• Login
    View Item 
    •   Home
    • Massey Documents by Type
    • Theses and Dissertations
    • View Item
    •   Home
    • Massey Documents by Type
    • Theses and Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Network models of mindfulness : a thesis presented in partial fulfilment of the requirements for the degree of Doctor in Clinical Psychology at Massey University, Albany campus, New Zealand

    Icon
    View/Open Full Text
    SmithDClinPsychThesis.pdf (4.088Mb)
    Export to EndNote
    Abstract
    Contemporary mindfulness research at the level of self-report has often represented mindfulness as a latent (trait) variable. Recently, a novel psychometric methodology has been developed which allows mindfulness to be modelled as a complex system or network at the level of self-report. This network perspective is argued to provide a more plausible conceptualisation of mindfulness. A network perspective implies that a more densely connected network of practices may be indicative of a greater level of development of mindfulness. It also implies that certain practices may be more strongly interconnected or central than others. These highly central practices may be potentially useful targets for interventions. Mindfulness networks were estimated for practitioners and non-practitioners using the Friedberg Mindfulness Inventory (Study 1) and an adapted version of the Applied Mindfulness Process Scale (Study 2). A total of 371 regular mindfulness practitioners, 224 non-practitioners and 59 irregular practitioners were recruited online from the Amazon Mechanical Turk database. Across both measures, comparisons between practitioners and non-practitioners’ networks indicated that network density did not significantly differ, whereas evidence was found in support of a significant difference in network structure. Exploratory analyses revealed practitioners’ networks to be characterised by greater differentiation in their community structures relative to non-practitioners across both measures. In Study 1, Acceptance was revealed to be much more central to the practitioners’ network relative to non-practitioners; and Returning to the Present much more peripheral. The practice of Attending to Actions and/or the negative path it shared with Self-kindness were identified as possible targets to facilitate mindfulness in non-practitioners. In Study 2, highly eudemonic practices were revealed to be more central to the practitioners’ network relative to non-practitioners, whilst more foundational de-centering practices were more peripheral. These studies provide support for the plausibility of investigating mindfulness as a complex network at the level of self-report. However, the lack of difference in network density indicates that future research is needed to examine network dynamics in the context of regular mindfulness practice. Future research is also required to establish whether the networks estimated are behavioural or semantic.
    Date
    2019
    Author
    Smith, Joseph Hendry
    Rights
    The Author
    Publisher
    Massey University
    URI
    http://hdl.handle.net/10179/15303
    Collections
    • Theses and Dissertations
    Metadata
    Show full item record

    Copyright © Massey University
    | Contact Us | Feedback | Copyright Take Down Request | Massey University Privacy Statement
    DSpace software copyright © Duraspace
    v5.7-2020.1-beta1
     

     

    Tweets by @Massey_Research
    Information PagesContent PolicyDepositing content to MROCopyright and Access InformationDeposit LicenseDeposit License SummaryTheses FAQFile FormatsDoctoral Thesis Deposit

    Browse

    All of MROCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Statistics

    View Usage Statistics

    Copyright © Massey University
    | Contact Us | Feedback | Copyright Take Down Request | Massey University Privacy Statement
    DSpace software copyright © Duraspace
    v5.7-2020.1-beta1