MétaCan
Menu
Back to cohort

Web-Based Presence for Social Connectedness in Long-Term Care: Protocol for a Qualitative Multimethods Study

2023· article· en· W7093299202 on OpenAlexaboutno aff

Bibliographic record

VenueScholar Commons (University of South Carolina) · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsSocial connectednessThematic analysisQualitative researchTriangulationMental healthInterpretation (philosophy)Content analysisProtocol (science)

Abstract

fetched live from OpenAlex

BACKGROUND: The COVID-19 pandemic and resultant restrictions on social gatherings significantly impacted many peoples' sense of social connectedness, defined as an individual's subjective sense of having close relationships with others. Older adults living in long-term care homes (LTCHs) experienced extreme restrictions on social gatherings, which negatively impacted their physical and mental health as well as the health and well-being of their family caregivers. Their experiences highlighted the need to reconceptualize social connectedness. In particular, the pandemic highlighted the need to explore novel ways to attain fulfilling relationships with others in the absence of physical gatherings such as through the use of a hybridized system of web-based and in-person presence. OBJECTIVE: Given the potential benefits and challenges of web-based presence technology within LTCHs, the proposed research objectives are to (1) explore experiences regarding the use of web-based presence technology (WPT) in support of social connectedness between older adults in LTCHs and their family members, and (2) identify the contextual factors that must be addressed for successful WPT implementation within LTCHs. METHODS: This study will take place in south western Ontario, Canada, and be guided by a qualitative multimethod research design conducted in three stages: (1) qualitive description with in-depth qualitative interviews guided by the Technology Acceptance Model (TAM) and analyzed using content analysis; (2) qualitative description and document analysis methodologies, informed by content and thematic analysis methods; and (3) explicit between-methods triangulation of study findings from stages 1 and 2, interpretation of findings and development of a guiding framework for technology implementation within LTCHs. Using a purposeful, maximum variation sampling approach, stage 1 will involve recruiting approximately 45 participants comprising a range of older adults, family members (30 participants) and staff (15 participants) within several LTCH settings. In stage 2, theoretical sampling will be used to recruit key LTCH stakeholders (directors, administrators, and IT support). In stage 3, the findings from stages 1 and 2 will be triangulated and interpreted to develop a working framework for WPT usage within LTCHs. RESULTS: Data collection will begin in fall 2023. The findings emerging from this study will provide insights and understanding about how the factors, barriers, and facilitators to embedding and spreading WPT in LTCHs may benefit or negatively impact older adults in LTCHs, family caregivers, and staff and administrators of LTCHs. CONCLUSIONS: The results of this research study will provide a greater understanding of potential approaches that could be used to successfully integrate WPTs in LTCHs. Additionally, benefits as well as challenges for older adults in LTCHs, family caregivers, and staff and administrators of LTCHs will be identified. These findings will help increase knowledge and understanding of how WPT may be used to support social connectedness between older adults in LTCHs and their family members. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/50137.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.080
GPT teacher head0.410
Teacher spread0.330 · 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.

Study designQualitative
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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueScholar Commons (University of South Carolina)Same topicTechnology Use by Older AdultsFrench-language works237,207