Evidence map›Paper›PMID 39909418›Full record

ArticleJournal of medical Internet research2025

Technological-Based Interventions in Cancer and Factors Associated With the Use of Mobile Digital Wellness and Health Apps Among Cancer Information Seekers: Cross-Sectional Study.

Ogochukwu Juliet Ezeigwe, Kenechukwu Obumneme Samuel Nwosu, Oladipo Kunle Afolayan, Akpevwe Amanda Ojaruega, Jovita Echere, Manali Desai, Modupe Olajumoke Onigbogi, Olajumoke Ope Oladoyin, Nnenna Chioma Okoye, Pierre Fwelo

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

10 authors.

Ogochukwu Juliet EzeigweDepartment of Epidemiology, The University of Texas Health Science Center, Houston, TX, United States.ORCID 0000-0002-3770-7603
Kenechukwu Obumneme Samuel NwosuDepartment of Epidemiology, The University of Texas Health Science Center, Houston, TX, United States.ORCID 0000-0002-3583-385X
Oladipo Kunle AfolayanDepartment of Biostatistics, The University of Texas Health Science Center, Houston, TX, United States.ORCID 0000-0002-4621-3648
Akpevwe Amanda OjaruegaDepartment of Epidemiology, The University of Texas Health Science Center, Houston, TX, United States.ORCID 0000-0003-2811-2824
Jovita EchereDepartment of Epidemiology, The University of Texas Health Science Center, Houston, TX, United States.ORCID 0000-0002-7947-4537
Manali DesaiDepartment of Epidemiology, The University of Texas Health Science Center, Houston, TX, United States.ORCID 0000-0002-5451-7254
Modupe Olajumoke OnigbogiDepartment of Epidemiology, The University of Texas Health Science Center, Houston, TX, United States.ORCID 0000-0002-7735-3088
Olajumoke Ope OladoyinDepartment of Health Promotion and Behavioral Sciences, The University of Texas Health Science Center, Houston, TX, United States.ORCID 0000-0001-8129-3914
Nnenna Chioma OkoyeDepartment of Pharmaceuticals, Gwarinpa General Hospital, Abuja, Nigeria.ORCID 0009-0006-7920-2511
Pierre FweloDepartment of Epidemiology, The University of Texas Health Science Center, Houston, TX, United States.ORCID 0000-0002-9390-5268

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMobile digital wellness and health apps play a significant role in optimizing health and aiding in cancer management and decision-making.

objectiveThis study aims to identify the factors influencing the use of mobile health and wellness apps among cancer information seekers in the United States.

methodsWe conducted a cross-sectional study using data from the Health Information National Trends Survey. Our analysis focused on 4770 participants who sought cancer information. We performed weighted univariate and multivariable logistic regression to determine the association between the use of health and wellness apps and socioeconomic factors, medical history and conditions, and lifestyle and behavioral factors.

resultsA total of 4770 participants who sought cancer information were included in the final analysis. Of these, 80.9% (n=2705) were health and wellness app users, while 19.1% (n=793) were nonusers. In the final adjusted model, participants with household incomes ≥US $50,000 had 49% higher adjusted odds of using these apps than those with incomes <US $50,000 (adjusted odds ratio [aOR]=1.49, 95% CI 1.02-2.14). College graduates and those with higher educational levels were avid users compared to those with a high school diploma or less (aOR=1.87, 95% CI 1.30-2.67). Internet users had over 3 times the odds of using these apps compared to nonusers (aOR=3.28, 95% CI 1.70-6.33). Participants within the age group 18-34 years were 3.70 times more likely (aOR=3.70, 95% CI 1.90-7.23) to use a health and wellness app compared to participants within the age group of 75 years and older.

conclusionsAge, education, household income, and use of the internet are the major determinants of the adoption of digital health and wellness apps among seekers of cancer information. Hence, public health programs could be directed toward addressing these factors to improve cancer diagnosis, treatment, and management using these apps.

Indexed as

Mobile ApplicationsNeoplasmsAdolescentAdultAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedSocioeconomic FactorsUnited StatesYoung Adultadultbarriercancer informationcancer interventioncancer managementcancer screeningcross-sectional studydecision-makingdigital healthdigital health and wellness appsdigital health engagementdiversityengagementhealth seeking behaviorknowledge seekinglogistic regressionmhealthmobile healthmobile phoneregression analysistelehealthUnited Statesutilizationyoung adult

Identifiers

PMID39909418
PMCPMC11840364

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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.