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      Stroking in early mother-infant exchanges: The role of maternal tactile biography and interoceptive sensibility

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          Abstract

          Caress-like is a crucial component of caregiving and a key factor in mother-infant interactions. Mother’s experience of touch during her own childhood (i.e., tactile biography) has been found to be related to maternal actual use of caress-like touch (i.e., stroking) during mother-infant exchanges. Evidence also suggests that maternal interoceptive sensibility (i.e., self-perceived sensitivity to inner-body sensations) might be related to sensitive caregiving abilities. However, further empirical investigation is needed to understand to what extent tactile biography and interoceptive sensibility have an impact on mothers’ stroking when interacting with their infants. Using an online survey, this cross-sectional study explored the potential association between maternal tactile biography, interoceptive sensibility and use of touch for interaction with their own infants in a group of 377 Italian mothers (mean age = 33.29; SD = 4.79). We tested and compared a series of multivariate linear mediation models using maternal tactile biography as predictor, maternal use of affective touch as outcome variable and Multidimensional Assessment of Interoceptive Awareness (MAIA) subscale scores as mediators. We found that, if a mother had positive touch experiences in her own childhood, she may be more likely to use touch in a positive and nurturing way with her own infant (i.e., stroking). Furthermore, mothers’ interoceptive sensibility in the form of attention regulation, self-regulation and body listening mediates the association between their past experiences of positive touch and their use of caress-like touch in mother-infant exchanges. This study highlights that maternal tactile biography is directly associated with mothers’ use of caress-like touch and indirectly linked to it through the mediating role of interoceptive sensibility.

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          lavaan: AnRPackage for Structural Equation Modeling

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            The structure of negative emotional states: Comparison of the Depression Anxiety Stress Scales (DASS) with the Beck Depression and Anxiety Inventories

            The psychometric properties of the Depression Anxiety Stress Scales (DASS) were evaluated in a normal sample of N = 717 who were also administered the Beck Depression Inventory (BDI) and the Beck Anxiety Inventory (BAI). The DASS was shown to possess satisfactory psychometric properties, and the factor structure was substantiated both by exploratory and confirmatory factor analysis. In comparison to the BDI and BAI, the DASS scales showed greater separation in factor loadings. The DASS Anxiety scale correlated 0.81 with the BAI, and the DASS Depression scale correlated 0.74 with the BDI. Factor analyses suggested that the BDI differs from the DASS Depression scale primarily in that the BDI includes items such as weight loss, insomnia, somatic preoccupation and irritability, which fail to discriminate between depression and other affective states. The factor structure of the combined BDI and BAI items was virtually identical to that reported by Beck for a sample of diagnosed depressed and anxious patients, supporting the view that these clinical states are more severe expressions of the same states that may be discerned in normals. Implications of the results for the conceptualisation of depression, anxiety and tension/stress are considered, and the utility of the DASS scales in discriminating between these constructs is discussed.
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              AIC model selection using Akaike weights.

              The Akaike information criterion (AIC; Akaike, 1973) is a popular method for comparing the adequacy of multiple, possibly nonnested models. Current practice in cognitive psychology is to accept a single model on the basis of only the "raw" AIC values, making it difficult to unambiguously interpret the observed AIC differences in terms of a continuous measure such as probability. Here we demonstrate that AIC values can be easily transformed to so-called Akaike weights (e.g., Akaike, 1978, 1979; Bozdogan, 1987; Burnham & Anderson, 2002), which can be directly interpreted as conditional probabilities for each model. We show by example how these Akaike weights can greatly facilitate the interpretation of the results of AIC model comparison procedures.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Supervision
                Role: Data curationRole: Formal analysisRole: MethodologyRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2024
                7 March 2024
                : 19
                : 3
                : e0298733
                Affiliations
                [1 ] Department of Developmental and Social Psychology, University of Padua, Padua, Italy
                [2 ] 0-3 Center for the at-Risk Infant, Scientific Institute IRCCS E. Medea, Bosisio Parini, Italy
                University of Modena and Reggio Emilia: Universita degli Studi di Modena e Reggio Emilia, ITALY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0003-0958-5124
                Article
                PONE-D-23-17344
                10.1371/journal.pone.0298733
                10919687
                38451923
                d40f5456-fdc1-48cc-8dc2-e88bb4068902
                © 2024 Mariani Wigley et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 15 September 2023
                : 29 January 2024
                Page count
                Figures: 1, Tables: 4, Pages: 15
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100003196, Ministero della Salute;
                Award ID: SG-2018-12368279
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100003196, Ministero della Salute;
                Award ID: Ricerca Corrente 2021-2023
                Award Recipient :
                The contribution of Eleonora Mascheroni was partially supported by Italian Ministry of Health grant# Ricerca Finalizzata SG-2018-12368279. The contribution of Rosario Montirosso was partially supported by the Italian Ministry of Health Ricerca Corrente 2021-2023. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognitive Psychology
                Perception
                Sensory Perception
                Touch
                Biology and Life Sciences
                Psychology
                Cognitive Psychology
                Perception
                Sensory Perception
                Touch
                Social Sciences
                Psychology
                Cognitive Psychology
                Perception
                Sensory Perception
                Touch
                Biology and Life Sciences
                Neuroscience
                Sensory Perception
                Touch
                People and Places
                Population Groupings
                Age Groups
                Children
                Infants
                People and Places
                Population Groupings
                Families
                Children
                Infants
                People and Places
                Population Groupings
                Families
                Mothers
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognitive Psychology
                Perception
                Sensory Perception
                Biology and Life Sciences
                Psychology
                Cognitive Psychology
                Perception
                Sensory Perception
                Social Sciences
                Psychology
                Cognitive Psychology
                Perception
                Sensory Perception
                Biology and Life Sciences
                Neuroscience
                Sensory Perception
                Biology and Life Sciences
                Psychology
                Emotions
                Social Sciences
                Psychology
                Emotions
                Biology and Life Sciences
                Psychology
                Behavior
                Social Sciences
                Psychology
                Behavior
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Psychological Stress
                Biology and Life Sciences
                Psychology
                Psychological Stress
                Social Sciences
                Psychology
                Psychological Stress
                Medicine and Health Sciences
                Health Care
                Caregivers
                Custom metadata
                All files are available from the OSF database (accession number DOI 10.17605/OSF.IO/GU4DR). Minimal data set is available here: https://osf.io/gu4dr/.

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