Attachment Styles and Mental Health During the COVID-19 Pandemic

This study makes an important contribution by using cutting-edge causal analysis techniques with a robust sample to elucidate the relationships between attachment style and mental health during a global crisis. The advanced methodology enables stronger causal inferences compared to previous observational research.

The findings validate attachment theory – identifying attachment insecurity as a risk factor for poor mental health outcomes, especially anxiety and loneliness, during the upheaval of a pandemic. Loneliness appears to be a key mechanism linking insecure attachment to depressive and anxious symptoms.

Vowels, L. M., Vowels, M. J., Carnelley, K. B., Millings, A., & Gibson-Miller, J. (2023). Toward a causal link between attachment styles and mental health during the COVID-19 pandemic. The British Journal of Clinical Psychology, 62(3), 605–620. https://doi.org/10.1111/bjc.12428

Key Points

• The study found that individuals with insecure attachment styles (anxious, avoidant, fearful-avoidant) experienced worse mental health outcomes compared to securely attached individuals during the COVID-19 pandemic.
• Attachment anxiety and fearful-avoidant attachment were risk factors for higher depression, anxiety, and loneliness. Attachment avoidance was associated with less social distancing.
• Loneliness partially mediated the relationship between insecure attachment and poor mental health outcomes.
• The research relied on self-report measures and a categorical attachment measure, limiting conclusions.
• Understanding causal risk factors for poor mental health during crises like pandemics can inform interventions to support at-risk groups.

Rationale

The COVID-19 pandemic created immense disruption and stress globally. Research suggests the pandemic led to worse population mental health, including increased rates of depression, anxiety, and loneliness (Pierce et al., 2020; Vindegaard & Benros, 2020).

However, not everyone experienced poor mental health to the same degree. Individual differences like attachment style may help explain variance in pandemic-related mental health outcomes (Vowels, Carnelley, & Stanton, 2022).

Attachment theory proposes that early experiences with caregivers shape working models of self and others that manifest as attachment styles in adulthood (Bowlby, 1969). Attachment anxiety involves fear of abandonment, while avoidance involves discomfort with intimacy. Attachment security supports well-being, while insecurity confers mental health risk (Mikulincer & Shaver, 2016).

Prior studies found insecure attachment associated with worse mental health during the pandemic, especially attachment anxiety (Carbajal et al., 2021; Mazza et al., 2021; Moccia et al., 2020). However, these were observational studies unable to make causal claims.

This study aimed to elucidate the causal relationships between adult attachment styles, adherence to pandemic public health guidelines, and mental health using innovative statistical techniques. Understanding causal pathways can inform interventions to support at-risk groups during public crises.

Method

This secondary analysis used data from a longitudinal COVID-19 psychological survey of UK adults (C19PRCS) during the early months of pandemic restrictions (McBride et al., 2021).

The baseline nationally representative sample included 1325 adults who completed measures of attachment style, social distancing behaviors, depression, anxiety, and loneliness at wave 2 (April-May 2020) during lockdown.

A subset of 950 participants completed follow-up mental health measures at wave 3 (July-August 2020) when restrictions had eased.

Attachment style was measured categorically via the Relationship Questionnaire (Bartholomew & Horowitz, 1991). Participants selected one of four styles: secure, anxious, avoidant, or fearful-avoidant.

Social distancing adherence was assessed via a 16-item scale about following government guidelines in the past week.

Depression and anxiety were measured using validated scales – the Patient Health Questionnaire-9 (Kroenke et al., 2001) and the Generalized Anxiety Disorder scale (Spitzer et al., 2006). The 3-item UCLA Loneliness Scale (Hughes et al., 2004) assessed loneliness.

The researchers used cutting-edge causal discovery and inference techniques. The causal discovery algorithm SAM identified putative causal relationships among variables (Kalainathan et al., 2020).

Targeted learning then estimated specific causal effects, like the effect of attachment anxiety on depression (van der Laan & Rose, 2011).

Sample:

• Nationally representative UK adult sample: N = 1325 at baseline, n = 950 at follow-up
• Age: M = 49 years at baseline, M = 52 years at follow-up
• 51.5% male at baseline, 54.8% male at follow-up
• 88% white British/Irish ethnicity
• Diverse relationship status, income change during pandemic, education, employment status

Statistical measures:

• Causal discovery using Structural Agnostic Modeling (SAM) algorithm
• Estimation of causal effects using targeted learning

Results

• Fearful-avoidant and anxious attachment were associated with 5-6% higher depression and anxiety scores compared to secure attachment.
• Fearful-avoidant and anxious attachment were associated with 17-18% higher loneliness versus secure attachment.
• Avoidant attachment was associated with a 2% decrease in social distancing adherence versus secure attachment.
• Causal discovery analysis identified loneliness as a mediator between insecure attachment and mental health outcomes.
• Attachment styles at wave 2 predicted mental health at wave 3, but did not predict changes in mental health from wave 2 to 3.

Implications

• These findings demonstrate attachment insecurity confers mental health risks during crises like the pandemic. However, the effect sizes were small-to-moderate, suggesting individual differences like attachment style are just one factor influencing pandemic mental health outcomes.
• Nevertheless, identifying causal risk factors can inform public health messaging and interventions. For instance, attachment-informed programs to mitigate loneliness could support at-risk groups during public health emergencies. Outreach should specifically target anxiously attached individuals likely experiencing distress.
• Providing mental health resources proactively, especially initiatives that foster social connection, may help reduce the burden of poor mental health during population-wide crises.

Future Research

• The results highlight the need to proactively identify and support insecurely attached individuals experiencing loneliness during public health emergencies. Fostering social connections could help buffer poor mental health in high-risk groups.

Strengths & Limitations

The study had many methodological strengths, including:

• Nationally representative sample enhances generalizability
• Longitudinal follow-up data
• Use of causal analysis techniques improves ability to make causal inferences
• Large sample size
• Inclusion of validated measures of key constructs

However, this study was limited in a few ways:

• Self-report measures prone to reporting biases
• Categorical attachment measure may lack nuance
• Data collected early in the pandemic may not generalize to later stages
• Unable to compare pre-post pandemic mental health
• Sample not internationally diverse

Conclusion

This research elucidates attachment style as a causal risk factor for poor mental health outcomes during the pandemic, specifically heightened depression, anxiety, and loneliness. Loneliness appears central in linking insecure attachment to symptomatology.

The advanced causal methodology enables stronger inferences to guide intervention. However, further research should replicate findings using dimensional attachment measures and behavioral observations.

This study highlights the need for proactive mental health support for insecurely attached individuals prone to isolation during public crises. Fostering social connections and addressing loneliness may mitigate mental health risks.

Population-wide disruptions like pandemics will likely continue to occur. Understanding causal factors linked to distress can inform policies to support at-risk groups.

While pandemics create collective stress, they do not uniformly impact mental health, due to individual differences. Attachment theory offers a valuable framework for identifying those most vulnerable.

References

Primary Paper

Vowels, L. M., Vowels, M. J., Carnelley, K. B., Millings, A., & Gibson-Miller, J. (2023). Toward a causal link between attachment styles and mental health during the COVID-19 pandemic. The British Journal of Clinical Psychology, 62(3), 605–620. https://doi.org/10.1111/bjc.12428

Other References

Bartholomew, K., & Horowitz, L. M. (1991). Attachment styles among young adults: A test of a four-category model. Journal of Personality and Social Psychology, 61(2), 226-244. https://doi.org/10.1037/0022-3514.61.2.226

Bowlby, J. (1969). Attachment and loss: Volume 1. Attachment (1st ed.). Basic Books.

Carbajal, J., Ponder, W. N., Whitworth, J., Schuman, D. L., & Galusha, J. M. (2021). The impact of COVID-19 on first responders’ resilience and attachment. Journal of Human Behavior in the Social Environment, 32, 781-797. https://doi.org/10.1080/10911359.2021.1962777

Hughes, M. E., Waite, L. J., Hawkley, L. C., & Cacioppo, J. T. (2004). A short scale for measuring loneliness in large surveys: Results from two population-based studies. Research on Aging, 26(6), 655-672.

Kalainathan, D., Goudet, O., Guyon, I., Lopez-Paz, D., & Sebag, M. (2020). Structural agnostic modeling: Adversarial learning of causal graphs. arXiv:1803.04929v3.

Kroenke, K., Spitzer, R. L., & Williams, J. B. (2002). The PHQ-15: Validity of a new measure for evaluating the severity of somatic symptoms. Psychosomatic Medicine, 64(2), 258-266.

McBride, O., Murphy, J., Shevlin, M., Gibson-Miller, J., Hartman, T. K., Hyland, P., Levita, L., Mason, L., Martinez, A. P., McKay, R., Stocks, T. V. A., Bennett, K., Vallières, F., Karatzias, T., Valiente, C., Vazquez, C., & Bentall, R. P. (2021). Monitoring the psychological, social, and economic impact of the COVID-19 pandemic in the population: Context, design and conduct of the longitudinal COVID-19 psychological research consortium (C19PRC) study. International Journal of Methods in Psychiatric Research, 30(1), e1861. https://doi.org/10.1002/mpr.1861

Mikulincer, M., & Shaver, P. R. (2016). Attachment in adulthood: Structure, dynamics, and change (2nd ed.). Guilford Press.

Moccia, L., Janiri, D., Pepe, M., Dattoli, L., Molinaro, M., De Martin, V., Chieffo, D., Janiri, L., Fiorillo, A., Sani, G., & Di Nicola, M. (2020). Affective temperament, attachment style, and the psychological impact of the COVID-19 outbreak: An early report on the Italian general population. Brain, Behavior, and Immunity, 87, 75-79. https://doi.org/10.1016/j.bbi.2020.04.048

Pierce, M., Hope, H., Ford, T., Hatch, S., Hotopf, M., John, A., Kontopantelis, E., Webb, R., Wessely, S., McManus, S., & Abel, K. M. (2020). Mental health before and during the COVID-19 pandemic: A longitudinal probability sample survey of the UK population. The Lancet Psychiatry, 7, 883-892. https://doi.org/10.1016/S2215-0366(20)30308-4

Spitzer, R. L., Kroenke, K., Williams, J. B. W., & Löwe, B. (2006). A brief measure for assessing generalized anxiety disorder: The GAD-7. Archives of Internal Medicine, 166(10), 1092-1097. https://doi.org/10.1001/archinte.166.10.109

van der Laan, M. J., Polley, E. C., & Hubbard, A. E. (2007). Super learner. Statistical Applications of Genetics and Molecular Biology, 6(25). https://doi.org/10.2202/1544-6115.1309

van der Laan, M. J., & Rose, S. (2011). Targeted learning—Causal inference for observational and experimental data. Springer International.

Vindegaard, N., & Benros, M. E. (2020). COVID-19 pandemic and mental health consequences: Systematic review of the current evidence. Brain and Behavior: A Cognitive Neuroscience Perspective, and Immunity, 89, 531-542. https://doi.org/10.1016/j.bbi.2020.05.048

Vowels, L. M., Carnelley, K. B., & Stanton, S. C. E. (2022). Attachment anxiety predicts worse mental health outcomes during COVID-19: Evidence from two longitudinal studies. Personality and Individual Differences, 185, 111256. https://doi.org/10.1016/j.paid.2021.111256

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