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Record W4323361321 · doi:10.2196/45920

Acceptability and Initial Adoption of the Heart Observation App for Infants With Congenital Heart Disease: Qualitative Study

2023· article· en· W4323361321 on OpenAlexvenueno aff
Elin Hjorth‐Johansen, Elin Børøsund, Ingeborg Martinsen Østen, Henrik Holmstrøm, Anne Moen

Bibliographic record

VenueJMIR Formative Research · 2023
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsnot available
Fundersnot available
KeywordsThematic analysisComprehensionMedicineHeart diseaseNursingQualitative researchHealth careCoping (psychology)PsychologyFamily medicineDevelopmental psychologyClinical psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Approximately 1% of all infants are born with a congenital heart disease (CHD). Internationally CHD remains a major cause of infant death, some of which occur unexpectedly after a gradual deterioration at home. Many parents find it difficult to recognize worsening of symptoms. OBJECTIVE: This study aims to report the acceptability and initial adoption of a mobile app, the Heart Observation app (HOBS), aiming to support parents' understanding and management of their child's condition and to increase quality in follow-up from health care professionals in complex health care services in Norway. METHODS: A total of 9 families were interviewed on discharge from the neonatal intensive care unit and after 1 month at home. The infant's primary nurse, community nurse, and cardiologist were also interviewed regarding their experiences about collaboration with the family. The interviews were analyzed inductively with thematic content analysis. RESULTS: The analysis generated 4 main themes related to acceptability and adoption: (1) Individualize Initial Support, (2) Developing Confidence and Coping, (3) Normalize When Appropriate, and (4) Implementation in a Complex Service Pathway. The receptivity of parents to learn and attend in the intervention differs according to their present situation. Health care professionals emphasized the importance of adapting the introduction and guidance to parents' receptivity to ensure comprehension, self-efficacy, and thereby acceptance before discharge (Individualize Initial Support). Parents perceived that HOBS served them well and nurtured confidence by teaching them what to be aware of. Health care professionals reported most parents as confident and informed. This potential effect increased the possibility of adoption (Developing Confidence and Coping). Parents expressed that HOBS was not an "everyday app" and wanted to normalize everyday life when appropriate. Health care professionals suggested differentiating use according to severity and reducing assessments after recovery to adapt the burden of assessments when appropriate (Normalize When Appropriate). Health care professionals' attitude to implement HOBS in their services was positive. They perceived HOBS as useful to systemize guidance, to enhance communication regarding an infant's condition, and to increase understanding of heart defects in health care professionals with sparse experience (Implementation in a Complex Service Pathway). CONCLUSIONS: This feasibility study shows that both parents and health care professionals found HOBS as a positive addition to the health care system and follow-up. HOBS was accepted and potentially useful, but health care professionals should guide parents initially to ensure comprehension and adapt timing to parents' receptivity. By doing so, parents may be confident to know what to look for regarding their child's health and cope at home. Differentiating between various diagnoses and severity is important to support normalization when appropriate. Further controlled studies are needed to assess adoption, usefulness, and benefits in the health care system.

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)0.014
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.014
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.028
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.131
GPT teacher head0.485
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 source (direct Gemma or distilled Codex), 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

Citations4
Published2023
Admission routes1
Has abstractyes

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