MétaCan
Menu
Back to cohort
Record W2511011311 · doi:10.1093/fampra/cmw084

Engaging caregivers: exploring perspectives on web-based health information

2016· article· en· W2511011311 on OpenAlexafffundabout
Tabitha Tonsaker, Susan Law, Ilja Ormel, Cecilia Nease, Gillian Bartlett

Bibliographic record

VenueFamily Practice · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsSt Mary's Hospital CentreMcGill University
FundersCanadian Institutes of Health ResearchCollege of Family Physicians of Canada
KeywordsThematic analysisMedicineThe InternetFocus groupHealth informationHealth careQualitative researchNursingEmpowermentInformation seeking behaviorMEDLINEMedical educationWorld Wide Web

Abstract

fetched live from OpenAlex

Background: Informal or family caregivers are important contributors to health and health care and require support to sustain their role and address particular challenges. An experience-based health website may be an accessible, effective way to offer caregivers peer support and ultimately better equip them to care for themselves and their loved ones. Objectives: This study investigated how caregivers access and use information on the Internet about caregiving and their perspectives on the design and features of a new personal health experiences (PHEx) website. Methods: This was a qualitative descriptive study that involved three focus groups of caregivers for a total of 16 participants in a university-affiliated hospital in Quebec. Thematic analysis was used with transcriptions of recorded sessions. Results: With respect to how participants accessed and used health information, three themes emerged: searching for and choosing health websites, empowerment through the use of online health information, and concerns about health information on the Internet. In terms of their views on a health experiences website, the two main themes were: factors important for first impressions and perceived needs and expectations. Conclusion: Caregivers accessed and chose health information in a similar manner to other people but still offered additional insights regarding online health information retrieval, usage, and other perspectives, which will be helpful for future web-based initiatives that aim to provide support to caregivers.

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)0.005
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.725
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.013
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.003

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 head0.139
GPT teacher head0.443
Teacher spread0.304 · 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 designNot applicable
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

Citations18
Published2016
Admission routes3
Has abstractyes

Explore more

Same venueFamily PracticeSame topicHealth Literacy and Information AccessibilityFrench-language works237,207