Evidence map›Paper›PMID 26003189›Full record

Trial reportPathology oncology research : POR2015

Characterization of Individuals Taking Part in Low Dose Computed Tomography (LDCT) Screening Program.

Mariann Moizs, Gábor Bajzik, Zsuzsanna Lelovics, János Strausz, Marianna Rakvács, Péter Zádori, Árpád Kovács, Imre Repa

Abstract readClinical Trial
PubMed Publisher
In one paragraph

Trial report in Pathology oncology research : POR, 2015. 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. Review
  2. Lung cancer screening: targeting the hard to reach-a review.Translational lung cancer research · 2021
    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

8 authors.

Mariann Moizs"Moritz Kaposi" General Hospital, H-7400, Kaposvár, Tallián Gyula u. 20-32, Kaposvár, Hungary.
Gábor Bajzik
Zsuzsanna Lelovics
János Strausz
Marianna Rakvács
Péter Zádori
Árpád Kovács
Imre Repa

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

unlabelledIn the past years the participation rate in conventional voluntary x-ray lung screening has been around 22 % in Somogy County in Hungary. Due to the high morbidity and mortality rates of lung cancer, low participation rate of the high risk individuals on the screening is a primary question in Hungary. To obtain an effectively high level of participation in our ongoing low dose CT screening program, we had to emphasize the benefits of participation for the targeted individuals. As a first step, our aim was to gather information on the aspects affecting the individuals' will for participation. We used the most accessible source of information: individuals over the age of 50, who attended the conventional voluntary lung screening, were approached to fill a questionnaire on their habits relating to smoking, health issues and their prior participation of lung screening. 1080 adults anonymously completed the questionnaire. Analyzing the results, beside other findings, we found a unique variable factor, which altered negatively the compliance for the screening: older individuals, who started participating in the screening in obligation to the health regulations, took part in the voluntary screening programs at a significantly lower rate. Our findings led us to better understanding the complexity of decision making affecting the individual's participation and attitudes toward health issues.

trial registrationIG/03833/2012.

Indexed as

Early Detection of CancerFemaleHumansHungaryLungLung NeoplasmsMaleMiddle AgedSmokingSurveys and QuestionnairesTomography, X-Ray Computed

Identifiers

What OpenQuestion holds

Textmetadata
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.