MétaCan
Menu
Back to cohort

A grounded theory study to identify caregiving phases and support needs across the Alzheimer’s disease trajectory

2020· article· en· W6920735854 on OpenAlexaff

Bibliographic record

VenueFigshare · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Thermodynamics and Statistical Mechanics
Canadian institutionsProvincial Health Services Authority
Fundersnot available
KeywordsGrounded theoryDiseaseConstructivist grounded theoryData collectionCognitionActivities of daily livingNeeds assessment

Abstract

fetched live from OpenAlex

Caregivers of individuals with Alzheimer’s disease require support across the full disease trajectory. The aim of this study was to develop a conceptual framework of caregiving phases across the Alzheimer’s disease and caregiving trajectories and the corresponding caregiver support needs. Constructivist grounded theory informed data collection and analysis. 40 spousal (n = 20) and adult children (n = 20) caregivers were interviewed. Recruitment was completed when theoretical saturation was achieved. Member-checking interviews occurred with 10 participants. Participants described five phases of caregiving related to their responsibilities to support people with Alzheimer’s disease including monitoring initial symptoms, navigating their diagnosis, assisting with instrumental activities of daily living, assisting with basic activities of daily living, and preparing for the future. Support (i.e., informational, emotional, instrumental, and appraisal) needs were often specific to the phase of care. For example, during the initial symptoms phase, caregivers reported needing information to assist them to distinguish normal aging from cognitive impairment. In contrast, during the preparing for the future phase, caregivers emphasized support for accessing institutional long term-care placement. Findings highlight caregiver-identified phases of caregiving and corresponding support needs across the Alzheimer’s disease trajectory. Findings can inform the development, evaluation and implementation of programs and services to meet caregivers’ changing needs across the disease trajectory.IMPLICATIONS FOR REHABILITATIONCaregivers for individuals with Alzheimer’s disease can experience distinct caregiving phases across the disease trajectory with corresponding support needs.Rehabilitation clinicians can use these findings to help caregivers navigate available supports at appropriate times to ensure that their needs are addressed across the disease trajectory.Occupational therapists and other rehabilitation professionals can enable caregivers with timely education and support as they progress across the disease trajectory. Caregivers for individuals with Alzheimer’s disease can experience distinct caregiving phases across the disease trajectory with corresponding support needs. Rehabilitation clinicians can use these findings to help caregivers navigate available supports at appropriate times to ensure that their needs are addressed across the disease trajectory. Occupational therapists and other rehabilitation professionals can enable caregivers with timely education and support as they progress across the disease trajectory.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.037
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.196

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0370.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.005
Science and technology studies0.0070.008
Scholarly communication0.0060.008
Open science0.0020.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.050
GPT teacher head0.345
Teacher spread0.294 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueFigshareSame topicAdvanced Thermodynamics and Statistical MechanicsFrench-language works237,207