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Record W1983989358 · doi:10.1111/bjhp.12066

Comparison of four methods for assessing the importance of attitudinal beliefs: An international <scp>D</scp> elphi study in intensive care settings

2013· article· en· W1983989358 on OpenAlexafffundabout
Jill Francis, Eilidh Duncan, Maria Prior, Graeme MacLennan, Andrea P. Marshall, Elisabeth C. Wells, Laura Todd, Louise Rose, Marion Campbell, Fiona Webster, Martin Eccles, Geoff Bellingan, Ian Seppelt, Jeremy Grimshaw, Brian H. Cuthbertson

Bibliographic record

VenueBritish Journal of Health Psychology · 2013
Typearticle
Languageen
FieldMedicine
TopicNosocomial Infections in ICU
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreOttawa HospitalUniversity of OttawaUniversity of TorontoUniversity of Guelph
FundersMedical Research CouncilCanadian Institutes of Health ResearchIntensive Care SocietyNational Institute for Health and Care ResearchAustralian and New Zealand College of AnaesthetistsHealth Technology Assessment ProgrammeScottish GovernmentChief Scientist Office, Scottish Government Health and Social Care DirectorateGroupe canadien de recherche en soins intensifsIntensive Care Foundation
KeywordsLikert scaleDelphi methodPsychologyPsychological interventionBivariate analysisClinical psychologyMedicineSocial psychologyStatisticsDevelopmental psychologyMathematicsPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVES: Behaviour change interventions often target 'important' beliefs. The literature proposes four methods for assessing importance of attitudinal beliefs: elicitation frequency, importance ratings, and strength of prediction (bivariate and multivariate). We tested congruence between these methods in a Delphi study about selective decontamination of the digestive tract (SDD). SDD improves infection rates among critically ill patients, yet uptake in intensive care units is low internationally. METHODS: A Delphi study involved three iterations ('rounds'). Participants were 105 intensive care clinicians in the United Kingdom, Canada, and Australia/New Zealand. In Round 1, semi-structured interviews were conducted to elicit beliefs about delivering SDD. In Rounds 2 and 3, participants completed questionnaires, rating agreement and importance for each belief-statement (9-point Likert scales). Belief importance was assessed using elicitation frequency, mean importance ratings, and prediction of global attitude (Pearson's correlations; beta-weights). Correlations between indices were computed. RESULTS: Participants generated 14 attitudinal beliefs. Indices had adequate variation (frequencies: 4-94, mean importance ratings: 4.93-8.00, Pearson's correlations: ± 0.09 to ± 0.54, beta-weights: ± 0.01 to ± 0.30). SDD increases antibiotic resistance was the most important belief according to three methods and was ranked second by beta-weights (behind Overall, SDD benefits patients to whom it is delivered). Spearman's correlations were significant for importance ratings with frequencies and correlations. However, other indices were unrelated. The top four beliefs differed according to the measure used. CONCLUSIONS: Results provided evidence of congruence across three methods for assessing belief importance. Beta-weights were unrelated to other indices, suggesting that they may not be appropriate as the sole method. STATEMENT OF CONTRIBUTION: What is already known on this subject? Attitudinal beliefs (specific beliefs about the consequences of performing an action) are key to designing interventions to change intentions and behaviour. The literature reports four methods for assessing the importance of attitudinal beliefs: frequency of elicitation in interviews, importance ratings in questionnaires, and strength of prediction (bivariate and multivariate) of global attitude scores. The congruence between these measures of importance is not known. What does this study add? Four indices of importance were examined in a multi-professional, international study about the use of selective digestive decontamination to prevent infection in intensive care settings. Three indices were correlated with one another. Each method used to assess importance produced a different subset of the most important beliefs. Selection of the most important beliefs should use multiple assessment methods. This evidence suggests that multiple regression approaches may not be appropriate as the sole method for assessing belief importance.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.068
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.146
GPT teacher head0.566
Teacher spread0.421 · 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.

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".

Quick stats

Citations17
Published2013
Admission routes3
Has abstractyes

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