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Record W3157775497 · doi:10.2196/25616

The Digital Engagement of Older People: Systematic Scoping Review Protocol

2021· article· en· W3157775497 on OpenAlexvenueno aff
Abraham Sahilemichael Kebede, Lise‐Lotte Ozolins, Hanna Holst, Kathleen Galvin

Bibliographic record

VenueJMIR Research Protocols · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
FundersEuropean Commission
KeywordsCINAHLPsycINFOGrey literatureDigital healthMEDLINEGerontologyData extractionMedicineInclusion (mineral)PopulationHealth careSystematic reviewPsychologyMedical educationNursingPsychological interventionPolitical scienceSocial psychologyEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: There is an ongoing negative narrative about aging that portrays older people as a socioeconomic burden on society. However, increased longevity and good health will allow older adults to contribute meaningfully to society and maximize their well-being. As such, a paradigm shift toward healthy and successful aging can be potentially facilitated by the growing digital technology use for mainstream (day-to-day activities) and assisted living (health and social care). Despite the rising digital engagement trend, digital inequality between the age groups persists. OBJECTIVE: The aims of this scoping review are to identify the extent and breadth of existing literature of older people's perspectives on digital engagement and summarize the barriers and facilitators for technological nonuse, initial adoption, and sustained digital technology engagement. METHODS: This review will be based on the Arksey and O'Malley framework for scoping reviews. The 6-stage framework includes: identifying research questions, identifying relevant studies, study selection, charting the data, summarizing and reporting the results, and a consultation exercise. Published literature will be searched on primary electronic databases such as the Association of Computing Machinery, Web of Science, MEDLINE, PsycINFO, CINAHL, and ScienceDirect. Common grey literature sources will complement the database search on the topic. A two-stage (title/abstract and full article) screening will be conducted to obtain eligible studies for final inclusion. A standardized data extraction tool will be used to extract variables such as the profile of the study population, technologies under investigation, stage of digital engagement, and the barriers and facilitators. Identified and eligible studies will be analyzed using a quantitative (ie, frequency analysis) and qualitative (ie, content analysis) approach suitable for comparing and evaluating literature to provide an evaluation of the current state of the older person's digital engagement. Inclusion will be based on the Joanna Briggs Institute-recommended participant, concept, and context framework. Articles on older people (65 years and older), on digital technology engagement, and from a global context will be included in our review. RESULTS: The results of this review are expected in July 2021. CONCLUSIONS: The findings from this review will identify the extent and nature of empirical evidence on how older people digitally engage and the associated barriers and facilitators. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/25616.

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)0.009
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.079
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.195
GPT teacher head0.571
Teacher spread0.376 · 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 designSystematic review
Domainnot available
GenreProtocol

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

Citations22
Published2021
Admission routes1
Has abstractyes

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