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Record W4226276633 · doi:10.2196/35425

Online Peer Support for People With Parkinson Disease: Narrative Synthesis Systematic Review

2022· review· en· W4226276633 on OpenAlexvenueno aff
Esther Vera Gerritzen, Abigail Rebecca Lee, Orii McDermott, Neil Coulson, Martin Orrell

Bibliographic record

VenueJMIR Aging · 2022
Typereview
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsnot available
FundersHorizon 2020 Framework ProgrammeMarie CurieNational Institute for Health and Care Research
KeywordsLonelinessSocial supportPsychosocialPsychologyChecklistPeer reviewSocial isolationSystematic reviewAnonymityCoping (psychology)Peer supportMedical educationApplied psychologyClinical psychologyMedicineMEDLINESocial psychologyComputer sciencePsychiatryPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Parkinson disease (PD) significantly impacts the lives of people with the diagnosis and their families. In addition to the physical symptoms, living with PD also has an emotional impact. This can result in withdrawal from social roles, increasing the risk for social isolation and loneliness. Peer support is a way to stay socially connected, share experiences, and learn new coping skills. Peer support can be provided both in person and on the internet. Some of the advantages of online peer support are that it overcomes geographical barriers and provides a form of anonymity; moreover, support can be readily available when needed. However, the psychosocial impact of PD is still underresearched, and there is no systematic synthesis of online peer support for people with PD. OBJECTIVE: This review aims to explore the benefits and challenges of online peer support and identify successful elements of online peer support for people with PD. METHODS: The method selected for this systematic review is narrative synthesis. A total of 6 databases were systematically searched in April 2020 for articles published between 1989 and 2020. The quality of the included studies was assessed using the Critical Appraisal Skills Programme qualitative research checklist and the Downs and Black quality checklist. RESULTS: A total of 10,987 unique articles were identified through a systematic database search. Of these 10,987 articles, 8 (0.07%) were included in this review. Of the 8 studies, 5 (63%) were of good or high quality, 2 (25%) were of medium or fair quality, and 1 (13%) study was of poor quality. Web-based platforms included discussion forums, a web-based virtual world, and Facebook groups. Most papers reported on text-based communication. The included studies reported on sharing social support and personal experiences. Successful elements included increasing similarity between members and offering the opportunity to directly ask questions to a physician. Challenges included members leaving without a warning and PD symptoms hindering the use of technology. CONCLUSIONS: Peer support can improve social support and help people with PD in living meaningful and satisfying lives. Peer support is unique and cannot be replaced by family members, friends, or health care professionals. Online peer support can be a solution for those who do not have access to an in-person support group or whose PD symptoms restrict them from travelling. However, research on the personal experiences of those who engage in online peer support and potential barriers in accessing it remains limited. Future research could use qualitative methods to explore these fields further.

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)0.016
metaresearch head score (Gemma)0.090
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.090
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.006
Bibliometrics0.0110.011
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0020.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.241
GPT teacher head0.488
Teacher spread0.246 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations40
Published2022
Admission routes1
Has abstractyes

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