Evidence map›Paper›PMID 40735548›Full record

ArticleDigital health

Impact of a pediatric digital mental health intervention on caregiver sleep and stress: A retrospective exploration of moderators of improvement.

Darian Lawrence-Sidebottom, Kelsey L McAlister, Donna McCutchen, Monika Roots, Jennifer Huberty

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Darian Lawrence-SidebottomBend Health Inc., Madison, WI, USA.ORCID https://orcid.org/0000-0001-8252-2424
Kelsey L McAlisterFit Minded Inc., Phoenix, AZ, USA.ORCID https://orcid.org/0000-0003-1548-4936
Donna McCutchenBend Health Inc., Madison, WI, USA.
Monika RootsBend Health Inc., Madison, WI, USA.ORCID https://orcid.org/0009-0005-6691-8353
Jennifer HubertyBend Health Inc., Madison, WI, USA.ORCID https://orcid.org/0000-0002-0276-4640

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Children's mental health (MH) places significant strain on their caregivers, who often experience disrupted sleep and heightened stress. Given the close relationship between caregiver and child MH symptoms, understanding how digital MH interventions (DMHIs) influence both child and caregiver symptoms is essential for optimizing family-centered treatment approaches. Objectives: The purpose of this study was to (a) examine associations between child MH and caregiver sleep problems and stress before beginning MH treatment, (b) explore whether a child's engagement level with a DMHI moderates their rate of MH improvement, and (c) determine whether a child's rate of MH improvement is associated with their caregiver's rate of improvement in sleep problems and stress. Methods: Child-caregiver pairs ( Results: Caregiver sleep problems were associated with child internalizing symptoms (anxiety, depression, and sleep problems; Conclusion: Caregivers of children with more severe symptoms experienced higher stress and sleep disturbances. Greater session engagement was linked to greater child symptom improvement, and greater child symptom improvement was associated with greater reductions in caregiver sleep problems and stress. This highlights how a pediatric DMHI can drive meaningful improvements in MH that extend beyond the child, creating positive ripple effects for caregivers as well.

Indexed as

adolescentscaregiver mental healthchildrenfamily-based careMeasurement-based care model

Identifiers

PMID40735548
PMCPMC12304602

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.