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Record W4387138597 · doi:10.3389/fpsyg.2023.1168340

Ageing, the digital and everyday life during and since the Covid-19 pandemic

2023· article· en· W4387138597 on OpenAlexfundno aff
Wendy Martin, George Collett, Christopher Bell, Amy Prescott

Bibliographic record

VenueFrontiers in Psychology · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsEveryday lifePandemicDigital healthFocus groupCoronavirus disease 2019 (COVID-19)Embodied cognitionMeaning (existential)PsychologyInternet privacySociologyComputer scienceMedicinePolitical scienceHealth care

Abstract

fetched live from OpenAlex

Introduction: During and since the Covid-19 pandemic there has been an intensified integration of digital technologies into the everyday lives of older people. We do, however, know little about the ways in which older people incorporate digital technologies and communications into their daily lives and their own meanings, embodiment and experiences of the digital during and since the Covid-19 pandemic. Method: The aim of our research was to explore the use of digital devices during and since the Covid-19 pandemic and to identify facilitators and barriers to incorporating digital devices into everyday life. The research involved a series of online focus groups with people aged between 63 and 86 years living in the United Kingdom and were conducted in 2022. Each focus group lasted around 90 min and data was audio-recorded and transcribed. The data was analysed thematically. Results: From the analysis, three interconnecting whilst analytically distinct themes around the meaning and experiences of using digital devices in everyday life during and since the pandemic, are thematically presented as: (1) Incorporating the digital into everyday life; (2) Social and digital connectivity; and (3) Challenges and limitations of the digital in everyday life. Discussion: The research has provided insights into the way digital devices were used by older people during and since the Covid-19 pandemic. In particular, we highlight the increasing importance of digital connectivity and the ways in which older people actively engage (and resist) technologies of communication in their daily lives; and the significance of embodied co-presence and the immediacy of shared space and/or time is highlighted.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.308
Threshold uncertainty score0.656

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.332
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2023
Admission routes1
Has abstractyes

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