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Record W3003833448 · doi:10.2196/15943

Feasibility and Acceptability of a Mobile Mindfulness Meditation Intervention Among Women: Intervention Study

2020· article· en· W3003833448 on OpenAlexvenueno aff
Ariane L. Rung, Evrim Oral, Lara Berghammer, Edward Peters

Bibliographic record

VenueJMIR mhealth and uhealth · 2020
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsnot available
FundersNational Institute of Environmental Health Sciences
KeywordsMindfulnessmHealthMedicinePopulationPsychological interventionIntervention (counseling)Mobile appsMental healthGerontologyClinical psychologyPsychiatryEnvironmental healthWorld Wide Web

Abstract

fetched live from OpenAlex

BACKGROUND: Traditional mindfulness-based stress reduction programs are resource intensive for providers and time- and cost-intensive for participants, but the use of mobile technologies may be particularly convenient and cost-effective for populations that are busy, less affluent, or geographically distant from skilled providers. Women in southern Louisiana live in a vulnerable, disaster-prone region and are highly stressed, making a mobile program particularly suited to this population. OBJECTIVE: This study aimed to (1) assess the feasibility and acceptability of a mobile mindfulness app in real-world conditions in a pilot study of a community sample of women residing in southern Louisiana, (2) describe predictors of app usage, and (3) assess the effect of the app on secondary health outcomes. METHODS: Women were recruited from an oil spill study on health. A total of 236 women completed a baseline survey, were offered the mobile mindfulness program, and completed a follow-up survey. Subjects were asked to download and use the app for at least 30 days for 10 min. All study procedures were completed on the web. Primary outcomes were feasibility and acceptability of the app and characteristics of app utilization. Secondary outcomes included mindfulness, depression, perceived stress, sleep quality, physical activity, BMI, and healthy eating. RESULTS: Overall, 74.2% (236/318) of subjects completed the follow-up survey, and 13.5% (43/318) used the app. The main barrier to app usage was lack of time, cited by 37% (16/43) of users and 48.7% (94/193) of nonusers of the app. Women who chose to use the app were more highly educated (16/43, 63% had a college education vs 65/193, 33.7% of nonparticipants; P<.001), had higher incomes (23/43, 58% had incomes >US $50,000 per year vs 77/193, 43.0% of nonparticipants), and were employed (34/43, 79% vs 122/193, 63.2% of nonparticipants; P=.047). Those who engaged with the app did so at high levels, with 72% (31/43) of participants self-reporting the completion of some or all sessions and 74% (32/43) reporting high levels of satisfaction with the app. Participation with the app had a beneficial impact on depression (odds ratio [OR] 0.3, 95% CI 0.11-0.81), sleep quality (OR 0.1, 95% CI 0.02-0.96), sleep duration (OR 0.3, 95% CI 0.07-0.86), sleep latency (OR 0.3, 95% CI 0.11-0.81), and physical activity (2.8 95% CI 1.0-7.8), but mindfulness scores did not change from baseline to follow-up. CONCLUSIONS: The Headspace mobile mindfulness app was easy and cost-effective to implement and acceptable to those who participated, but few women elected to try it. The unique characteristics of this southern Louisiana population suggest that more intense promotion of the benefits of mindfulness training is needed, perhaps in conjunction with some therapist or researcher support. Several short-term benefits of the app were identified, particularly for depression and sleep.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.448
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.076
GPT teacher head0.427
Teacher spread0.351 · 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 designObservational
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

Citations43
Published2020
Admission routes1
Has abstractyes

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