Evidence map›Paper›PMID 36069848›Full record

ReviewJMIR mental health2022

The Apple Watch for Monitoring Mental Health-Related Physiological Symptoms: Literature Review.

Gough Yumu Lui, Dervla Loughnane, Caitlin Polley, Titus Jayarathna, Paul P Breen

Abstract readReview
In one paragraph

Review in JMIR mental health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 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

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  9. Using Apple Watches to Monitor Health and Behaviors of Individuals With Cognitive Impairment: A Case Series Study.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025
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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

5 authors.

Gough Yumu LuiThe MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Penrith, NSW, Australia.ORCID https://orcid.org/0000-0003-1042-5793
Dervla LoughnaneVirtual Psychologist, Southport Park, QLD, Australia.ORCID https://orcid.org/0000-0002-2573-0945
Caitlin PolleyElectrical and Electronic Engineering, School of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW, Australia.ORCID https://orcid.org/0000-0002-1918-0393
Titus JayarathnaThe MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Penrith, NSW, Australia.ORCID https://orcid.org/0000-0002-1849-4235
Paul P BreenThe MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Penrith, NSW, Australia.ORCID https://orcid.org/0000-0002-8860-2086

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAn anticipated surge in mental health service demand related to COVID-19 has motivated the use of novel methods of care to meet demand, given workforce limitations. Digital health technologies in the form of self-tracking technology have been identified as a potential avenue, provided sufficient evidence exists to support their effectiveness in mental health contexts.

objectiveThis literature review aims to identify current and potential physiological or physiologically related monitoring capabilities of the Apple Watch relevant to mental health monitoring and examine the accuracy and validation status of these measures and their implications for mental health treatment.

methodsA literature review was conducted from June 2021 to July 2021 of both published and gray literature pertaining to the Apple Watch, mental health, and physiology. The literature review identified studies validating the sensor capabilities of the Apple Watch.

resultsA total of 5583 paper titles were identified, with 115 (2.06%) reviewed in full. Of these 115 papers, 19 (16.5%) were related to Apple Watch validation or comparison studies. Most studies showed that the Apple Watch could measure heart rate acceptably with increased errors in case of movement. Accurate energy expenditure measurements are difficult for most wearables, with the Apple Watch generally providing the best results compared with peers, despite overestimation. Heart rate variability measurements were found to have gaps in data but were able to detect mild mental stress. Activity monitoring with step counting showed good agreement, although wheelchair use was found to be prone to overestimation and poor performance on overground tasks. Atrial fibrillation detection showed mixed results, in part because of a high inconclusive result rate, but may be useful for ongoing monitoring. No studies recorded validation of the Sleep app feature; however, accelerometer-based sleep monitoring showed high accuracy and sensitivity in detecting sleep.

conclusionsThe results are encouraging regarding the application of the Apple Watch in mental health, particularly as heart rate variability is a key indicator of changes in both physical and emotional states. Particular benefits may be derived through avoidance of recall bias and collection of supporting ecological context data. However, a lack of methodologically robust and replicated evidence of user benefit, a supportive health economic analysis, and concerns about personal health information remain key factors that must be addressed to enable broader uptake.

Indexed as

Apple Watchdatadigital healthenergy expenditureheart rate variabilitymental healthmobile phoneprecision medicinepsychologysleep trackingvalidation

Identifiers

PMID36069848
PMCPMC9494213

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.