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Record W7008901949

Consumer reported digital immunization records : feasibility, applicability, and public health utility in the Canadian context

2024· article· en· W7008901949 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Archive (Karolinska Institutet) · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsnot available
Fundersnot available
KeywordsImmunizationContext (archaeology)Public healthVaccinationmHealthPublic health surveillancePsychological intervention
DOInot available

Abstract

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Background: Vaccination is one of the most effective public health interventions of all time. Public health programs collect data on Vaccination Coverage (VC) to determine levels of protection and guide resource allocation for further vaccination campaigns but VC data completeness and utility is a challenge in many settings. Self-report is a sensitive and relatively specific indicator of vaccination status but incorporation into VC analyses is limited. Mobile technologies can enhance Immunization Information Systems, not least by facilitating bi-directional communications with individuals. This permits collection of self-reported immunization records and a channel to deliver reminders and reliable information back to individuals. However, evaluations of consumer apps for immunization are still nascent, often small-scale, and conducted most in controlled research environments. Aim: The overarching aim of this thesis is to shed light on the feasibility, public health utility and applicability of mHealth apps for recording, reporting, and encouraging immunization. Methods: Paper I was an ecological, quality-assurance study describing use of Pan- Canadian mobile immunization app for parental reporting of children’s primary immunization series in Ottawa, Ontario, Canada. Paper II was a single cohort interrupted time series analysis examining the impact of the COVID-19 pandemic in Canada on uptake of a Pan-Canadian mobile immunization app as well as parentally reported pneumococcal series completion rates at the child’s 13-months of age. Paper III was a cross-sectional study describing the characteristics of family/parental characteristics and their association of reporting vaccinating their children against influenza among Pan-Canadian mobile immunization app users in the 2018/2019 influenza season. Paper IV was a systematic review and meta-analysis examining effectiveness of digital push interventions compared to non-digital interventions at increasing vaccine uptake and series completion. Results: Feasibility and Acceptability: The first successful transmission of records occurred April 27, 2015 (Paper I). There were 63,833 pediatric records and 11,381 unique parent-child dyads that met inclusion criteria, respectively in Papers II and III. The onset of COVID-19 restrictions was associated with an abrupt and continued decline in enrollment of children in the app compared to expected values (Paper II). Public Health Utility: 530 (20%) of children were less than 12 months old when their record was first submitted via the app (Paper I). The onset of COVID-19 restrictions was associated with an initial increase in self-reported completion of pneumococcal series, followed by a modest decrease leading to a net effect of -20%, compared to expected values (Paper II). Influenza vaccination was reported for 32.3% (3,675/11,381) of children and 42.0% (4,788/11,381) of parents. Parents receiving the seasonal influenza vaccine was the most strongly associated characteristic with pediatric influenza vaccination (OR 17.05, 95% CI 15.08, 19.28) compared to parents who did not report being vaccinated against influenza that season (Paper III). Applicability: When comparing digital push with non-digital interventions, patients had 1.18 (95% CI 1.11, 1.25) the odds of receiving vaccination or series completion. Analyses had high statistical heterogeneity, but risk of bias was low (Paper IV). Conclusions: Through four studies, this thesis provided supportive evidence on the potential to mobile apps to enhance IIS. Successful transmission of self-reported immunization records to public health via mobile app was demonstrated to be feasible and acceptable. The onset of COVID-19 was associated with decreased app use and reported pediatric pneumococcal series completion. Parents receiving the seasonal influenza vaccine was associated with reporting their children as immunized. Receiving digital push notifications increases the odds of vaccine uptake and series completion. These studies are subject to limitations but show potential for mHealth apps to facilitate self-report of vaccination data, assess trends and associations in vaccine behavior and encourage immunization through push interventions. List of scientific papers I. Atkinson, K.M., El-Khatib, Z., Barnum, G., Bell, C., Turcotte, M.C., Murphy, M.S., Teitelbaum, M., Chakraborty, P., Laflamme, L. and Wilson, K., 2017. Using Mobile Apps to Communicate Vaccination Records: A City-wide Evaluation with a National Immunization App, Maternal Child Registry and Public Health Authorities. Healthcare Quarterly. 20(3), pp.41-46. https://doi.org/10.12927/hcq.2017.25289 II. Atkinson, K.M., Ntacyabukura, B., Hawken, S., Laflamme, L. and Wilson, K., 2022. Effects of the COVID-19 pandemic on selfreported 12-month pneumococcal vaccination series completion rates in Canada. Human Vaccines & Immunotherapeutics. 18(7), p.2158005. https://doi.org/10.1080/21645515.2022.2158005 III. Atkinson, K.M., Ntacyabukura, B., Hawken, S., El-Khatib, Z., Laflamme, L., Wilson, K. Parent and family characteristics associated with selfreported uptake of pediatric influenza vaccine in a sample of Canadian digital vaccination platform users. A cross-sectional study. [Submitted] IV. Atkinson, K.M., Wilson, K., Murphy, M.S., El-Halabi, S., Kahale, L.A., Laflamme, L.L. and El-Khatib, Z., 2019. Effectiveness of digital technologies at improving vaccine uptake and series completion–A systematic review and meta-analysis of randomized controlled trials. Vaccine. 37(23), pp.3050-3060. https://doi.org/10.1016/j.vaccine.2019.03.063

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)0.026
metaresearch head score (Gemma)0.098
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score0.760

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.098
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.014
Science and technology studies0.0070.003
Scholarly communication0.0080.003
Open science0.0040.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.103
GPT teacher head0.366
Teacher spread0.263 · 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 designObservational
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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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