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Record W3206295173 · doi:10.2196/17568

A Self-help Tool to Facilitate Implementation of eHealth Initiatives in Health Care (E-Ready): Formative Evaluation

2021· article· en· W3206295173 on OpenAlexvenueno aff
Petra Dannapfel, Kristin Thomas, Alexander Chakhunashvili, Jeanette Melin, Ylva Trolle Lagerros

Bibliographic record

VenueJMIR Formative Research · 2021
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordseHealthFormative assessmentPreprintHealth careRasch modelStatus quoPsychologyMedical educationPsychological interventionKnowledge managementApplied psychologyNursingMedicineComputer sciencePolitical sciencePedagogy

Abstract

fetched live from OpenAlex

BACKGROUND: eHealth interventions have the potential to increase the efficiency and effectiveness of health care. However, research has shown that implementing eHealth in routine health care practice is difficult. Organizational readiness to change has been shown to be central to successful implementation. This paper describes the development and formative evaluation of a generic self-help tool, E-Ready, designed to be used by managers, project leaders, or others responsible for implementation in a broad range of health care settings. OBJECTIVE: The aim of this study is to develop and evaluate a tool that could facilitate eHealth implementation in, for example, health care. METHODS: A first version of the tool was generated based on implementation theory (E-Ready 1.0). A formative evaluation was undertaken through expert panels (n=15), cognitive interviews (n=17), and assessment of measurement properties on E-Ready items from 3 different workplaces (n=165) using Rasch analyses. E-Ready 1.0 was also field tested among the target population (n=29). Iterative revisions were conducted during the formative evaluation process, and E-Ready 2.0 was generated. RESULTS: The E-Ready Tool consists of a readiness assessment survey and a hands-on manual. The survey measures perceived readiness for change (willingness and capability) at individual and collective levels: perceived conditions for change at the workplace, perceived individual conditions for change, perceived support and engagement among management, perceived readiness among colleagues, perceived consequences on status quo, and perceived workplace attitudes. The manual contains a brief introduction, instructions on how to use the tool, information on the themes of E-Ready, instructions on how to create an implementation plan, brief advice for success, and tips for further reading on implementation theory. Rasch analyses showed overall acceptable measurement properties in terms of fit validity. The subscale Individual conditions for change (3 items) had the lowest person reliability (0.56), whereas Perceived consequences on status quo (5 items) had the highest person reliability (0.87). CONCLUSIONS: E-Ready 2.0 is a new self-help tool to guide implementation targeting health care provider readiness and engagement readiness ahead of eHealth initiatives in, for example, health care settings. E-Ready can be improved further to capture additional aspects of implementation; improvements can also be made by evaluating the tool in a larger sample.

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)0.004
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.320
Threshold uncertainty score0.830

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.236
GPT teacher head0.590
Teacher spread0.354 · 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 designQualitative
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

Citations21
Published2021
Admission routes1
Has abstractyes

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