Evidence map›Paper›PMID 38012565›Full record

ArticleBMC geriatrics2023

Older adults in the digital health era: insights on the digital health related knowledge, habits and attitudes of the 65 year and older population.

Zsuzsa Győrffy, Julianna Boros, Bence Döbrössy, Edmond Girasek

Open access · goldAbstract read
In one paragraph

Article in BMC geriatrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 1 pooled it
55.6field-weighted citation impact, top 1% 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

42 citing papers in PubMed, 1 synthesis or guideline pooled it, 64 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Article
  5. Article
  6. Observational
  7. Review
  8. Observational
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

4 authors at 1 institution in 1 country.

Zsuzsa GyőrffyInstitute of Behavioural Sciences, Faculty of Medicine, Semmelweis University, Nagyvárad tér 4. 20th floor, Budapest, H-1089, Hungary. gyorffy.zsuzsa.mail@gmail.com.ORCID 0000-0001-6866-4653
Julianna BorosInstitute of Behavioural Sciences, Faculty of Medicine, Semmelweis University, Nagyvárad tér 4. 20th floor, Budapest, H-1089, Hungary.ORCID 0000-0003-3191-3630
Bence DöbrössyInstitute of Behavioural Sciences, Faculty of Medicine, Semmelweis University, Nagyvárad tér 4. 20th floor, Budapest, H-1089, Hungary.ORCID 0000-0002-1937-1528
Edmond GirasekInstitute of Behavioural Sciences, Faculty of Medicine, Semmelweis University, Nagyvárad tér 4. 20th floor, Budapest, H-1089, Hungary.ORCID 0000-0002-0579-6592
Semmelweis University · HU

Funding

National Research, Development and Innovation Office OTKA-FK 134372
6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has increased internet use by older age groups to an unprecedented level in Hungary mirroring the general tendency in the total population. Nevertheless, international trends indicate that this group is less likely to use digital health technologies than younger ones. The aging population raises the question of successfully integrating elderly people into the digital health ecosystem. Our research aim is to investigate the digital health usage patterns and attitudes of the population aged 65 and over through a representative sample.

methodsA national representative questionnaire survey was conducted by telephone (CATI), interviewing 1723 respondents. Within this sample we examined 428 people in the over-65 age group, 246 in the 65-74 age group and 182 in the over-75 age group. Predictors of demand for digital solutions were tested using binary logistic regression model.

results50.8% of people aged 65-74 and 37.1. % of people aged 75 + use the internet for health-related purposes, mostly to access websites. 85% of respondents in 65-74 and 74% in 75 + age group have used more than one digital health device and around 70% of both age groups have a need for more than one digital solution. 90.2% (64-75 age group) and 85.7% (75 + age group) of respondents are familiar with e-prescription, 86.4% and 81.4% of them use it. 77.1% of 65-74-year-olds have heard of and nearly half 45.5% have used online appointment. More than half (52.7%) of the respondents in this age group have heard of and used electronic transmission of medical records and data. A similar proportion has heard about and used apps: 54.3% has heard of them, but only 17.3% has used them. The multivariate analyses emphasized that the need for digital solutions increases with the level of education and the more benefits one perceives in using digital solutions.

conclusionOur research has shown that the senior age group has measurable needs in the field of digital health, so helping them on this journey is in the interest of the whole health ecosystem. Their high level of interest is indicated by the fact that more than a fifth of older adults would like to have access to between 7 and 10 of the maximum number of digital devices available. The differences between the two age groups - with younger people being more open to digital solutions and using them more - and the fact that the under 65s are better adapted digitally in all respects, raises the possibility that the specific trends in digital health for older people may virtually disappear in 10 years' time (when the under 65s now enter this age group).

Indexed as

COVID-19PandemicsAgedEcosystemHabitsHumansInternetSurveys and QuestionnairesBio-psycho-social-digital modelDigitalizationDigital solutionsOlder adultsOnline information seeking

Identifiers

PMID38012565
PMCPMC10683351
OpenAlexW4389057550

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.