Evidence map›Paper›PMID 28385683›Full record

ArticleJournal of medical Internet research2017

The Multimodal Assessment of Adult Attachment Security: Developing the Biometric Attachment Test.

Federico Parra, Raphaële Miljkovitch, Gwenaelle Persiaux, Michelle Morales, Stefan Scherer

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
3.7field-weighted citation impact, top 8% 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

4 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Toward Impactful Collaborations on Computing and Mental Health.Journal of medical Internet research · 2018
    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

5 authors at 3 institutions in 2 countries.

Federico ParraInstitute for Creative Technologies, University of Southern California, Los Angeles, CA, United States.ORCID 0000-0002-5333-8211
Raphaële MiljkovitchParagraphe Laboratory, Paris VIII University, Saint-Denis, France.ORCID 0000-0003-3140-8730
Gwenaelle PersiauxUniversity Hospital Center Sainte-Étienne, Sainte-Étienne, France.ORCID 0000-0003-2211-9742
Michelle MoralesInstitute for Creative Technologies, University of Southern California, Los Angeles, CA, United States.ORCID 0000-0003-3238-9244
Stefan SchererInstitute for Creative Technologies, University of Southern California, Los Angeles, CA, United States.ORCID 0000-0002-0280-5393
University of Southern California · USCentre Hospitalier Universitaire de Saint-Étienne · FRUniversité Paris 8 · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAttachment theory has been proven essential for mental health, including psychopathology, development, and interpersonal relationships. Validated psychometric instruments to measure attachment abound but suffer from shortcomings common to traditional psychometrics. Recent developments in multimodal fusion and machine learning pave the way for new automated and objective psychometric instruments for adult attachment that combine psychophysiological, linguistic, and behavioral analyses in the assessment of the construct.

objectiveThe aim of this study was to present a new exposure-based, automatic, and objective adult-attachment assessment, the Biometric Attachment Test (BAT), which exposes participants to a short standardized set of visual and music stimuli, whereas their immediate reactions and verbal responses, captured by several computer sense modalities, are automatically analyzed for scoring and classification. We also aimed to empirically validate two of its assumptions: its capacity to measure attachment security and the viability of using themes as placeholders for rotating stimuli.

methodsA total of 59 French participants from the general population were assessed using the Adult Attachment Questionnaire (AAQ), the Adult Attachment Projective Picture System (AAP), and the Attachment Multiple Model Interview (AMMI) as ground truth for attachment security. They were then exposed to three different BAT stimuli sets, whereas their faces, voices, heart rate (HR), and electrodermal activity (EDA) were recorded. Psychophysiological features, such as skin-conductance response (SCR) and Bayevsky stress index; behavioral features, such as gaze and facial expressions; as well as linguistic and paralinguistic features, were automatically extracted. An exploratory analysis was conducted using correlation matrices to uncover the features that are most associated with attachment security. A confirmatory analysis was conducted by creating a single composite effects index and by testing it for correlations with attachment security. The stability of the theory-consistent features across three different stimuli sets was explored using repeated measures analysis of variances (ANOVAs).

resultsIn total, 46 theory-consistent correlations were found during the exploration (out of 65 total significant correlations). For example, attachment security as measured by the AAP was correlated with positive facial expressions (r=.36, P=.01). AMMI's security with the father was inversely correlated with the low frequency (LF) of HRV (r=-.87, P=.03). Attachment security to partners as measured by the AAQ was inversely correlated with anger facial expression (r=-.43, P=.001). The confirmatory analysis showed that the composite effects index was significantly correlated to security in the AAP (r=.26, P=.05) and the AAQ (r=.30, P=.04) but not in the AMMI. Repeated measures ANOVAs conducted individually on each of the theory-consistent features revealed that only 7 of the 46 (15%) features had significantly different values among responses to three different stimuli sets.

conclusionsWe were able to validate two of the instrument's core assumptions: its capacity to measure attachment security and the viability of using themes as placeholders for rotating stimuli. Future validation of other of its dimensions, as well as the ongoing development of its scoring and classification algorithms is discussed.

Indexed as

Object AttachmentAdultCombined Modality TherapyFacial ExpressionFemaleHumansInterpersonal RelationsLanguageMaleMental HealthMiddle AgedPsychometricsattachmentCOVAREPfacial expressionheart ratelinguisticspsychometricspsychopathologypsychophysiology

Identifiers

PMID28385683
PMCPMC5399225
OpenAlexW2604206595

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.