID 38720750›Full record

ArticleHeliyon2024

Comparing the efficacy of single-skill and multiple-skill simulation scenarios in advancing clinical nursing competency.

Sami Alyateem, Majeda Al-Ruzzieh, Bahaa Shtayeh, Aladeen Alloubani

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Sami AlyateemKing Hussein Cancer Center, Amman, Jordan.
Majeda Al-RuzziehKing Hussein Cancer Center, Amman, Jordan.
Bahaa ShtayehKing Hussein Cancer Center, Amman, Jordan.
Aladeen AlloubaniKing Hussein Cancer Center, Amman, Jordan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: This study aims to compare the effectiveness of single-skill and multiple skills patient care simulation scenarios in enhancing nursing competency and to evaluate nurses' perceptions of these different simulation scenarios. Methods: A mixed-method design was used. In the quantitative part, 130 newly hired nurses with less than one year of experience participated in this study. For the qualitative part, a subset of 26 of these nurses was selected for in-depth interviews until data saturation was achieved. The study was conducted in the simulation-based learning (SBL) lab in a specialized Jordan cancer center. Data collection took place between June 2022 and March 2023. Results: A significant difference was found in the IV skill between single and multiple skills scenarios; the mean score for the single-skill group was 44.42 (SD = 3.85), the mean score for the multiple-skill group was 45.63 (SD = 2.26) (P = 0.014). Moreover, a significant difference was found between the pre-and post-test scores for single-skill and multiple-skill groups. The mean score for the medication skill scenario pre-intervention single group was (M = 23.90, SD = 5.33); however, the score was increased post-intervention (M = 45.38, SD = 3.33), (P = <.001). Furthermore, the mean score was raised in the multiple skills medication scenario from (M = 22.92, SD = 5.44) to (M = 45.72, SD = 2.75), (<.001). Conclusion: Participants in both groups reported similar findings regarding physical exhaustion, scenario management, and overall satisfaction with the simulation experience. Loss of concentration and memory was reported more with multiple competencies simulation scenarios; this might indicate that this scenario has more cognitive load than the Single Competency Scenario.

Indexed as

Clinical nursing competencyNursesPerceptionScenariosSimulation-based learning

Identifiers

PMID38720750
PMCPMC11076845

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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.