Evidence map›Paper›PMID 38913405›Full record

Observational studyJMIR mHealth and uHealth2024

Improvement and Maintenance of Clinical Outcomes in a Digital Mental Health Platform: Findings From a Longitudinal Observational Real-World Study.

Lydia G Roos, Sara J Sagui-Henson, Cynthia Castro Sweet, Camille E Welcome Chamberlain, Brooke J Smith

Abstract readObservational Study
In one paragraph

Observational study in JMIR mHealth and uHealth, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
  4. Observational
  5. Review
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Lydia G RoosDepartment of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0003-4688-5687
Sara J Sagui-HensonModern Health, San Francisco, CA, United States.ORCID 0000-0001-5410-2684
Cynthia Castro SweetModern Health, San Francisco, CA, United States.ORCID 0000-0001-6860-4095
Camille E Welcome ChamberlainModern Health, San Francisco, CA, United States.ORCID 0000-0003-2735-7299
Brooke J SmithModern Health, San Francisco, CA, United States.ORCID 0000-0001-7554-7092

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital mental health services are increasingly being provided by employers as health benefit programs that can improve access to and remove barriers to mental health care. Stratified care models, in particular, offer personalized care recommendations that can offer clinically effective interventions while conserving resources. Nonetheless, clinical evaluation is needed to understand their benefits for mental health and their use in a real-world setting.

objectiveThis study aimed to examine the changes in clinical outcomes (ie, depressive and anxiety symptoms and well-being) and to evaluate the use of stratified blended care among members of an employer-sponsored digital mental health benefit.

methodsIn a large prospective observational study, we examined the changes in depressive symptoms (9-item Patient Health Questionnaire), anxiety symptoms (7-item Generalized Anxiety Disorder scale), and well-being (5-item World Health Organization Well-Being Index) for 3 months in 509 participants (mean age 33.9, SD 8.7 years; women: n=312, 61.3%; men: n=175, 34.4%; nonbinary: n=22, 4.3%) who were newly enrolled and engaged in care with an employer-sponsored digital mental health platform (Modern Health Inc). We also investigated the extent to which participants followed the recommendations provided to them through a stratified blended care model.

resultsParticipants with elevated baseline symptoms of depression and anxiety exhibited significant symptom improvements, with a 37% score improvement in depression and a 29% score improvement in anxiety (P values <.001). Participants with baseline scores indicative of poorer well-being also improved over the study period (90% score improvement; P=.002). Furthermore, over half exhibited clinical improvement or recovery for depressive symptoms (n=122, 65.2%), anxiety symptoms (n=127, 59.1%), and low well-being (n=82, 64.6%). Among participants with mild or no baseline symptoms, we found high rates of maintenance for low depressive (n=297, 92.2%) and anxiety (n=255, 86.7%) symptoms and high well-being (n=344, 90.1%). In total, two-thirds of the participants (n=343, 67.4%) used their recommended care, 16.9% (n=86) intensified their care beyond their initial recommendation, and 15.7% (n=80) of participants underused care by not engaging with the highest level of care recommended to them.

conclusionsParticipants with elevated baseline depressive or anxiety symptoms improved their mental health significantly from baseline to follow-up, and most participants without symptoms or with mild symptoms at baseline maintained their mental health over time. In addition, engagement patterns indicate that the stratified blended care model was efficient in matching individuals with the most effective and least costly care while also allowing them to self-determine their care and use combinations of services that best fit their needs. Overall, the results of this study support the clinical effectiveness of the platform for improving and preserving mental health and support the utility and effectiveness of stratified blended care models to improve access to and use of digitally delivered mental health services.

Indexed as

Mental Health ServicesAdultDepressionFemaleHumansLongitudinal StudiesMaleMiddle AgedProspective StudiesSurveys and QuestionnairesTelemedicineanxietydepressiondigital mental healthemployee healthmobile phonewell-being

Identifiers

PMID38913405
PMCPMC11231619

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.