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Record W3080195164 · doi:10.2196/20730

Ease of Use of the Electroconvulsive Therapy App by Its Users: Cross-Sectional Questionnaire Study

2020· article· en· W3080195164 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJMIR Biomedical Engineering · 2020
Typearticle
Languageen
FieldMedicine
TopicElectroconvulsive Therapy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthMedicineComputer-assisted web interviewingGeneral partnershipService (business)PsychologyPsychiatry

Abstract

fetched live from OpenAlex

Background Electroconvulsive therapy (ECT) is one of the oldest, most effective, and potentially life-saving noninvasive brain stimulation treatments for psychiatric illnesses such as severe depression, mania, and catatonia. The decision-making process to use ECT involves well-informed discussion between the clinician and the client. A platform, like an app, which provides this information in an easy-to-understand format may be of benefit to various stakeholders in making an informed decision. Apps developed by clinicians/hospitals taking into consideration user perspectives will filter and provide trustworthy information to the users. In this regard, the ECT app, an app which is freely available for download at the Apple Store, was developed by the Leicestershire Partnership National Health Service (NHS) Trust and Leicestershire Health Informatics Service (LHIS). Objective The objective of this study is to evaluate and demonstrate the accessibility of the ECT app to the chosen audiences it was created for, via a paper and electronic questionnaire. Methods A survey was conducted between January 2017 and March 2019. A survey questionnaire designed for the study was sent to mental health professionals, medical students, patients, carers, and members of the public via post, email, and SurveyMonkey or informed via posts shared in Psychiatry online groups and face-to-face contact. All participants who were willing to participate in the study were included. Results Results were collected via paper forms, email responses, and SurveyMonkey and all were inputted into SurveyMonkey to facilitate analysis. A total of 20 responses were received during the study period (January 2017 to March 2019). The participants of the survey, which included a mixed group of professionals (12/20, 60%), patients (3/20, 15%), and carers (1/20, 5%), opined that the app was easy to download (14/20, 70%) and use (9/20, 45%); contained adequate information (19/20, 95%); they felt more informed after having used the app (9/20, 45%); and they would recommend it to others (19/20, 95%). The participants of the survey also provided suggestions on the app (10/20, 50%). Conclusions The ECT app can be beneficial in sharing appropriate information to professionals and the public alike and help in gathering unbiased and nonjudgmental information on the current use of ECT as a treatment option.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score0.621

Codex and Gemma teacher scores by category

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

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 head0.025
GPT teacher head0.297
Teacher spread0.271 · 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