MétaCan
Menu
Back to cohort
Record W6977582061 · doi:10.6084/m9.figshare.c.3888982

Intermittent auscultation versus continuous fetal monitoring: exploring factors that influence birthing unit nurses’ fetal surveillance practice using theoretical domains framework

2017· other· en· W6977582061 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2017
Typeother
Languageen
FieldSocial Sciences
TopicDemographic Trends and Gender Preferences
Canadian institutionsnot available
Fundersnot available
KeywordsUnit (ring theory)Context (archaeology)Intervention (counseling)AuscultationElectronic fetal monitoringFetal heart rate

Abstract

fetched live from OpenAlex

Abstract Background Intermittent Auscultation (IA) is the recommended method of fetal surveillance for healthy women in labour. However, the majority of women receive continuous electronic monitoring. We used the Theoretical Domains Framework (TDF) to explore the views of Birthing Unit nurses about using IA as their primary method of fetal surveillance for healthy women in labour. Methods Using a semi-structured interview guide, we interviewed a convenience sample of birthing unit nurses throughout Ontario, Canada to elicit their views about fetal surveillance. Interviews were recorded and transcribed verbatim. Transcripts were content analysed using the TDF and themes were framed as belief statements. Domains potentially key to changing fetal surveillance behaviour and informing intervention design were identified by noting the frequencies of beliefs, content, and their reported influence on the use of IA. Results We interviewed 12 birthing unit nurses. Seven of the 12 TDF domains were perceived to be key to changing birthing unit nurses’ behaviour The nurses reported that competing tasks, time constraints and the necessity to multitask often limit their ability to perform IA (domains Beliefs about capabilities; Environmental context and resources). Some nurses noted the decision to use IA was something that they consciously thought about with every patient while others stated it their default decision as long as there were no risk factors (Memory, attention and decision processes, Nature of behaviour). They identified positive consequences (e.g. avoid unnecessary interventions, mother-centered care) and negative consequences of using IA (e.g. legal concerns) and reported that the negative consequences can often outweigh positive consequences (Beliefs about consequences). Some reported that hospital policies and varying support from care teams inhibited their use of IA (Social influences), and that support from the entire team and hospital management would likely increase their use (Social influences; Behavioural regulation). Conclusion We identified potential influences on birthing unit nurses’ use of IA as their primary method of fetal surveillance. These beliefs suggest potential targets for behaviour change interventions to promote IA use.

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)0.000
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.941
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.000

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 head0.169
GPT teacher head0.392
Teacher spread0.223 · 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.

Study designNot applicable
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

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueFigshareSame topicDemographic Trends and Gender PreferencesFrench-language works237,207