Evidence map›Paper›PMID 34343965›Full record

ArticleJMIR formative research2021

Assessing the Care Modality Preferences and Predictors for Digital Mental Health Treatment Seekers in a Technology-Enabled Stepped Care Delivery System: Cross-sectional Study.

Elissa Kozlov, Meghan McDarby, Maximo Prescott, Myra Altman

Abstract read
In one paragraph

Article in JMIR formative research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 3 pooled it
–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

9 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Interventions to improve the psychosocial outcomes of individuals with lymphedema: a systematic review.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Pooled it
  2. Therapist-guided remote versus in-person cognitive behavioural therapy: a systematic review and meta-analysis of randomized controlled trials.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2024
    Pooled it
  3. Pooled it
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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

4 authors.

Elissa KozlovInstitute for Health, Health Policy and Aging Research, School of Public Health, Rutgers University, New Brunswick, NJ, United States.ORCID https://orcid.org/0000-0003-1027-2352
Meghan McDarbyDepartment of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, United States.ORCID https://orcid.org/0000-0001-9295-1812
Maximo PrescottModern Health, San Francisco, CA, United States.ORCID https://orcid.org/0000-0003-1879-1835
Myra AltmanModern Health, San Francisco, CA, United States.ORCID https://orcid.org/0000-0001-7634-9514

Funding

Pilot CoreP30AG022845 · NIA · WEILL MEDICAL COLL OF CORNELL UNIV · PI Manney Carrington Reid, ELAINE WETHINGTON · 2003 to 2026
$15.2M
NIA NIH HHS P30 AG022845
6 · The paper itself

Abstract

backgroundAccess to mental health services continues to be a systemic problem in the United States and around the world owing to a variety of barriers including the limited availability of skilled providers and lack of mental health literacy among patients. Individuals seeking mental health treatment may not be aware of the multiple modalities of digital mental health care available to address their problems (eg, self-guided and group modalities, or one-to-one care with a provider). In fact, one-to-one, in-person treatment is the dominant care model with a masters- or doctoral-level trained mental health provider, and it may or may not be the appropriate or preferred level of care for an individual. Technology-enabled mental health platforms may be one way to improve access to mental health care by offering stepped care, but more research is needed to understand the care modality preferences of digital mental health care seekers because additional modalities become increasingly validated as effective treatment options.

objectiveThe purpose of this study was to describe and evaluate the predictors of care modality preferences among individuals enrolled in a technology-enabled stepped mental health care platform.

methodsThis exploratory, cross-sectional study used employee data from the 2021 Modern Health database, an employer-sponsored mental health benefit that uses a technology-enabled platform to optimize digital mental health care delivery. Chi-square tests and one-way analysis of variance (ANOVA) were conducted to evaluate associations among the categorical and continuous factors of interest and the preferred care modality. Bivariate logistic regression models were constructed to estimate the odds ratios (ORs) of preferring a one-on-one versus self-guided group, or no preference for digital mental health care modalities.

resultsData were analyzed for 3661 employees. The most common modality preference was one-on-one care (1613/3661, 44.06%). Approximately one-fourth of the digital mental health care seekers (881/3661, 24.06%) expressed a preference for pursuing self-guided care, and others (294/3661, 8.03%) expressed a preference for group care. The ORs indicated that individuals aged 45 years and above were significantly more likely to express a preference for self-guided care compared to individuals aged between 18 and 24 years (OR 2.47, 95% CI 1.70-3.59; P<.001). Individuals screening positive for anxiety (OR 0.73, 95% CI 0.62-0.86; P<.001) or depression (OR 0.79, 95% CI 0.66-0.95; P=.02) were more likely to prefer one-on-one care.

conclusionsOur findings elucidated that care modality preferences vary and are related to clinical severity factors and demographic variables among individuals seeking digital mental health care.

Indexed as

mental health carepatient-centered carestepped caretechnology

Identifiers

PMID34343965
PMCPMC8482163

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.