Evidence map›Paper›PMID 42423238›Full record

ArticlePLOS digital health2026

Evaluating the quality, reliability and readability of digital and artificial intelligence resources for adults with cancer who have significant caregiving responsibilities for children.

Rohan Anand, Cherith J Semple, Lisa Strutt, Sally Paul, Jeffrey R Hanna

Abstract read
In one paragraph

Article in PLOS digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Rohan AnandInstitute of Nursing and Health Research, Ulster University, Belfast, United Kingdom.ORCID https://orcid.org/0000-0002-1957-5336
Cherith J SempleInstitute of Nursing and Health Research, Ulster University, Belfast, United Kingdom.ORCID https://orcid.org/0000-0002-4560-7637
Lisa StruttLisa Strutt Leadership and Coaching, Belfast, United Kingdom.ORCID https://orcid.org/0009-0000-9825-6482
Sally PaulDepartment of Social Work and Social Policy, University of Strathclyde, Glasgow, United Kingdom.ORCID https://orcid.org/0000-0003-1690-8411
Jeffrey R HannaInstitute of Nursing and Health Research, Ulster University, Belfast, United Kingdom.ORCID https://orcid.org/0000-0002-8218-5939

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Families often report searching the internet for guidance on how best to support children when a significant adult has cancer. This study aimed to identify and evaluate the quality, reliability, readability and content of websites, videos, and artificial intelligence (AI) resources available to adults with cancer who have caregiving responsibilities for children. Online platforms were searched using 10 phrases across Google web, YouTube, TikTok and four AI platforms. The mDISCERN instrument assessed reliability and quality, GQS assessed overall quality, and the NHS Medical Document Readability Tool assessed readability. Quantitative differences between sources were determined using pairwise analysis. Google web had significantly higher quality and reliability compared with AI and TikTok sources, with mean mDISCERN and GQS scores of 3.74 and 3.72, respectively. AI-generated resources showed lower mean mDISCERN and GQS scores of 2.77 (P < .05) and 2.32 (P < .05), respectively. TikTok videos had lower scores of 2.73 (P < .05) for mDISCERN and 2.49 (P < .05) for GQS. Estimated reading time was significantly longer (P < .05) for Google web (11:45mins) compared to AI (02:09mins). However, reading age did not differ (P = .31) at 15.09 years and 15.17 years respectively. There was a lack of accessible and inclusive resources for non-nuclear families, adults with neurodivergent children, culturally and ethnically diverse populations and families at end of life. Although Google web resources demonstrated higher overall quality and reliability, written resources across platforms often exceeded recommended reading levels, which may represent a significant health equity concern for individuals with lower health literacy and families experiencing deprivation. AI presents an opportunity whereby a single high-quality and evidence-based resource can be rapidly adapted into multiple formats, reading levels, languages and be culturally relevant. Future resources may benefit from co-production using a trusted, regulated, and centralised information hub, with supportive collaboration between health and social care professionals and technology providers.

Identifiers

PMID42423238
PMCPMC13347835

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.