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Record W4401550913 · doi:10.2196/41221

Online Yoga Pilot Intervention for Black Women at High Cardiovascular Risk: Internet-Based Recruitment and Engagement

2024· article· en· W4401550913 on OpenAlexvenueno aff
Candace C. Johnson

Bibliographic record

VenueJMIR Formative Research · 2024
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsnot available
FundersNational Center for Advancing Translational Sciences
KeywordsPreprintIntervention (counseling)The InternetAfrican americanGerontologyPsychologyMedicineComputer scienceSociologyWorld Wide WebNursingAnthropology

Abstract

fetched live from OpenAlex

BACKGROUND: Disproportionately adverse heart health outcomes in Black women, characterized by high metabolic syndrome prevalence, underscore the need for innovative, accessible interventions. Digital health strategies, particularly web-based yoga videos, show promise for engaging this high-risk group in health-promoting behaviors. OBJECTIVE: This study aimed to evaluate the feasibility and acceptability of a web-based yoga intervention for community-dwelling Black women, providing preliminary data to inform a larger, mixed methods study on reducing cardiometabolic risks. METHODS: In this 4-week pilot study, grounded in Pender's Health Promotion Model, 28 participants engaged in daily online health education and yoga activities through YouTube videos. Using Fitbit trackers, electronic blood pressure monitors, and web-based logs, the study measured metabolic syndrome risk factors and sedentary behavior. Participant experiences were further explored through postintervention focus groups aiming to contextualize the intervention's impact. RESULTS: =5.67, P=.02) were key to participant adherence. The intervention was well-received, with 95% (19/20) of survey respondents finding it satisfactory and suitable. Technology use was high, with all participants having access to the internet, 96% (27/28) owning smartphones, and 53% (15/28) having a YouTube account prior to the study. Recruitment was effectively conducted online, primarily via Facebook and a university newsletter, each accounting for 39.3% (11/28) of participants. The qualitative focus group data unveiled 4 major themes: (1) accountability, emphasizing the shift toward self-prioritization and collective health responsibility; (2) increased awareness, highlighting enhanced understanding of health behaviors and metabolic syndrome risks; (3) health benefits, noting observed improvements in blood pressure and stress levels; and (4) unanticipated stressors, identifying external factors that challenged engagement. These insights underscore the intervention's multifaceted impact, from fostering health awareness to navigating external stressors. CONCLUSIONS: This pilot study demonstrated the feasibility and acceptability of a culturally tailored, online yoga intervention among community-based, Black women at high risk for metabolic syndrome, showing promising engagement and potential health benefits. The high rates of participation and completion highlight the intervention's acceptability and the potential for digital platforms to facilitate health behavior changes in high-risk populations. The qualitative findings reveal critical insights into the psychological and social dynamics influencing health behavior change, suggesting the importance of addressing both individual and communal barriers to improve intervention efficacy. Future research should further explore these dynamics in larger, more diverse cohorts to substantiate the intervention's potential in reducing cardiometabolic risks.

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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.199
GPT teacher head0.464
Teacher spread0.265 · 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 designNon-randomized 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

Citations2
Published2024
Admission routes1
Has abstractyes

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