Evidence map›Paper›PMID 35629085›Full record

ArticleJournal of personalized medicine2022

Predictors of Colorectal Cancer Screening among Average and High-Risk Saudis Population.

Fuad H Abuadas, Abdalkarem F Alsharari, Mohammad H Abuadas

Open access · goldAbstract read
In one paragraph

Article in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.6field-weighted citation impact, top 31% 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

7 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Review
  3. Role of Nanoformulations in the Treatment of Lung Cancer.Recent patents on nanotechnology · 2025
    Review
  4. Article
  5. Review
  6. Advances in Personalized Nursing Care.Journal of personalized medicine · 2023
    Article
  7. 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

3 authors at 2 institutions in 1 country.

Fuad H AbuadasNursing Department, College of Applied Medical Sciences, Jouf University, Sakaka 72388, Saudi Arabia.ORCID 0000-0002-4880-0862
Abdalkarem F AlsharariNursing Department, College of Applied Medical Sciences, Jouf University, Sakaka 72388, Saudi Arabia.
Mohammad H AbuadasFaculty of Nursing, King Khalid University, Khamis Mushait 62529, Saudi Arabia.ORCID 0000-0002-2739-7314
Jouf University · SAKing Khalid University · SA

Funding

Al Jouf University DSR 451
6 · The paper itself

Abstract

Colorectal cancer (CRC) screening intention is one of the most important elements influencing the longstanding effectiveness of community-based CRC screening programs. The primary purpose of this study is to generate and validate a predictive screening model that investigates the influence of Saudis’ demographics, CRC knowledge, and beliefs on intention to undergo CRC screening via fecal occult blood test (FOBT). Convenience sampling was used to recruit 600 average and high-risk participants from multiple primary health care centers in three major Saudi provinces. A valid and reliable self-administered online survey was used to collect data from March 2021 to October 2021. The final modified screening prediction model explained 57.35% of the variance in screening intention. Intention to screen was significantly influenced by seven factors in which the perceived barriers factor (β = −0.55, p < 0.001) was the strongest predictor. Those who had lower perceived barriers and greater levels of knowledge (β = 0.36, p < 0.001), health motivation (β = 0.35, p < 0.001), perceived benefits of screening (β = 0.35, p < 0.001), severity (β = 0.29, p < 0.001), and susceptibility (β = 0.28, p < 0.001) were more likely to become involved in screening practices. Health care practitioners and various media forms could benefit from the prediction model playing a significant role in raising awareness, reducing perceived barriers, and enhancing Saudi screening rates.

Indexed as

cancer preventioncolorectal cancerprediction modelscreening practicesscreening program

Identifiers

PMID35629085
PMCPMC9144519
OpenAlexW4224237549

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.