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A longitudinal study on quality of life and depression in ALS patient–caregiver couples

2007· article· nl· W2011506008 on OpenAlexaboutno aff
A. Gauthier, A. Vignola, Andrea Calvo, Enrico Cavallo, Cristina Moglia, L. Sellitti, Roberto Mutani, Adriano Chiò

Bibliographic record

VenueNeurology · 2007
Typearticle
Languagenl
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsnot available
Fundersnot available
KeywordsDepression (economics)Quality of life (healthcare)PsychologyLongitudinal studyMedicinePsychiatryClinical psychologyGerontologyPsychotherapist

Abstract

fetched live from OpenAlex

OBJECTIVES: To evaluate the modification of quality of life (QoL) and depression in a series of amyotrophic lateral sclerosis (ALS) patient-caregiver couples during a period of 9 months and compare them to patients' ALS Functional Rating Scale (ALS-FRS). METHODS: Depression was assessed with Zung Depression Scale (ZDS) and QoL with McGill Quality of Life Questionnaire (MQoL). Caregivers' burden was assessed with Caregiver Burden Inventory (CBI), and patients' feeling to be a burden with the Self-Perceived Burden Scale (SPBS). RESULTS: Thirty-one ALS patient-caregiver couples were interviewed at baseline and after 9 months. The mean ALS-FRS score was 28.7 (SD 7) at baseline and 24.1 (6.9) at the second interview (p = 0.0001). Patients' mean MQoL score slightly increased from 6.8 (1.6) to 7 (1.1) (p = 0.07); their ZDS score slightly increased (43.2 [8.7] at baseline and 45.7 [9.3] at the second interview) but they remained in the not depressed range. Caregivers' mean MQoL score slightly decreased, and their mean ZDS increased from 38.9 (8.1) to 42.2 (8.7) (p = 0.02). The mean CBI score increased from 50.3 (17.6) to 55.8 (16.4) (p = 0.03). CONCLUSIONS: We found a substantial steadiness of quality of life and depression in patients with amyotrophic lateral sclerosis over a 9-month period, vs a significant increase of burden and depression of their caregivers.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.008
Threshold uncertainty score0.742

Codex and Gemma teacher scores by category

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

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 head0.094
GPT teacher head0.379
Teacher spread0.285 · 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 teacher head, 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

Citations257
Published2007
Admission routes1
Has abstractyes

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