MétaCan
Menu
Back to cohort
Record W4414408541 · doi:10.2196/83618

Characterizing Digital Mindfulness Intervention Utilization and Weekly Assessments: A Secondary Analysis of a Randomized Controlled Trial of Caregivers of Persons Living with Dementia (Preprint)

2025· preprint· en· W4414408541 on OpenAlexvenueno aff
M. Williams, Darby Simon, Raquel Tatar, Jennifer Huberty, Ana‐Maria Vranceanu, Evan Plys

Bibliographic record

VenueJMIR Aging · 2025
Typepreprint
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsMindfulnessRandomized controlled trialMindfulness-based stress reductionPsychological interventionDementiaIntervention (counseling)Repeated measures designDescriptive statistics

Abstract

fetched live from OpenAlex

<sec> <title>BACKGROUND</title> Caregivers of persons living with dementia (PLWD) are at increased risk of reporting high stress. Mindfulness based interventions (MBIs) teach caregivers mindfulness skill and are effective at reducing stress. Digital MBIs are a feasible way to improve access to MBIs for caregivers of PWLD. Yet, caregiver improvement with digital MBI utilization is less defined in the literature. </sec> <sec> <title>OBJECTIVE</title> The goal of this secondary data analysis was to characterize weekly mindfulness and stress ratings among caregivers of PLWD and how digital MBI utilization impacted ratings throughout 12 weeks of a feasibility trial. </sec> <sec> <title>METHODS</title> Participants were eligible for this secondary analysis if they were randomized to the digital MBI condition (Healthy Mind Program for Caregivers [HMP-C], n=46) and completed weekly ratings over the 12-week trial. At baseline and at the end of each week of the trial, participants rated their mindfulness and stress in the past week from 0-10. Weekly HMP-C utilization was defined as time spent using HMP-C in the week prior to weekly ratings. Descriptive statistics and visualizations were used to characterize mindfulness and stress ratings. Generalized linear mixed models (GLMMs) were used to estimate the effect of mindfulness on stress and the effect of HMP-C utilization on stress and mindfulness throughout the trial (alpha=0.05). </sec> <sec> <title>RESULTS</title> Baseline mindfulness and stress ratings were 4 (IQR=3, range=0-8) and 7 (IQR=1.5, range=4-10), respectively. Stress evidenced the greatest decrease between baseline and week 3 (-2 points on average), whereas mindfulness had the greatest increase between baseline and week 4 (+2.5 points on average). There was a significant fixed effect of baseline mindfulness on baseline stress (β=0.5, p&lt;0.001), with a significant interaction between mindfulness and study week (β=0.05, p=0.001), suggesting that this relationship was attenuated over time. There was variability in baseline stress (τ00=2.04) and the relationship between mindfulness and stress (τ₁₁=0.08), with a high correlation (ρ01=0.86), suggesting that those with high baseline stress benefited most from increases in mindfulness. For every 10 minutes of HMP-C utilization between baseline and week 1, mindfulness and stress ratings were 0.14 points higher (p&lt;.001) and 0.14 points lower (p&lt;.001), respectively. Despite a significant interaction between HMP-C utilization and study week in both models, the effect size was small (mindfulness:β=0.02, p&lt;0.001; stress:β=0.01, p=0.013), suggesting that this relationship was sustained over time. </sec> <sec> <title>CONCLUSIONS</title> Mindfulness and stress improved mostly during the first 3-4 weeks of the trial. During this time of mindfulness skill acquisition, mindfulness and stress were the most significantly negatively related, especially among those with high baseline stress. The consistent relationship between HMP-C utilization and mindfulness and stress suggests that continued use of HMP-C may be helpful for skill maintenance. </sec> <sec> <title>CLINICALTRIAL</title> ClinicalTrials.gov [NCT05732038] https://clinicaltrials.gov/study/NCT05732038?cond=%22Dementia%22&amp;intr=%22Folate%22&amp;viewType=Table&amp;rank=4 </sec>

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.025
GPT teacher head0.370
Teacher spread0.346 · 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 designRandomized trial
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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJMIR AgingSame topicDigital Mental Health InterventionsFrench-language works237,207