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Record W4211096105 · doi:10.3389/fnagi.2022.838674

Divergence Between Informant and Self-Ratings of Activities of Daily Living Impairments in Parkinson’s Disease

2022· article· en· W4211096105 on OpenAlexaff
Sara Becker, Susanne Solbrig, Katja Michaelis, Bettina Faust, Kathrin Brockmann, Inga Liepelt‐Scarfone

Bibliographic record

VenueFrontiers in Aging Neuroscience · 2022
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversity of Calgary
FundersEberhard Karls Universität TübingenMichael J. Fox Foundation for Parkinson's Research
KeywordsActivities of daily livingCognitionDementiaDepression (economics)PsychologyDiseaseMedicineClinical psychologyPhysical therapyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Objective To examine the agreement between self- and informant-reported activities of daily living (ADL) deficits in Parkinson’s Disease (PD) patients, and to examine factors influencing ADL ratings. Background In PD, the loss of functional independence is an important outcome of disease progression. The valid assessment of ADL function in PD is essential, but it is unclear to what extent informants’ and patients’ perceptions of their daily functions concur, and how other factors may influence both ratings. Methods Data of 150 PD patients who underwent cognitive and motor testing, as well as their informants were analyzed. The 10-item Functional Activities Questionnaire (FAQ), completed separately by patients (FAQ-S) and their informants (FAQ-I), assessed ADL function. Weighted κ statistics summarized level of agreement, and a discrepancy score (FAQ-I – FAQ-S) quantified agreement. Correlation analyses between FAQ total scores, patient and informant characteristics, and cognitive scores were conducted, with post hoc regressions to determine the associations between both FAQ scores and cognition, independent of patient characteristics. Results The sample included 87 patients with normal cognition, 50 with mild cognitive impairment, and 13 with dementia. Overall, there was fair to moderate agreement between patients and informants on individual FAQ items (0.27 ≤ κ ≤ 0.61, p < 0.004), with greater discrepancies with increasing cognitive impairment. Patients’ age, motor severity, non-motor burden, and depression also affected both ratings (0.27 ≤ r ≤ 0.50, p < 0.001), with motor severity showing the greatest influence on both ratings. Both the FAQ-I and FAQ-S were correlated with almost all cognitive domains. Post hoc regression analyses controlling for patient characteristics showed that the attention domain was a significant predictor of both the FAQ-S and FAQ-I scores, and memory was also a significant predictor of the FAQ-I score. Only 29.3% of patients agreed perfectly with informants on the FAQ total score, with informants most commonly rating ADL impairments as more severe than patients. Conclusions Patient and informant ratings of ADL function using FAQ items showed moderate agreement, with only few items reaching substantial agreement. Ratings of both were associated with patient cognitive status, but also other characteristics. In addition to patient and informant reports, objective measures are needed to accurately classify ADL deficits in PD.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.038
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.244
Teacher spread0.233 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2022
Admission routes1
Has abstractyes

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