Evidence map›Paper›PMID 34840697›Full record

ReviewJournal of healthcare engineering2021

Applying the Fuzzy Analytic Hierarchy Process Method to Evaluate Key Indicators of Health Promotion Policies for the Elderly in Taiwan.

Ling-Mei Hsu, Ji-Feng Ding

Open access · hybridAbstract readReview
In one paragraph

Review in Journal of healthcare engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.5field-weighted citation impact, top 15% 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, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

2 authors at 1 institution in 1 country.

Ling-Mei HsuProgram in Business and Operations Management, Chang Jung Christian University, Tainan City 71101, Taiwan.ORCID 0000-0003-4318-3479
Ji-Feng DingDepartment of Aviation and Maritime Transportation Management, Chang Jung Christian University, Tainan City 71101, Taiwan.ORCID 0000-0001-5268-3024
Chang Jung Christian University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Investigation of the key indicators of health promotion policies for an aging society can shed light on the priority of the government's health promotion efforts. This study applied the fuzzy analytic hierarchy process (AHP) method in an empirical analysis of the key indicators of the health promotion policies for Taiwan's aging society. Based on a review of the literature and expert interviews, this paper first conducted a preliminary study and evaluation of major factors affecting health promotion policies and found 4 major evaluation aspects and 16 evaluation indicators. After employing an AHP expert questionnaire in an empirical investigation, the following findings were made: (1) "healthy living" was the most important evaluation aspect for Taiwan's health promotion policies for its aging society. (2) The six leading key indicators of health promotion policies were "promotion of personal health awareness and behavior," "promotion of home medical services," "guaranteeing the economic security of the elderly," "planning a family caregiver support service system," "well-planned health promotion plans for the elderly," and "training long-term care service personnel and providing professional medical care." Following discussion, recommendations concerning these six key indicators are made as a reference for future evaluation of health promotion policies for an aging society.

Indexed as

Analytic Hierarchy ProcessHealth PolicyAgedAgingHealth PromotionHumansTaiwan

Identifiers

PMID34840697
PMCPMC8616644
OpenAlexW3212944863

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.