Evidence map›Paper›PMID 37655786›Full record

ArticleJMIR aging2023

Examining the Impact of Selected Sociodemographic Factors and Cancer-Related Fatalistic Beliefs on Patient Engagement via Health Information Technology Among Older Adults: Cross-Sectional Analysis.

Maryum Zaidi, Priscilla Gazarian, Heather Mattie, Lisa Kennedy Sheldon, C Ann Gakumo

Open access · goldAbstract read
In one paragraph

Article in JMIR aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.4field-weighted citation impact, top 17% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Machine Learning-Based Prediction of Binge Drinking among Adults in the United State: Analysis of the 2022 Health Information National Trends Survey.Proceedings of the 2024 9th International Conference on Mathematics and Artificial Intelligence · 2024
    Article
  3. Review
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 at 5 institutions in 1 country.

Maryum ZaidiSolomont School of Nursing, Zuckerberg College of Health Sciences, University of Massachusetts Lowell, Lowell, MA, United States.ORCID https://orcid.org/0000-0002-6417-7257
Priscilla GazarianManning College of Nursing & Health Sciences, University of Massachusetts Boston, Boston, MA, United States.ORCID https://orcid.org/0000-0002-4928-293X
Heather MattieHarvard T H Chan School of Public Health, Boston, MA, United States.ORCID https://orcid.org/0000-0002-1263-2537
Lisa Kennedy SheldonSt Joseph Hospital, New Hampshire, NH, United States.ORCID https://orcid.org/0000-0002-5958-8529
C Ann GakumoCollege of Nursing, University of Cincinnati, Cincinnati, OH, United States.ORCID https://orcid.org/0000-0002-5231-6862
Boston University · USHarvard University · USSt. Joseph Hospital · USUniversity of Cincinnati Medical Center · USUniversity of Massachusetts Lowell · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite the role of health information technology (HIT) in patient engagement processes and government incentives for HIT development, research regarding HIT is lacking among older adults with a high burden of chronic diseases such as cancer. This study examines the role of selected sociodemographic factors and cancer-related fatalistic beliefs on patient engagement expressed through HIT use for patient engagement in adults aged ≥65 years. We controlled for cancer diagnosis to account for its potential influence on patient engagement.

objectiveThis study has 2 aims: to investigate the role of sociodemographic factors such as race, education, poverty index, and psychosocial factors of cancer fatalistic beliefs in accessing and using HIT in older adults and to examine the association between access and use of HIT in the self-management domain of patient activation that serves as a precursor to patient engagement.

methodsThis is a secondary data analysis of a subset of the Health Information National Trend Survey (Health Information National Trend Survey 4, cycle 3). The subset included individuals aged ≥65 years with and without a cancer diagnosis. The relationships between access to and use of HIT to several sociodemographic variables and psychosocial factors of fatalistic beliefs were analyzed. Logistic and linear regression models were fit to study these associations.

resultsThis study included 180 individuals aged ≥65 years with a cancer diagnosis and 398 without a diagnosis. This analysis indicated that having less than a college education level (P=<.001), being an individual from an ethnic and minority group (P=<.001), and living in poverty (P=.001) were significantly associated with decreased access to HIT. Reduced HIT use was associated with less than a college education (P=.001) and poverty(P=.02). This analysis also indicated that fatalistic beliefs about cancer were significantly associated with lower HIT use (P=.03). Specifically, a 1-point increase in the cancer fatalistic belief score was associated with a 36% decrease in HIT use. We found that controlling for cancer diagnosis did not affect the outcomes for sociodemographic variables or fatalistic beliefs about cancer. However, patients with access to HIT had a self-management domain of patient activation (SMD) score of 0.21 points higher (P=.003) compared with patients who did not have access. SMD score was higher by 0.28 points (P=.002) for individuals who used HIT and 0.14 points higher (P=.04) who had a prior diagnosis of cancer.

conclusionsSociodemographic factors (education, race, poverty, and cancer fatalistic beliefs) impact HIT access and use in older adults, regardless of prior cancer diagnosis. Among older adults, HIT users report higher self-management, which is essential for patient activation and engagement.

Indexed as

digital healthhealth information technologymobile phoneolder adultspatient portalsself-management

Identifiers

PMID37655786
PMCPMC10625088
OpenAlexW4311620994

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.