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Record W4390515049 · doi:10.2196/52560

Mental Health and Well-Being in Racial or Ethnic Minority Individuals After Using a Faith and Prayer Mobile App (Pray.com): Feasibility and Preliminary Efficacy Trial

2024· article· en· W4390515049 on OpenAlexvenueno aff
Breanne Laird, Sabrina Zuniga, Joshua N. Hook, Daryl R. Van Tongeren, Lynda Joeman, Jennifer Huberty

Bibliographic record

VenueJMIR Formative Research · 2024
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
FundersBiola University
KeywordsPrayerFaithEthnic groupMental healthPsychologyGerontologyReligious studiesSociologyGender studiesPsychotherapistMedicineTheologyAnthropologyPhilosophy

Abstract

fetched live from OpenAlex

BACKGROUND: Research is needed on how faith and prayer apps fit within the values of racial and ethnic minority (REM) groups, as well as whether such apps are effective in promoting mental health and well-being. OBJECTIVE: This study aims to determine the feasibility and preliminary effectiveness of using the mobile app Pray.com on mental health and well-being among REM participants. METHODS: This study was a single-group (N=77), 4-week feasibility trial in REM groups (65/77, 84% Black or African American). Participants were asked to use the Pray.com app at no cost for at least 5 times per week for 5 minutes per day. Participants completed questionnaires at the baseline and postintervention time points. Feasibility questionnaires were only completed at the postintervention time point, including qualitative interviews (n=15). The feasibility questions included acceptability (ie, satisfaction, intent to continue use, perceived appropriateness, and fit within culture), demand (ie, self-reported app use, expressed interest, and perceived demand), and practicality (ie, ease or difficulty of use, ability to use the app, and cost-effectiveness). Frequency and descriptive statistics were used to analyze feasibility outcomes. Changes in dependent variables were analyzed using paired-sample 2-tailed t tests. Partial correlations were conducted to explore the association between app use and outcomes, controlling for baseline scores. RESULTS: Participants reported (54/72, 75% responded with "very likely" or "likely" to the feasibility questions) that they perceived the Pray.com app as acceptable. These findings were supported by qualitative interviews (n=15). Most participants (62/72, 86%) did not meet the app use prescription but expressed interest in using the app in the future and perceived demand for it in their communities. In addition, participants reported that the app was easy to use and perceived it to be inexpensive (US $7.99). Participants reported improved mental health (ie, stress and depressive and anxiety symptoms) and well-being (ie, satisfaction with life, spiritual well-being, religious commitment, and racial or ethnic identity development) at postintervention despite relatively low average levels and high variability of app use (average total of 45.83, SD 111.90 min over the course of the study). Greater app use was significantly associated with improvements in mental health and spiritual well-being. However, app use and study methodology limitations suggest that the study results may not accurately capture the full impact of Pray.com use. CONCLUSIONS: This is the first study to assess the feasibility of a faith and prayer app for mental health and well-being in a sample of REM individuals. Our findings suggest that the use of a faith and prayer app (ie, Pray.com) could be feasible and significantly impactful for the improvement of mental health symptoms and well-being in REM individuals and their communities, especially Black and African American individuals with a Christian affiliation. Further research is warranted.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.148
GPT teacher head0.539
Teacher spread0.391 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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