ArticleBMC cancer2021
Using patients' own knowledge of early sensations and symptoms to develop an interactive, individualized e-questionnaire to facilitate early diagnosis of lung cancer.
Article in BMC cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 3 citations in OpenAlex.
- Predicting lung cancer stage at diagnosis based on self-reported symptoms and background factors using machine learning models.Scientific reports · 2026Article
- Multiplex plasma protein assays as a diagnostic tool for lung cancer.Cancer science · 2024Article
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Authors and funding
8 authors at 7 institutions in 3 countries.
Funding
Abstract
backgroundOne reason for the often late diagnosis of lung cancer (LC) may be that potentially-indicative sensations and symptoms are often diffuse, and may not be considered serious or urgent, making their interpretation complicated. However, with only a few exceptions, efforts to use people's own in-depth knowledge about prodromal bodily experiences has been a missing link in efforts to facilitate early LC diagnosis. In this study, we describe and discuss facilitators and challenges in our process of developing and initial testing an interactive, self-completion e-questionnaire based on patient descriptions of experienced prodromal sensations and symptoms, to support early identification of lung cancer (LC).
methodsE-questionnaire items were derived from in-depth, detailed explorative interviews with individuals undergoing investigation for suspected LC. The descriptors of sensations/symptoms and the background items obtained were the basis for developing an interactive, individualized instrument, PEX-LC, which was refined for usability through think-aloud and other interviews with patients, members of the public, and clinical staff.
resultsMajor challenges in the process of developing PEX-LC related to collaboration among many actors, and design/user interface problems including technical issues. Most problems identified through the think-aloud interviews related to design/user interface problems and technical issues rather than content, for example we re-ordered questions to be in line with patients' chronological, rather than retrospective, descriptions of their experiences. PEX-LC was developed into a final e-questionnaire on a touch-screen smart tablet with one background module covering sociodemographic characteristics, 10 interactive, individualized modules covering early sensations and symptoms, and a 12th assessing current symptoms.
conclusionsClose collaboration with patients throughout the process was intrinsic for developing PEX-LC. Similarly, we recognized the extent to which clinicians and technical experts were also important in this process. Similar endeavors should assure all necessary competence is included in the core research team, to facilitate timely progress. Our experiences developing PEX-LC combined with new empirical research suggest that this individualized, interactive e-questionnaire, developed through systematizing patients' own formulations of their prodromal symptom experiences, is both feasible for use and has potential value in the intended group.
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Registered trials
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.