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Record W2964434111 · doi:10.3389/fneur.2019.00892

Communication About OFF Periods in Parkinson's Disease: A Survey of Physicians, Patients, and Carepartners

2019· article· en· W2964434111 on OpenAlexaff
Tara Rastgardani, Melissa J. Armstrong, Anna R. Gagliardi, Arthur Grabovsky, Connie Marras

Bibliographic record

VenueFrontiers in Neurology · 2019
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsToronto General HospitalUniversity Health NetworkToronto Western HospitalUniversity of Toronto
FundersAcorda TherapeuticsMichael J. Fox Foundation for Parkinson's Research
KeywordsFacilitatorMedicineDiseaseParkinson's diseaseMotor symptomsQuality of life (healthcare)CognitionPsychologyFamily medicinePhysical therapyPsychiatryNursingSocial psychologyInternal medicine

Abstract

fetched live from OpenAlex

Background: OFF periods impair quality of life in Parkinson’s disease and are often amenable to treatment. Optimal treatment decisions rely on effective communication between physicians, patients and carepartners regarding this highly variable and complex phenomenon. Little is published in the literature about communication about OFF periods. Methods: Informed by interviews with physicians, patients and carepartners we designed questionnaires for each group. We surveyed these parties using an online platform to investigate the frequency, content and ease of communication about OFF periods and barriers and facilitators of communication with physicians.. Results: 50 movement disorder neurologists, 50 general neurologists, 442 patients and 97 carepartners participated. A free-flowing dialogue is the mainstay of communication according to all parties. Motor aspects of OFF periods are discussed more frequently than non-motor aspects (90% vs <50% according to both general neurologists and movement disorder neurologists). The most common physician-reported barriers to communication are patient cognitive impairment, patient difficulty recognizing OFF periods and poor patient understanding of OFF periods’ relationship to medication timing. The barriers most commonly cited as major by patients were that they perceived OFF periods to be part of the disease (i.e., not a clinical aspect that could be improved by a physician), variability of symptoms, and difficulty in describing symptoms. The most commonly described facilitator (by physicians) was the input of a caregiver. Positively viewed but less commonly used facilitators included pre-visit questionnaires or diaries, digital apps and wearable devices to monitor fluctuations. The majority of patients and carepartners identified a free-flowing dialogue with their physicians and having an agenda as helpful facilitators of communication about OFF periods which they already use. The majority of both groups felt that keeping a diary and pre-visit questionnaires were potentially helpful facilitators that were not currently in use. Conclusions: Perceived barriers and facilitators to communication about OFF periods are different between health care providers and receivers of health care. Modifiable barriers and facilitators that could be implemented were identified by both groups. Future research should develop and test strategies based on this input to optimize communication and thus clinical care for this common and debilitating problem.

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)0.002
metaresearch head score (Gemma)0.009
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 score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.008
GPT teacher head0.248
Teacher spread0.240 · 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

Citations16
Published2019
Admission routes1
Has abstractyes

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