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Record W2260676932 · doi:10.3402/gha.v9.30337

Communication strategies to promote the uptake of childhood vaccination in Nigeria: a systematic map

2016· article· en· W2260676932 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGlobal Health Action · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsInternational Society for Equity in HealthCentre for Global Health Research
FundersMedical Research CouncilNorges ForskningsrådSouth African Medical Research Council
KeywordsPsychological interventionHealth communicationIntervention (counseling)VaccinationPublic relationsPsychologyMedicineMedical educationPolitical scienceNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Effective communication is a critical component in ensuring that children are fully vaccinated. Although numerous communication interventions have been proposed and implemented in various parts of Nigeria, the range of communication strategies used has not yet been mapped systematically. This study forms part of the 'Communicate to vaccinate' (COMMVAC) project, an initiative aimed at building research evidence for improving communication with parents and communities about childhood vaccinations in low- and middle-income countries. OBJECTIVE: This study aims to: 1) identify the communication strategies used in two states in Nigeria; 2) map these strategies against the existing COMMVAC taxonomy, a global taxonomy of vaccination communication interventions; 3) create a specific Nigerian country map of interventions organised by purpose and target; and 4) analyse gaps between the COMMVAC taxonomy and the Nigerian map. DESIGN: We conducted the study in two Nigerian states: Bauchi State in Northern Nigeria and Cross River State in Southern Nigeria. We identified vaccination communication interventions through interviews carried out among purposively selected stakeholders in the health services and relevant agencies involved in vaccination information delivery; through observations and through relevant documents. We used the COMMVAC taxonomy to organise the interventions we identified based on the intended purpose of the communication and the group to which the intervention was targeted. RESULTS: The Nigerian map revealed that most of the communication strategies identified aimed to inform and educate and remind or recall. Few aimed to teach skills, enhance community ownership, and enable communication. We did not identify any intervention that aimed to provide support or facilitate decision-making. Many interventions had more than one purpose. The main targets for most interventions were caregivers and community members, with few interventions directed at health workers. Most interventions identified were used in the context of campaigns rather than routine immunisation programmes. CONCLUSIONS: The identification and development of the Nigerian vaccination communication interventions map could assist programme managers to identify gaps in vaccination communication. The map may be a useful tool as part of efforts to address vaccine hesitancy and improve vaccination coverage in Nigeria and similar settings.

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)0.001
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 score0.910
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.024
GPT teacher head0.363
Teacher spread0.339 · 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