Evidence map›Paper›PMID 31435177›Full record

ArticleWorld journal of gastroenterology2019

Inflammatory bowel disease patient profiles are related to specific information needs: A nationwide survey.

Saleh Daher, Tawfik Khoury, Ariel Benson, John R Walker, Oded Hammerman, Ron Kedem, Timna Naftali, Rami Eliakim, Ofer Ben-Bassat, Charles N Bernstein and 1 more

Abstract read
In one paragraph

Article in World journal of gastroenterology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

11 authors.

Saleh DaherInstitute of Gastroenterology and Liver Diseases, Hadassah-Hebrew University Medical Center, Jerusalem 91120, Israel. saleh@hadassah.org.il.
Tawfik KhouryInstitute of Gastroenterology and Liver Diseases, Hadassah-Hebrew University Medical Center, Jerusalem 91120, Israel.
Ariel BensonInstitute of Gastroenterology and Liver Diseases, Hadassah-Hebrew University Medical Center, Jerusalem 91120, Israel.
John R WalkerIBD Clinical and Research Centre, University of Manitoba, Winnipeg, MB R3E3P4, Canada.
Oded HammermanInstitute of Gastroenterology and Liver Diseases, Hadassah-Hebrew University Medical Center, Jerusalem 91120, Israel.
Ron KedemResearch Branch, IDF Medical Corps, Tel-Hashomer, Ramat Gan 52630, Israel.
Timna NaftaliInstitute of Gastroenterology, Meir Medical Center, Kfar-saba 4428164, Israel.
Rami EliakimSackler School of Medicine, Tel-Aviv University, Tel-Aviv 6997801, Israel.
Ofer Ben-BassatInstitute of Gastroenterology, Rabin Medical Center, Petach-Tikva 49100, Israel.
Charles N BernsteinIBD Clinical and Research Centre, University of Manitoba, Winnipeg, MB R3E3P4, Canada.
Eran IsraeliInstitute of Gastroenterology and Liver Diseases, Hadassah-Hebrew University Medical Center, Jerusalem 91120, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInflammatory bowel diseases (IBD) is a heterogenous, lifelong disease, with an unpredictable and potentially progressive course, that may impose negative psychosocial impact on patients. While informed patients with chronic illness have improved adherence and outcomes, previous research showed that the majority of IBD patients receive insufficient information regarding their disease. The large heterogeneity of IBD and the wide range of information topics makes a one-size fits all knowledge resource overwhelming and cumbersome. We hypothesized that different patient profiles may have different and specific information needs, the identification of which will allow building personalized computer-based information resources in the future.

aimTo evaluate the scope of disease-related knowledge among IBD patients and determine whether different patient profiles drive unique information needs.

methodsWe conducted a nationwide survey addressing hospital-based IBD clinics. A Total of 571 patients completed a 28-item questionnaire, rating the amount of information received at time of diagnosis and the importance of information, as perceived by participants, for a newly diagnosed patient, and for the participants themselves, at current time. We performed an exploratory factor analysis of the crude responses aiming to create a number of representative knowledge domains (factors), and analyzed the responses of a set of 15 real-life patient profiles generated by the study team.

resultsParticipants gave low ratings for the amount of information received at disease onset (averaging 0.9/5) and high ratings for importance, both for the newly diagnosed patients (mean 4.2/5) and for the participants themselves at current time (mean 3.5/5). Factor analysis grouped responses into six information-domains. The responses of selected profiles, compared with the rest of the participants, yielded significant associations (defined as a difference in rating of > 0.5 points with a

conclusionWe demonstrate unmet patient information needs. Analysis of various patient profiles revealed associations with specific information topics, paving the way for building patient-tailored information resources.

Indexed as

Health Knowledge, Attitudes, PracticeHealth Services Needs and DemandInformation Seeking BehaviorAdaptation, PsychologicalAdultColitis, UlcerativeCrohn DiseaseHumansIsraelMiddle AgedPatient Education as TopicQuality of LifeSeverity of Illness IndexSurveys and QuestionnairesYoung AdultInflammatory bowel diseasesInformation needsKnowledge resourcesPatient educationPatient profiles

Identifiers

PMID31435177
PMCPMC6700696

What OpenQuestion holds

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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.