Evidence map›Paper›PMID 33196666›Full record

ArticlePloS one2020

Interrogative suggestibility in the elderly.

Silvia Biondi, Cristina Mazza, Graziella Orrù, Merylin Monaro, Stefano Ferracuti, Eleonora Ricci, Alberto Di Domenico, Paolo Roma

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 1 country.

Silvia BiondiDepartment of Human Neuroscience, Faculty of Medicine and Dentistry, Sapienza University of Rome, Rome, Italy.
Cristina MazzaDepartment of Neuroscience, Imaging and Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy.
Graziella OrrùDepartment of Surgical, Medical, Molecular & Critical Area Pathology, University of Pisa, Pisa, Italy.
Merylin MonaroDepartment of General Psychology, University of Padova, Padova, Italy.
Stefano FerracutiDepartment of Human Neuroscience, Faculty of Medicine and Dentistry, Sapienza University of Rome, Rome, Italy.
Eleonora RicciDepartment of Human Neuroscience, Faculty of Medicine and Dentistry, Sapienza University of Rome, Rome, Italy.
Alberto Di DomenicoDepartment of Psychological, Health, and Territorial Sciences, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy.
Paolo RomaDepartment of Human Neuroscience, Faculty of Medicine and Dentistry, Sapienza University of Rome, Rome, Italy.ORCID 0000-0002-1031-0948
Sapienza University of Rome · ITUniversity of Chieti-Pescara · ITUniversity of Padua · ITUniversity of Pisa · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Interrogative suggestibility (IS) describes the extent to which an individual behavioral response is affected by messages communicated during formal questioning within a closed social interaction. The present study aimed at improving knowledge about IS in the elderly (aged 65 years and older), in particular about its association with both emotive/affective and cognitive variables. The sample (N = 172) was divided into three groups on the basis of age: late adult (aged 55-64, N = 59), young elderly (aged 65-74, N = 63), and elderly (aged 75 and older, N = 50). Cognitive (i.e., Kaufman Brief Intelligence Test-2, Rey Auditory Verbal Learning Test), emotive/affective (i.e., Rosenberg Self-Esteem Scale, Marlowe-Crowne Social Desirability Scale, Penn State Worry Questionnaire) and suggestibility measures (i.e., Gudjonsson Suggestibility Scale-2) were administered. In order to identify differences and associations between groups in IS, cognitive and emotive/affective variables, ANOVAs tests and Pearson's correlations were run. Furthermore, moderation analyses and hierarchical regression were set to determine whether age, cognitive and emotive/affective variables predicted IS components (i.e., Yield and Shift). Finally, machine learning models were developed to highlight the best strategy for classifying elderly subjects with high suggestibility. The results corroborated the significant link between IS and age, showing that elderly participants had the worst performance on all suggestibility indexes. Age was also the most important predictor of both Yield and Shift. Results also confirmed the important role of non-verbal intelligence and memory impairment in explaining IS dimensions, showing that these associations were stronger in young elderly and elderly groups. Implications about interrogative procedures with older adults were discussed.

Indexed as

SuggestionAgedAged, 80 and overAlgorithmsAnalysis of VarianceCognitionEmotionsFemaleHumansLinear ModelsMachine LearningMaleMiddle Aged

Identifiers

PMID33196666
PMCPMC7668574
OpenAlexW3101037026

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.