Evidence map›Paper›PMID 39366985›Full record

ArticleSchizophrenia (Heidelberg, Germany)2024

A generalisability theory approach to quantifying changes in psychopathology among ultra-high-risk individuals for psychosis.

Zohreh Doborjeh, Oleg N Medvedev, Maryam Doborjeh, Balkaran Singh, Alexander Sumich, Sugam Budhraja, Wilson Wen Bin Goh, Jimmy Lee, Margaret Williams, Edmund M-K Lai and 1 more

Abstract read
In one paragraph

Article in Schizophrenia (Heidelberg, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

11 authors.

Zohreh DoborjehKnowledge Engineering and Discovery Research Institute, School of Engineering, Computer, and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand. zohreh.doborjeh@aut.ac.nz.ORCID http://orcid.org/0000-0003-1431-8258
Oleg N MedvedevSchool of Psychological and Social Sciences, The University of Waikato, Hamilton, New Zealand.
Maryam DoborjehKnowledge Engineering and Discovery Research Institute, School of Engineering, Computer, and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand.
Balkaran SinghKnowledge Engineering and Discovery Research Institute, School of Engineering, Computer, and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand.
Alexander SumichNTU Psychology, School of Social Sciences, Nottingham Trent University, Nottingham, United Kingdom.ORCID http://orcid.org/0000-0003-4333-8442
Sugam BudhrajaKnowledge Engineering and Discovery Research Institute, School of Engineering, Computer, and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand.
Wilson Wen Bin GohLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore. wilsongoh@ntu.edu.sg.
Jimmy LeeLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.ORCID http://orcid.org/0000-0002-7724-7445
Margaret WilliamsSchool of Public Health and Interdisciplinary Studies, Auckland University of Technology, Auckland, New Zealand.ORCID http://orcid.org/0000-0001-8798-2550
Edmund M-K LaiKnowledge Engineering and Discovery Research Institute, School of Engineering, Computer, and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand.ORCID http://orcid.org/0000-0001-9159-3718
Nikola KasabovKnowledge Engineering and Discovery Research Institute, School of Engineering, Computer, and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand.ORCID http://orcid.org/0000-0003-4433-7521

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Distinguishing stable and fluctuating psychopathological features in young individuals at Ultra High Risk (UHR) for psychosis is challenging, but critical for building robust, accurate, early clinical detection and prevention capabilities. Over a 24-month period, 159 UHR individuals were assessed using the Positive and Negative Symptom Scale (PANSS). Generalisability Theory was used to validate the PANSS with this population and to investigate stable and fluctuating features, by estimating the reliability and generalisability of three factor (Positive, Negative, and General) and five factor (Positive, Negative, Cognitive, Depression, and Hostility) symptom models. Acceptable reliability and generalisability of scores across occasions and sample population were demonstrated by the total PANSS scale (Gr = 0.85). Fluctuating symptoms (delusions, hallucinatory behaviour, lack of spontaneity, flow in conversation, emotional withdrawal, and somatic concern) showed high variability over time, with 50-68% of the variance explained by individual transient states. In contrast, more stable symptoms included excitement, poor rapport, anxiety, guilt feeling, uncooperativeness, and poor impulse control. The 3-factor model of PANSS and its subscales showed robust reliability and generalisability of their assessment scores across the UHR population and evaluation periods (G = 0.77-0.93), offering a suitable means to assess psychosis risk. Certain subscales within the 5-factor PANSS model showed comparatively lower reliability and generalisability (G = 0.33-0.66). The identified and investigated fluctuating symptoms in UHR individuals are more amendable by means of intervention, which could have significant implications for preventing and addressing psychosis. Prioritising the treatment of fluctuating symptoms could enhance intervention efficacy, offering a sharper focus in clinical trials. At the same time, using more reliable total scale and 3 subscales can contribute to more accurate assessment of enduring psychosis patterns in clinical and experimental settings.

Identifiers

PMID39366985
PMCPMC11452639

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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.