Attachment Change in the Beginning Stages of Therapy: Examining Change Trajectories for Avoidance and Anxiety

Seedall, Ryan B.; Butler, Mark H.; Zamora, Justin P.; Yang, Chongming

doi:10.1111/jmft.12146

Cited by 12 publications

(13 citation statements)

References 39 publications

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“…Second, we introduced a new method (PRRSA) to explore changes in attachment within clients. PRRSA allows us to use changes in the attachment as predictors, whereas HLM or growth curve analysis focuses on changes in attachment as an outcome variable predicted by other variables (e.g., Sauer et al, 2010) or on overall change trajectory through the entire therapy (e.g., Seedall et al, 2016). Also, different from cross-lagged panel analysis (e.g., Murphy et al, 2016), only examining how the influence of the level of attachment insecurity at a time-point (T) predicted the level of the outcome at the following time-point (T + 1), PRRSA could investigate the immediate influence of consistency and change in a time period (between T and T + 1) on the outcome (T + 1).…”

Section: Discussionmentioning

confidence: 99%

Changes in client attachment in relation to client distress: A response surface analysis.

An¹,

Hillman²,

Kivlighan³

et al. 2022

Journal of Counseling Psychology

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Using multilevel polynomial regression and response surface analysis, we studied the association between Time 1 (T) and Time 2 (T + 1) attachment anxiety and attachment avoidance, and T + 1 psychological distress in 253 nine-session time periods for 65 adult community clients working with 13 doctoral student therapists in open-ended psychodynamic psychotherapy. Results indicated that when client attachment anxiety was consistent and higher from the beginning (T) to the end (T + 1) of a nine-session time period, clients tended to report higher distress at the end of the period; when attachment anxiety was consistent and lower across a time period, clients tended to report lower distress. When attachment anxiety decreased across a time period, clients reported lower distress at the end of the period; when attachment anxiety increased across a time period, clients reported higher distress. Neither within-client consistency nor change in attachment avoidance in a time period was significantly related to client distress at the end of the period. Limitations and implications of the present research are discussed. Public Significance StatementWhen client's attachment anxiety diminishes or remains low across nine sessions, they subsequently report being less psychologically distressed. Hence, therapists need to be particularly aware of times when clients are anxiously attached and help them reduce the attachment anxiety or help them maintain low levels of attachment anxiety.

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Section: Discussionmentioning

confidence: 99%

Changes in client attachment in relation to client distress: A response surface analysis.

An¹,

Hillman²,

Kivlighan³

et al. 2022

Journal of Counseling Psychology

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“…For example, growth mixture models have identified unique subgroups of people that change differently from one another across time in parenting stress (Chang & Fine, 2007), relationship adjustment (Foran, Hahlweg, Kliem, & O'Leary, 2013), and depressive symptoms (Updegraff, Perez-Brena, Umaña-Taylor, Jahromi, & Harvey-Mendoza, 2013). Change in outcomes over the course of therapy also can happen differently for subgroups of people, for example, attachment may change differently for partners throughout therapy (Seedall, Butler, Zamora, & Yang, 2016). Any experienced clinician recognizes that clients change in unique ways from one another.…”

Section: Growth Mixture Modeling To Assess Differences In Change Acromentioning

confidence: 99%

“…Of those n = 67, only n = 20 had employed a type of analysis capable of analyzing growth (i.e., latent growth curve, multilevel modeling, hierarchical linear modeling, latent transition analysis, or growth mixture modeling; contact the corresponding author for the full list of articles). In the past 12 years, only one manuscript published in the Journal of Marital and Family Therapy has employed GMM (i.e., Seedall, Butler, Zamora, & Yang, 2016). In fact, it is the only manuscript in the history of the journal to employ this particular analysis.…”

Section: Growth Mixture Modeling To Assess Differences In Change Acromentioning

confidence: 99%

Identifying Different Ways People Change: A Latent Basis Growth Mixture Model Example Identifying Nonlinear Trajectories of Binge Drinking

Soloski¹,

Durtschi

2019

J Marital Family Therapy

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Our field of couple and family therapy focuses on change, different ways people change, and how therapists can facilitate change. Change can be modeled as an average trajectorygrowth curve model-or as multiple classes of trajectories-growth mixture model. The field of MFT has not yet fully embraced implementing more advanced longitudinal modeling procedures to study what we care about most, change across time. To support our field moving in this direction, we provide a step-by-step description and example in Mplus software. Our example analysis used N = 5,958 participants from the Add Health dataset, to identify unique classifications of trajectories of binge drinking. We discuss how these analytical methods provide increased options to advance family science and clinical research. Studying change across time is at the heart of family science and clinical research. Family development, family processes, symptom development, and therapeutic change, are all complex, heterogeneous, and inherently longitudinal in nature. Therefore, a sophisticated approach to examine these intricacies capable of accounting for various rates of change across time is essential. Recent statistical developments can more fully reflect family and clinical dyadic processes across time, such as: autoregressive models (i.e., inter-associations across time between multiple variables), latent growth curves (LGC; average rate of change across time; Duncan, Duncan, & Strycker, 2006), and latent class growth analysis (LCGA) or growth mixture models (GMM; multiple paths of change across time; Jung & Wickrama, 2008), latent change score models (Grimm, Ram, & Estabrook, 2017), and latent transition analyses (Hawkins et al., 2017). These techniques vary in the research questions they can address and their focus. Most statistical approaches, including autoregressive models and latent growth curves, are what can be classified as "variablecentered" approaches, meaning that the population of interest is considered homogenous and that an average-level of association between variables, or an average rate of change adequately represents the data (Jung & Wickrama, 2008). Person-centered modeling, on the other hand, considers the population as heterogeneous. This type of modeling can identify groups of people that have similar response patterns to a questionnaire (e.g., latent class analysis), that membership in a subgroup can change over time (e.g., latent transition analysis), and that rates of change may vary between different groups of participants who may share common characteristics (e.g., growth mixture modeling). Growth mixture models (GMM) are a "person-centered" approach to identifying

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“…Analiz bulguları beraber değerlendirildiğinde güvenli bağlanma örüntüsüne sahip eşler, evlilik ilişkilerinde duygu ve düşüncelerini karşı tarafa rahatça ifade edip, verdikleri tepkiler olumsuz olsa dahi karşı tarafın her zaman olumsuz tepki vermeyeceğini, eşlerinin farklı tepkiler verebileceğini düşünmektedir. Güvenli bağlanan bireylerin, eşlerinden düşmanca tepkiler beklemedikleri için de, kaygı hissetmeyip, ilişki döngüsünü kesmeyerek, eşleri ile yakın ilişkiyi sürdürüp, evliliklerinden daha çok doyum alabildikleri düşünülmektedir (Knapp et al 2015;Seedall et al 2015). Bununla ilişkili olarak, duygu ve düşüncelerini karşı tarafa daha rahat dile getirebildikleri için de çatışmaları karşılıklı uzlaşı sağlayarak çözebildikleri belirtilmektedir (Tulum 2014;Karagöz-Okutan 2016).…”

Section: Fig 1 Modelunclassified

Bağlanma Örüntüleri ve Evlilik Uyumu Arasındaki İlişkide Eşe Yönelik Kişilerarası Şemaların Aracı Yolu

Hekimoğlu¹

2019

MJH

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Bu çalışma kapsamında evlilik uyumu ile bağlanma örüntüleri arasındaki ilişkide kişilerarası şemaların aracı rolünün bootstrap analizi ile incelenmesi amaçlanmaktadır. Araştırmanın örneklemi 135 kadın ve 133 erkek olmak üzere, 268 evli çiftten oluşmaktadır. Yakın İlişkilerde Yaşantılar Envanteri-II (YİYE-II), Kişilerarası Şemalar Ölçeği (KŞÖ) ve Çiftler Uyumu Ölçeği (ÇUÖ) ölçüm araçları olarak kullanılmıştır. Araştırma sonuçlarına göre güvensiz bağlanma örüntüsüne sahip evli bireylerin evlilik uyumları güvenli bağlananlara kıyasla daha düşüktür. Güvensiz bağlanma örüntüleri arasında ise kaçınıcı bağlananların evlilik uyumları kaygılı bağlananlara göre daha düşüktür. Güvensiz bağlanma ve evlilik uyumu arasındaki ilişkide ise yakınlık ekseninin (dostluk ve düşmanlık kişilerarası şemaları) aracı rolü bulunurken, kontrol ekseninin (baskınlık ve pasiflik kişilerarası şemalarının) aracı etkisi bulunmamıştır. Çalışma bulguları kişilerarası şemalar, bağlanma örüntüleri ve evlilik uyumu arasındaki ilişkinin mekanizmasının anlaşılması açısından önemli bulgular sunmaktadır. Araştırma bulguları ilgili alan yazın doğrultusunda ele alınmıştır.

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Attachment Change in the Beginning Stages of Therapy: Examining Change Trajectories for Avoidance and Anxiety

Cited by 12 publications

References 39 publications

Changes in client attachment in relation to client distress: A response surface analysis.

Changes in client attachment in relation to client distress: A response surface analysis.

Identifying Different Ways People Change: A Latent Basis Growth Mixture Model Example Identifying Nonlinear Trajectories of Binge Drinking

Bağlanma Örüntüleri ve Evlilik Uyumu Arasındaki İlişkide Eşe Yönelik Kişilerarası Şemaların Aracı Yolu

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