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Record W4400352265 · doi:10.2196/58356

Intervention for the Management of Neuropsychiatric Symptoms to Reduce Caregiver Stress: Protocol for the Mindful and Self-Compassion Care Intervention for Caregivers of Persons Living With Dementia

2024· article· en· W4400352265 on OpenAlexvenueno aff
Aniyah Travis, Arden O’Donnell, Natalia Giraldo‐Santiago, Sarah M Stone, Daniel Torres, Shelley R. Adler, Ana‐Maria Vranceanu, Christine S. Ritchie

Bibliographic record

VenueJMIR Research Protocols · 2024
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsnot available
FundersNational Institute on Aging
KeywordsMindfulnessPsychologyCaregiver stressDementiaIntervention (counseling)Self-compassionMoodClinical psychologyPsychological interventionMedicinePsychiatryDisease

Abstract

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BACKGROUND: Stress related to Alzheimer disease and related dementias (ADRD) is common, particularly among those who care for persons with challenging behaviors and personality or mood changes. Mindfulness and self-compassion programs are efficacious for managing stress. The skills of mindfulness and self-compassion, however, must be integrated with behavioral management skills in order to effectively improve caregiver stress. OBJECTIVE: In this study, we aimed to describe the development of the Mindful and Self-Compassionate Care (MASC) program, the first program that combines mindfulness and self-compassion with behavioral management skills to decrease caregiver stress, and its evaluation in the Supporting Our Caregivers in ADRD Learning (SOCIAL) study. METHODS: Using the National Institutes of Health (NIH) stage model, we describe 3 phases of work encompassing NIH Stages 1A and 1B. In phase 1, we conducted 5 focus groups (N=28) of stressed individuals caring for persons with ADRD and challenging behaviors. Rapid data analysis informed the development of a 6-week online intervention. Phase 2 (NIH stage 1A) includes an open pilot (N>10) with optional exit interviews. Phase 3 (NIH stage 1B) is a feasibility randomized controlled trial of the intervention versus the Health Education Program control. Primary outcomes focus on feasibility with secondary outcomes encompassing acceptability, credibility, fidelity, and signals of preliminary efficacy. Phase 1 follows traditional recommendations for qualitative analyses (at the point of thematic saturation) which was achieved after 5 focus groups (N=28). For the phase 2 open pilot, up to 12 participants will be recruited. For the phase 3 feasibility study, recruitment of 80 caregivers will allow the assessment of feasibility benchmarks. Data for phase 1 included 5 focus groups. In phases 2 and 3, data collection will occur through REDCap (Research Electronic Data Capture; Vanderbilt University) surveys and an optional qualitative exit interview. Analyses will include hybrid inductive-deductive analyses for qualitative data and assessment of changes in our intervention targets and outcomes using t tests and correlation analyses. RESULTS: In phase 1, caregivers reported interest in a brief, online stress management program. Participants held misconceptions about mindfulness and self-compassion, but after detailed explanation thoughts, these skills could be helpful when directly linked to implementation during caregiving routines. Phases 2 and 3 will be completed by the end of 2025. CONCLUSIONS: We describe the protocol for the Supporting Our Caregivers in ADRD Learning study, as well as the development and feasibility testing of the Mindful and Self-Compassionate Care intervention. Future work will include a fully powered efficacy-effectiveness randomized controlled trial. TRIAL REGISTRATION: ClinicalTrials NCT05847153; https://clinicaltrials.gov/study/NCT05847153; and ClinicalTrials.gov NCT06276023; https://clinicaltrials.gov/study/NCT06276023. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/58356.

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)0.010
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.044
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.009
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0020.001
Science and technology studies0.0040.002
Scholarly communication0.0010.001
Open science0.0030.002
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0440.007

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 head0.084
GPT teacher head0.483
Teacher spread0.400 · 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 designNot applicable
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

Citations4
Published2024
Admission routes1
Has abstractyes

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