Evidence map›Paper›PMID 38977903›Full record

ArticleNpj mental health research2024

Quantifying the interrelationships between physical, social, and cognitive-emotional components of mental fitness using digital technology.

Frank Iorfino, Mathew Varidel, William Capon, Matthew Richards, Jacob J Crouse, Haley M LaMonica, Shin Ho Park, Sarah Piper, Yun Ju Christine Song, Carla Gorban and 2 more

Abstract read
In one paragraph

Article in Npj mental health research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

12 authors.

Frank IorfinoBrain and Mind Centre, The University of Sydney, Sydney, Australia. frank.iorfino@sydney.edu.au.
Mathew VaridelBrain and Mind Centre, The University of Sydney, Sydney, Australia.
William CaponBrain and Mind Centre, The University of Sydney, Sydney, Australia.
Matthew RichardsBrain and Mind Centre, The University of Sydney, Sydney, Australia.
Jacob J CrouseBrain and Mind Centre, The University of Sydney, Sydney, Australia.
Haley M LaMonicaBrain and Mind Centre, The University of Sydney, Sydney, Australia.
Shin Ho ParkBrain and Mind Centre, The University of Sydney, Sydney, Australia.
Sarah PiperBrain and Mind Centre, The University of Sydney, Sydney, Australia.
Yun Ju Christine SongBrain and Mind Centre, The University of Sydney, Sydney, Australia.
Carla GorbanBrain and Mind Centre, The University of Sydney, Sydney, Australia.
Elizabeth M ScottBrain and Mind Centre, The University of Sydney, Sydney, Australia.
Ian B HickieBrain and Mind Centre, The University of Sydney, Sydney, Australia.

Funding

Australian Government Research Training Program (RTP) Scholarship NABill and Patricia Ritchie Foundation Fellowship NANHMRC Australia Fellowship 511921NHMRC Emerging Leadership Fellowship GNT2008197
6 · The paper itself

Abstract

Mental fitness is a construct that goes beyond a simple focus on subjective emotional wellbeing to encompass more broadly our ability to think, feel, and act to achieve what we want in our daily lives. The measurement and monitoring of multiple (often interacting) domains is crucial to gain a holistic and complete insight into an individual's mental fitness. We aimed to demonstrate the capability of a new mobile app to characterise the mental fitness of a general population of Australians and to quantify the interrelationships among different domains of mental fitness. Cross-sectional data were collected from 4901 adults from the general population of Australians engaged in work or education who used a mobile app (Innowell) between September 2021 and November 2022. Individuals completed a baseline questionnaire comprised of 26 questions across seven domains of mental fitness (i.e., physical activity, sleep and circadian rhythms, nutrition, substance use, daily activities, social connection, psychological distress). Network analysis was applied at both a domain-level (e.g., 7 nodes representing each cluster of items) and an individual item-level (i.e., 26 nodes representing all questionnaire items). Only 612 people (12%) were functioning well across all domains. One quarter (n = 1204, 25%) had only one problem domain and most (n = 3085, 63%) had multiple problem domains. The two most problematic domains were physical activity (n = 2631, 54%) and social connection (n = 2151, 44%), followed closely by daily activity (n = 1914, 39%). At the domain-level, the strongest association emerged between psychological distress and daily activity (r = 0.301). Psychological distress was the most central node in the network (as measured by strength and expected influence), followed closely by daily activity, sleep and circadian rhythms and then social connection. The item-level network revealed that the nodes with the highest centrality in the network were: hopelessness, depression, functional impairment, effortfulness, subjective energy, worthlessness, and social connectedness. Social connection, sleep and circadian rhythms, and daily activities may be critical targets for intervention due to their widespread associations in the overall network. While psychological distress was not among the most common problems, its centrality may indicate its importance for indicated prevention and early intervention. We showcase the capability of a new mobile app to monitor mental fitness and identify the interrelationships among multiple domains, which may help people develop more personalised insights and approaches.

Identifiers

PMID38977903
PMCPMC11231280

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.