Evidence map›Paper›PMID 39600394›Full record

ArticleDigital health

Comparative insights into clinic onboarding and interaction practices for patient engagement in long COVID digital health care.

Hadiza Ismaila, Ann Blandford, David Sunkersing, Fiona Stevenson, Henry Goodfellow

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Hadiza IsmailaDepartment of Primary Care and Population Health, University College London, London, UK.ORCID https://orcid.org/0009-0004-5852-1543
Ann BlandfordDepartment of Computer Science, UCLIC, University College London, London, UK.ORCID https://orcid.org/0000-0002-3198-7122
David SunkersingInstitute of Health Informatics, University College London, London, UK.
Fiona StevensonDepartment of Primary Care and Population Health, University College London, London, UK.
Henry GoodfellowDepartment of Primary Care and Population Health, University College London, London, UK.ORCID https://orcid.org/0000-0002-0979-2839

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: This study explores the influence of clinic-led onboarding and interaction processes on patient engagement within a digital health program for long COVID care, the Living with COVID Recovery (LWCR) program. We compared clinical practices and patient engagement levels across seven clinics utilising LWCR, gaining insights that could optimise digital health interventions (DHIs) for long COVID care. Methods: Using a mixed-methods approach, we conducted qualitative interviews with clinicians from seven clinics (out of thirty five) to understand their onboarding and interaction strategies for the LWCR program. We also performed a descriptive quantitative analysis of patient and clinic usage data to rank and classify patient engagement. These rankings were then compared against qualitative insights to explore the influence of clinic-led strategies on patient engagement. Additionally, we conducted interviews with 12 patients under the care of seven clinics to complement our mixed-method analysis. Results: Four key practices were identified in clinics with higher patient engagement: pre-assessment onboarding, proactive communication, patient education and the involvement of clinically experienced staff. Clinics that integrated these interdependent practices into a cohesive strategy demonstrated notably higher patient engagement levels. Conclusion: This study highlights the critical role of integrating multiple, interdependent clinic-led strategies to optimise patient engagement in DHIs, particularly for long COVID care. These findings provide actionable insights for healthcare providers and policymakers, suggesting that a comprehensive approach is essential for maximising patient engagement and improving care outcomes. The study lays the groundwork for future research to explore the broader applicability of these strategies across different healthcare contexts.

Indexed as

apps < personalised medicinechronic < diseasedigital health < generalMixed methods < studiespublic health < diseaseremote patient monitoring < personalised medicinetelehealth < general

Identifiers

PMID39600394
PMCPMC11590151

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.