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Record W2970503287 · doi:10.1017/s1041610219001200

Profile of mild behavioral impairment and factor structure of the Mild Behavioral Impairment Checklist in cognitively normal older adults

2019· article· en· W2970503287 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Psychogeriatrics · 2019
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of Calgary
FundersKing's College LondonNational Institute for Health and Care ResearchDepartment of Health and Social CareSouth London and Maudsley NHS Foundation Trust
KeywordsPsychologyChecklistClinical psychologyAnxietyMoodPopulationRespondentExploratory factor analysisPsychiatryPsychometricsMedicine

Abstract

fetched live from OpenAlex

OBJECTIVES: In this large population study, we set out to examine the profile of mild behavioral impairment (MBI) by using the Mild Behavioral Impairment Checklist (MBI-C) and to explore its factor structure when employed as a self-reported and informant-rated tool. DESIGN: This was a population-based cohort study. SETTING: Participants were recruited from the Platform for Research Online to Investigate Genetics and Cognition in Aging study (https://www.protect-exeter.org.uk). PARTICIPANTS: A total of 5,742 participant-informant dyads participated in the study. MEASUREMENTS: Both participants and informants completed the MBI-C. The factor structure of the MBI-C was evaluated by exploratory factor analysis. RESULTS: The most common MBI-C items, as rated by self-reported and informants, related to affective dysregulation (mood/anxiety symptoms), being present in 34% and 38% of the sample, respectively. The least common items were those relating to abnormal thoughts and perception (psychotic symptoms) (present in 3% and 6% of the sample, respectively). Only weak correlations were observed between self-reported and informant-reported MBI-C responses. Exploratory factor analysis for both sets of respondent answers indicated that a five-factor solution for the MBI-C was appropriate, reflecting the hypothesized structure of the MBI-C. CONCLUSION: This is the largest and most detailed report on the frequency of MBI symptoms in a nondementia sample. The full spectrum of MBI symptoms was present in our sample, whether rated by self-reported or informant report. However, we show that the MBI-C performs differently in self-reported versus informant-reported situations, which may have important implications for the use of the questionnaire in clinic and research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.330
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it