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Record W4399419649 · doi:10.2196/50356

Real-World Outcomes of a Digital Behavioral Coaching Intervention to Improve Employee Health Status: Retrospective Observational Study

2024· article· en· W4399419649 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJMIR mhealth and uhealth · 2024
Typearticle
Languageen
FieldPsychology
TopicCoaching Methods and Impact
Canadian institutionsnot available
Fundersnot available
KeywordsObservational studyPreprintCoachingIntervention (counseling)MedicineDigital healthmHealthPsychologyPhysical therapyApplied psychologyPsychological interventionHealth careNursingComputer sciencePsychotherapist

Abstract

fetched live from OpenAlex

BACKGROUND: Chronic noncommunicable diseases (NCDs) account for major disability and premature mortality worldwide, with low- and middle-income countries being disproportionately burdened. Given the negative impact of NCDs on employee performance and work productivity, there is a rising need for stakeholders to identify effective workplace solutions that can improve employee health outcomes. As the workplace becomes more dispersed post pandemic, digital behavioral coaching offers a scalable, personalized, and cost-effective method of managing chronic disease risk factors among employees. OBJECTIVE: This study aimed to retrospectively evaluate the impact of a digital behavioral coaching program on year-to-year changes in employee health status in a cohort of Indonesian employees. METHODS: This retrospective real-world exploratory analysis of secondary health data followed 774 employees of an Indonesian company who completed company-sponsored health screenings between 2021 and 2022 and were given access to Naluri (Naluri Hidup Sdn Bhd), a holistic digital therapeutics platform offering digital behavioral health coaching and self-help tools. Participants were retrospectively classified as those who received active coaching (n=177), passive coaching (n=108), and no coaching (n=489). Linear mixed-effects models were used to evaluate the year-to-year changes in health outcomes across the 3 employee groups, with post hoc analyses evaluating within-group differences between the 2 time points and between-group differences at follow-up. RESULTS: =-11.45, P<.001) for employees in the Active Coaching group between 2021 and 2022, with the other 2 groups reporting deteriorations in multiple health outcomes throughout the 2 time points. At follow-up, those who received active coaching between 2021 and 2022 reported significantly lower body weight (P<.001), BMI (P=.001), low-density lipoprotein (P=.045), and total cholesterol (P<.001) than the No Coaching group. CONCLUSIONS: This study demonstrates real-world outcomes and implications supporting the use of workplace digital behavioral coaching in improving employee health status. Given the rising burden of NCDs in the Southeast Asian region, our findings underscore the role that workplace digital health interventions can play in preventing and managing chronic disease risk factors.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.200
GPT teacher head0.536
Teacher spread0.336 · 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