Evidence map›Paper›PMID 40977796›Full record

ArticleFrontiers in public health2025

Transforming Alzheimer's disease nursing: integrating holistic care, innovative interventions, and evidence-based practices for enhanced patient outcomes.

Honglian Fang, Feng Cui, Ying Zhao, Qian Qian, Angel Yong, Peipei Lan, Chuanying Huang

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Honglian Fang *Department of Geriatric Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
Feng Cui *Shanghai Fuyuan Elderly Care Service Co., Ltd., Shanghai, China.
Ying ZhaoDepartment of Geriatric Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
Qian QianMufushan Community Health Service Center, Nanjing, China.
Angel YongDepartment of Geriatric Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
Peipei LanJiangsu Province Hospital of Chinese Medicine, Nanjing, China.
Chuanying HuangDepartment of Geriatric Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Alzheimer's disease (AD) represents a significant global healthcare challenge with increasing prevalence in aging populations. Traditional care models often focus primarily on symptom management with insufficient attention to holistic patient needs. Objectives: To evaluate the effectiveness of an integrated care approach combining holistic nursing interventions, innovative technologies, and evidence-based practices for enhanced patient outcomes in AD. Methods: A mixed-methods quasi-experimental study involving 248 AD patients across 9 healthcare facilities over 24 months. The intervention group ( Results: Patients receiving integrated care showed significantly improved cognitive stability (ADAS-Cog change: 4.2 ± 3.1 vs. 7.8 ± 3.6 points, Conclusion: The integrated care approach demonstrates significant benefits across multiple domains, supporting its implementation for improving AD patient and caregiver outcomes.

Indexed as

Alzheimer DiseaseDelivery of Health Care, IntegratedEvidence-Based PracticeHolistic NursingAgedAged, 80 and overFemaleHumansMaleMiddle AgedQuality of LifeAlzheimer’s diseasecaregiver supportdigital health technologyholistic nursingintegrated careperson-centered care

Identifiers

PMID40977796
PMCPMC12447846

What OpenQuestion holds

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LicenceCC BY
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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.