Evidence map›Paper›PMID 39702101›Full record

ArticleBMC nursing2024

Community health assessment of needs and continuous empowerment (CHANCE): a quantitative cross-sectional survey targeting primary health care nurses in Lebanon.

Gladys Honein-AbouHaidar, Reem Hoteit, Sarah Chehayeb, Nuhad Dumit, Tamar Avedissian, Bahia Abdallah, Randa Hamadeh

Abstract read
In one paragraph

Article in BMC nursing, 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
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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

7 authors.

Gladys Honein-AbouHaidarHariri School of Nursing, American University of Beirut, Bliss Street, Riad El Solh 1107, PO Box: 11 0236, Beirut, 1107 2020, Lebanon. gh30@aub.edu.lb.
Reem HoteitHariri School of Nursing, American University of Beirut, Bliss Street, Riad El Solh 1107, PO Box: 11 0236, Beirut, 1107 2020, Lebanon.
Sarah ChehayebIngram School of Nursing, McGill University, 680 Sherbrooke West, Montreal, Canada.
Nuhad DumitHariri School of Nursing, American University of Beirut, Bliss Street, Riad El Solh 1107, PO Box: 11 0236, Beirut, 1107 2020, Lebanon.
Tamar AvedissianHariri School of Nursing, American University of Beirut, Bliss Street, Riad El Solh 1107, PO Box: 11 0236, Beirut, 1107 2020, Lebanon.
Bahia AbdallahAlice Ramez Chagoury School of Nursing, Lebanese American University, PO Box: 36, Byblos, Lebanon.
Randa HamadehMinistry of Public Health, Beirut, Lebanon.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrimary Health Care (PHC) is the cornerstone of any healthcare system, with nurses forming the largest workforce involved in care. This study aimed to assess the current use of core competencies among community-based nurses, identify their learning needs, and assess factors associated with training needs within PHC centers.

methodsA quantitative cross-sectional survey design was used, targeting community health nurses working within primary healthcare centers. Data were collected using a survey instrument adapted from the Canadian Community Health Nurses' Standards of Practice and informed by a validated tool, then piloted for clarity in the Lebanese context. Data were collected between September and November 2018. Mean, standard deviation (SD), frequency, and percentage data were computed for descriptive purposes. The generalized estimating equation (GEE) was used to identify the factors associated with nurses' training needs clustered within centers. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using logistic GEE regression models that accounted for cluster effects.

resultsThe total number of PHCs that agreed to participate was 206, of which 173 returned completed surveys. Given that we do not have an accurate number of the population of nurses working in those centers, we assumed that there would be two nurses in each PHC. Thus, for a total of 251 surveys completed by nurses, the response rate is estimated to be 61%. Of the 173 surveys, 139 were included in the final analysis after deleting those that were incomplete. Descriptive results showed that nurses were competent in providing continuous care (60.0%), electronic technology use (55.08%), and clinical nursing assessment (54.01%). They reported a need for more training on community health promotion (65.12%), patient-centered care (PCC) (58.30%), and patient self-management of chronic diseases (52.0%). In comparison to nurses working in accredited centers, nurses working in centers in the process of becoming accredited required three times more training to become competent in PCC (OR = 3.39, 95% CI: 1.26-9.31, p = 0.016). Registered nurses required three times less training in PCC than senior/head nurses (OR = 0.30, 95% CI: 0.11-0.80, p = 0.016). Education level was statistically significantly associated with most training needs. Nurses with Baccalaureate and Technique Superior degrees needed six times more training (OR = 6.07, 95% CI: 1.81-31.16, p = 0.031) than those with a bachelor's or master's degree in nursing.

conclusionThis study provided a baseline assessment for the competencies that nurses reported implementing and those that they requested more training on. Future steps would be to develop interventions to empower nurses with the competencies they requested as priorities and to conduct a post intervention assessment to test the effect of the training on nursing adoption of those skills.

Indexed as

Community health nursesLearning needsNursing competenciesPatient centered carePrimary health careSelf-management

Identifiers

PMID39702101
PMCPMC11656780

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

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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.