Evidence map›Paper›PMID 41788570›Full record

ArticleFrontiers in health services2026

Are you bothered? Assessing the association between symptoms and botheredness using real-world data to help improve mental health services.

Timothy A Carey

Abstract read
In one paragraph

Article in Frontiers in health services, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Timothy A CareyCentre > Health Equity in Regional and Remote Communities, Central Queensland University, Rockhampton, QLD, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Healthcare can be inappropriate and waste valuable and finite resources when it is not aligned to the needs and goals of patients. In mental health, although the importance of subjective experience and the patient's perspective is generally recognized, many current clinical measures do not reflect this. Mental health services might become more effective and efficient if the data being collected from patients more closely reflected patients' priorities and preferences. To promote embedded clinical research (EmCR) as well as leveraging its benefits, a service innovation was introduced to investigate the interchangeability of symptom ratings and botheredness ratings. A file audit examined routinely collected real-world data including ratings of impairment as well as ratings of botheredness from a clinical psychology outpatient clinic in a public mental health service. The Work and Social Adjustment Scale was modified and data from 61 files were analysed using resampling methods to explore associations between and interchangeability of the ratings. The data indicated that ratings of impairment and botheredness were strongly correlated. Null hypothesis significance testing, however, provided evidence that impairment and botheredness were not, in general, interchangeable. Current approaches to obtaining mental health information from patients might not be aligned with their priorities. These findings could have implications for making mental health services more effective and efficient by improving the extent to which service delivery is meaningful and useful to patients.

Indexed as

embedded clinical researchinappropriate healthcaremental health disordermental health servicespatient-perspective carepsychological distressresamplingsymptom questionnaire

Identifiers

PMID41788570
PMCPMC12957990

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.