Initiating artificial nutrition support: a clinical judgement analysis

A Test-Retest Reliability Generalization Meta-Analysis of Judgments Via the Policy-Capturing Technique

Policy capturing is a widely used technique, but the temporal stability of policy-capturing judgments has long been a cause for concern. This article emphasizes the importance of reporting reliability, and in particular test-retest reliability, estimates in policy-capturing studies. We found that only 164 of 955 policy-capturing studies (i.e., 17.17%) reported a test-retest reliability estimate. We then conducted a reliability generalization meta-analysis on policy-capturing studies that did report test-retest reliability estimates—and we obtained an average reliability estimate of .78. We additionally examined 16 potential methodological and substantive antecedents to test-retest reliability (equivalent to moderators in validity generalization studies). We found that test-retest reliability was robust to variation in 14 of the 16 factors examined but that reliability was higher in paper-and-pencil studies than in web-based studies and was higher for behavioral intention judgments than for other (e.g., attitudinal and perceptual) judgments. We provide an agenda for future research. Finally, we provide several best-practice recommendations for researchers (and journal reviewers) with regard to (a) reporting test-retest reliability, (b) designing policy-capturing studies for appropriate reportage, and (c) properly interpreting test-retest reliability in policy-capturing studies.

Using judgement analysis to identify dietitians' referral prioritisation for assessment in adult acute services

BACKGROUND/OBJECTIVES

Dietitians need to prioritise referrals in order to manage their work load. Novice dietitians may not receive training on prioritisation and could be helped with an evidence-based, effective decision-making training tool. To develop such a tool, it is necessary to understand how experts make prioritisation decisions. This study aimed to model expert decision-making policy for prioritising dietetic referrals in adult acute-care services.

METHODS/SUBJECTS

Social judgement theory was used to model expert decision-making policy. Informational cues and cue levels were identified. A set of case scenarios that replicated dietetic referrals in adult acute services were developed using fractional factorial design approach. Experienced dietitians were asked to make prioritisation decisions on case scenarios. A model was derived using multiple regression analysis to elicit the weighting given to cues and cue levels by the experts when making prioritisation decisions.

RESULTS

Six cues and 21 cue levels were identified, and 60 unique case scenarios were created. Fifty experienced dietitians made decisions on these case scenarios. The 'reason for referral' and 'biochemistry picture' were the two most influential cues, and 'weight history' was the least significant. 'Nutritional status', 'presenting complaint' and 'previous food intake' had similar weightings. In all, 95.7% of the variability in the experts' average judgement (adjusted R2=0.93) was predicted by the 6 cues.

CONCLUSIONS

A model for referral prioritisation in adult acute services described experienced dietitians' decision-making policy. This can be used to develop training materials that may increase the effectiveness and quality of prioritisation judgements.European Journal of Clinical Nutrition advance online publication, 23 August 2017; doi:10.1038/ejcn.2017.123.