the relationship between state attachment security and daily interpersonal experience

5
Brief Report The relationship between state attachment security and daily interpersonal experience Fang Zhang * Dept. of Psychology, Assumption College, Worcester, MA 01609, United States article info Article history: Available online 8 January 2009 Keywords: State attachment security Daily interpersonal experience abstract Although past research suggests that state attachment security fluctuates in relation to daily interper- sonal events, information on this relationship is limited. This study aimed to replicate and extend previ- ous findings. The study followed 30 participants for 4 consecutive weeks, requiring them to report recent interpersonal events they experienced and their current attitudes toward attachment relationships twice each week. The results indicate that state attachment security fluctuated with daily interpersonal expe- rience. Specifically, state attachment anxiety increased the greater the reported number of negative inter- personal events or perceived interpersonal losses, and decreased as participants perceived greater interpersonal gain from positive interpersonal events. Ó 2009 Elsevier Inc. All rights reserved. 1. Introduction Over the past several decades, numerous studies have been con- ducted on the organizational role of adult attachment style in per- sonality functioning (Cassidy & Shaver, 1999). The central idea underlying this research is that adult attachment style reflects an individual’s characteristic working models—mental representa- tions—of self and others and, once formed, guides and organizes the individual’s thoughts, feelings, and behavior in subsequent relationships (Bowlby, 1969, 1973, 1980). More recent evidence indicates that attachment style varies across time and situation (Baldwin & Fehr, 1995; Davila & Cobb, 2004). This within-person variability, especially as a function of the situation, underscores state-dependent properties, as opposed to trait properties, of adult attachment style as well as the role of situation in activating and shaping attachment representations (Baldwin & Fehr, 1995; Baldwin, Keelan, Fehr, Enns, & Koh-Rang- arajoo, 1996; Davila, Burge, & Hammen, 1997; Davila & Sargent, 2003). Davila and Sargent (2003) linked this within-person vari- ability to daily life experience. They examined the relationship be- tween daily fluctuation in state attachment security and negative life events over an 8-week period, finding that day-to-day change in attachment security co-varied with the perception of interper- sonal loss associated with the events. As individuals perceive greater interpersonal loss from events, they also tend to report greater attachment insecurity. Davila and Sargent’s finding supports Bowlby’s (1969) view that attachment style can change as a result of new relationship expe- riences. More crucially, their finding underscores the importance of understanding the mechanism of within-person variability, for it may provide a microscopic perspective on the effects of major life events on long-term attachment change. Major life events, such as initiating a new relationship or ending one, unfold gradually, in a series of micro-episodes, activities and events taking place in the everyday environment, and are experienced by individuals as momentary change in feelings, perceptions, and attitudes with re- gard to self and others. Mundane activities with other, non-attach- ment, people, especially those who figure prominently in one’s everyday life (e.g., roommates or friends), also influence momen- tary perceptions of self and others, affecting one’s sense of security and relationship behavior. To date, few studies have looked into this dynamic interplay be- tween state attachment and everyday life activities and events. The present study, which had three purposes, was designed to fill this gap: first, the present study aimed to replicate Davila and Sargent’s (2003) findings, especially those relating to state attachment anx- iety (‘‘anxiety about abandonment” in their terms) and avoidance (‘‘low comfort with intimacy”). Attachment anxiety and avoidance reflect two distinct aspects of attachment representations and at the trait level have different influences on behavior, cognition, and emotion: anxiety reflects a person’s concern about rejection and abandonment; avoidance reflects the person’s comfort with intimacy and strategy of regulating attachment-related needs by approaching or avoiding interpersonal closeness (Hazan & Shaver, 1987). There is evidence to suggest that, at the trait level, anxiety is more likely to change than avoidance. Davila and Sargent found that after controlling for fluctuation at the state level, trait attach- ment anxiety declined significantly over the 8-week period, whereas avoidance did not change. Similarly, Davila, Karney, and 0092-6566/$ - see front matter Ó 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.jrp.2008.12.026 * Fax: +1 508 767 7263. E-mail address: [email protected] Journal of Research in Personality 43 (2009) 511–515 Contents lists available at ScienceDirect Journal of Research in Personality journal homepage: www.elsevier.com/locate/jrp

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Page 1: The relationship between state attachment security and daily interpersonal experience

Journal of Research in Personality 43 (2009) 511–515

Contents lists available at ScienceDirect

Journal of Research in Personality

journal homepage: www.elsevier .com/ locate/ j rp

Brief Report

The relationship between state attachment security and dailyinterpersonal experience

Fang Zhang *

Dept. of Psychology, Assumption College, Worcester, MA 01609, United States

a r t i c l e i n f o a b s t r a c t

Article history:Available online 8 January 2009

Keywords:State attachment securityDaily interpersonal experience

0092-6566/$ - see front matter � 2009 Elsevier Inc. Adoi:10.1016/j.jrp.2008.12.026

* Fax: +1 508 767 7263.E-mail address: [email protected]

Although past research suggests that state attachment security fluctuates in relation to daily interper-sonal events, information on this relationship is limited. This study aimed to replicate and extend previ-ous findings. The study followed 30 participants for 4 consecutive weeks, requiring them to report recentinterpersonal events they experienced and their current attitudes toward attachment relationships twiceeach week. The results indicate that state attachment security fluctuated with daily interpersonal expe-rience. Specifically, state attachment anxiety increased the greater the reported number of negative inter-personal events or perceived interpersonal losses, and decreased as participants perceived greaterinterpersonal gain from positive interpersonal events.

� 2009 Elsevier Inc. All rights reserved.

1. Introduction

Over the past several decades, numerous studies have been con-ducted on the organizational role of adult attachment style in per-sonality functioning (Cassidy & Shaver, 1999). The central ideaunderlying this research is that adult attachment style reflects anindividual’s characteristic working models—mental representa-tions—of self and others and, once formed, guides and organizesthe individual’s thoughts, feelings, and behavior in subsequentrelationships (Bowlby, 1969, 1973, 1980).

More recent evidence indicates that attachment style variesacross time and situation (Baldwin & Fehr, 1995; Davila & Cobb,2004). This within-person variability, especially as a function ofthe situation, underscores state-dependent properties, as opposedto trait properties, of adult attachment style as well as the role ofsituation in activating and shaping attachment representations(Baldwin & Fehr, 1995; Baldwin, Keelan, Fehr, Enns, & Koh-Rang-arajoo, 1996; Davila, Burge, & Hammen, 1997; Davila & Sargent,2003). Davila and Sargent (2003) linked this within-person vari-ability to daily life experience. They examined the relationship be-tween daily fluctuation in state attachment security and negativelife events over an 8-week period, finding that day-to-day changein attachment security co-varied with the perception of interper-sonal loss associated with the events. As individuals perceivegreater interpersonal loss from events, they also tend to reportgreater attachment insecurity.

Davila and Sargent’s finding supports Bowlby’s (1969) view thatattachment style can change as a result of new relationship expe-

ll rights reserved.

riences. More crucially, their finding underscores the importance ofunderstanding the mechanism of within-person variability, for itmay provide a microscopic perspective on the effects of major lifeevents on long-term attachment change. Major life events, such asinitiating a new relationship or ending one, unfold gradually, in aseries of micro-episodes, activities and events taking place in theeveryday environment, and are experienced by individuals asmomentary change in feelings, perceptions, and attitudes with re-gard to self and others. Mundane activities with other, non-attach-ment, people, especially those who figure prominently in one’severyday life (e.g., roommates or friends), also influence momen-tary perceptions of self and others, affecting one’s sense of securityand relationship behavior.

To date, few studies have looked into this dynamic interplay be-tween state attachment and everyday life activities and events. Thepresent study, which had three purposes, was designed to fill thisgap: first, the present study aimed to replicate Davila and Sargent’s(2003) findings, especially those relating to state attachment anx-iety (‘‘anxiety about abandonment” in their terms) and avoidance(‘‘low comfort with intimacy”). Attachment anxiety and avoidancereflect two distinct aspects of attachment representations and atthe trait level have different influences on behavior, cognition,and emotion: anxiety reflects a person’s concern about rejectionand abandonment; avoidance reflects the person’s comfort withintimacy and strategy of regulating attachment-related needs byapproaching or avoiding interpersonal closeness (Hazan & Shaver,1987). There is evidence to suggest that, at the trait level, anxiety ismore likely to change than avoidance. Davila and Sargent foundthat after controlling for fluctuation at the state level, trait attach-ment anxiety declined significantly over the 8-week period,whereas avoidance did not change. Similarly, Davila, Karney, and

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1 In order to gain preliminary insights into the influence of various types of eventson attachment change, the events were broken up into three subcategories—familymember-related events, friend-related events, and others-related events—andentered into HLM analyses, using a HLM model similar to the one described in theResults section. State attachment (anxiety or avoidance) was predicted from thenumbers of negative and positive events in the three subcategories, as well as overallperceptions of interpersonal loss and gain, while controlling for mood as well as theintercorrelation between the two attachment variables at each data point. The

512 F. Zhang / Journal of Research in Personality 43 (2009) 511–515

Bradbury (1999) found that over the first 2 years of marriage, hus-bands and wives showed a significant decline in anxiety aboutabandonment, but neither changed significantly in their comfortwith closeness and wives also did not change significantly in theircomfort with depending on others. These results suggest that anx-iety and avoidance may vary differently in relation to life eventsand that avoidance may be more resistant to change than anxiety.Davila and Sargent did not find differences between state attach-ment anxiety and avoidance in daily covariation with events. Thepresent study aimed to explore this issue further.

Second, Davila and Sargent’s analyses focused on infrequentmajor life events. They found the number of negative life eventsunrelated to state attachment security, once the subjective mean-ing of the events was taken into account. However, they measuredonly infrequent major events, such as the death of a parent or theending of a romantic relationship. The rarity of such events mayhave contributed to the small number of events reported in theirstudy (0.06–0.13 per week, on average) and may have resulted intheir underestimating the effect of the quantity of such events.The present study measured mundane life events that occur morefrequently on a day-by-day basis. Such mundane events not onlycapture micro-activities and interactions that constitute everydaylife but also are expected to show greater variability in quantity,both across time and participants.

Finally, psychologic research has been criticized for emphasiz-ing psychopathology and malfunction too much and overlookingpositive experiences and life outcomes (Gable & Haidt, 2005). Inan average individual’s everyday life, both positive and negativeevents come into play. Oftentimes positive experiences, ratherthan negative experiences, make up the bulk of the individual’severyday experience (Oishi, Diener, Choi, Kim-Prieto, & Choi,2007). It remains unclear from past research how state attachmentsecurity changes with positive and negative events as they occur ineveryday life. The present study extended the analysis of the effectof daily life events to both positive and negative events.

With these aims, the present study followed participants forfour consecutive weeks, each week asking them to report twiceon their recent interpersonal activities and events, as well as theircurrent attitudes toward attachment relationships. Based on Davilaand Sargent’s (2003) findings, it was predicted that: (1) stateattachment anxiety and avoidance would co-vary with the subjec-tive meaning of daily interpersonal events; that is, they would de-crease from baseline in relation to perceived interpersonal lossfrom negative daily events, but would increase from baseline withthe perception of gain associated with positive daily events. (2)State attachment anxiety and avoidance would co-vary with thequantity of positive and negative events as well, increasing in pro-portion to the number of positive events and decreasing in propor-tion to the number of negative events experienced. Alternatively,only anxiety was predicted to show these co-varying relationshipswith daily events, while state avoidance was predicted to show lit-tle covariation with daily events.

analyses revealed that perceptions of interpersonal loss and gain each predictedcurrent anxiety, respectively, b3j = 0.02, t(224) = 2.49, p < .05, andb4j= �0.02, t(224) =�2.43, p < .02. Moreover, the number of friend-related positive events and other-related positive events each predicted current anxiety, respectively, b = �0.11,t(224) = �2.45, p < .05 and b = �0.09, t(224) = �1.82, p < .07. With increases inperceived interpersonal loss from recent negative interpersonal events, participantsalso became more anxious. In contrast, as participants experienced more positiveinteractions with friends or others, or perceived greater interpersonal gain fromrecent positive interpersonal events, they also reported less anxiety. These results areconsistent with the predictions and added an interesting layer of meaning to thepresent findings.No significant results were found for avoidance. Given the largenumber of variables in this model (six event quantity variables plus five othervariables) and the fact that the present study only measured eight data points, themodel may lack statistical power. For this reason, a simplified HLM model wasreported in the Results section, using the combined totals for positive and negativeevents. With the combined totals, the results for negative events became significantbut the results for positive events became not significant.

2. Method

2.1. Participants

Thirty undergraduates (15 male, 15 female; all Caucasian,Mage = 21.23, SD = 0.94) participated in the study.

2.2. Procedure

Participants attended an information session 1 week before thestudy began. At the session, they were given diary booklets and in-structed to complete a diary entry at the end of the day, twice a

week (Mondays and Thursdays), for 4 consecutive weeks, returningthe completed diaries to the research team at the end of each week.In total, eight data points were collected from each participant.Twenty-eight participants completed the diaries for all eight datapoints, 1 person missed completing one diary, and another missedtwo.

2.3. Measures

Participants reported on the following measures in each diaryentry, with the order of reporting negative and positive eventscounterbalanced among participants to reduce bias.

2.3.1. Positive and negative moodEach time, participants rated their mood during the past few days

prior to reporting on seventeen affect terms, shortened from thePositive and Negative Affect Schedule (Watson, Clark, & Tellegen,1988) to adapt it for daily reporting (Charles & Pasupathi, 2003).The scores, measured on a 7-point scale (1-not at all to 7-extre-mely), were averaged to reflect positive and negative mood.

2.3.2. Daily interpersonal events and perception of interpersonal-lossor gain

Each time, participants reported on event checklists the inter-personal events that had taken place since the last reporting aswell as their resulting sense of interpersonal loss or gain. UnlikeDavila and Sargent’s measure, the checklists were designed to cap-ture mundane and recurring interpersonal interactions, activities,or events that are typical of undergraduates’ everyday lives.

The negative event checklist identified four major types of neg-ative interpersonal events/interactions (arguments, tensions, beingcriticized, or distance/disconnection) with three primary targetgroups (family members, close friends/boyfriend/girlfriend, otherindividuals [roommate, acquaintance, teacher, etc.]). Participantschecked the events that took place since the last reporting andprior to the current reporting. If they experienced a negative eventthat did not fit the categories, they specified this on a separate line.The checked and specified negative events/interactions weresummed to indicate the total number of negative daily events.The events were summed because many events had zero occur-rences and also the type of experienced events varied across partic-ipants and across time, making it impossible to analyze eachseparately.1 After completing the checklist, participants rated on a

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Table 1Sample means and standard deviations of all key variables over the 4-week period.

Variable M SD Range ofmeasurement

State attachment anxiety 3.17 0.77 1–7State attachment avoidance 3.59 0.93 1–7Number of negative daily interpersonal

events1.74 1.71

Number of positive daily interpersonalevents

2.99 1.51

Interpersonal loss 7.78 4.77 0–24Interpersonal gain 12.70 3.99 0–24Negative affect 3.28 0.85 1–7Positive affect 3.99 0.86 1–7

Note: N = 30.

2 The results reported here came from the HLM analyses in which the time-varyingcovariates were modeled as fixed effects at level 2. In the initial analyses, the time-varying covariates were modeled as random effects at level 2. The random effect wassignificant only for interpersonal gain and not significant for the number of positive ornegative events or interpersonal loss. Modeling all of the covariates as random effectsalso introduced colinearity. Therefore, the time-varying covariates were all modeledas fixed effects. In additional analyses, interpersonal gain was modeled as a randomeffect and the other three covariates were modeled as fixed effects. These analysesrevealed the same pattern as the one reported here. Thus, the results reported in thepaper are robust.

3 By definition, the event variables measured at each reporting time weretemporally prior to attachment state which was measured at the same time, becausethe events presumably took place since the last reporting and prior to the currentreporting, while attachment state reflected the attachment feelings at the time of thecurrent reporting. For this reason, the co-varying relationship between the twoshould reflect the influence of prior events on the current attachment state. Toconfirm this temporally sequential relationship and to rule out the possibility that thecurrent attachment state was only a carry-over of a prior attachment state, laggedanalyses were conducted. In these analyses, prior events and prior attachment statewere used to predict current attachment state, controlling for the mood and theintercorrelation between current anxiety and avoidance. The analyses revealed thatperceptions of interpersonal loss and gain predicted current anxiety, b3j = 0.02,t(164) = 2.49, p < .02, and b4j = �0.01, t(164) = �1.77, p < .08, whereas the number ofnegative events predicted current avoidance, b1j = 0.04, t(164) = 1.79, p < .08. Theseresults strongly indicate that prior events led to change in attachment state. Becausethe lagged analyses excluded the first attachment data point from being predictedand also did not fully capture the immediacy of the temporal co-varying relationshipbetween daily events and state attachment, they are reported here as supplementalanalyses.

F. Zhang / Journal of Research in Personality 43 (2009) 511–515 513

7-point scale (0-not at all to 6-a great deal) ‘‘how much these eventstogether” made them feel that they had lost emotional support,closeness or affection, friendship or companionship, and trust (Dav-ila & Sargent, 2003). A composite loss score was created by summingthe loss ratings.

The positive event checklist identified three major categories ofpositive interpersonal events/interactions (intimate connection,friendly interaction, or being complimented) with the same threetarget groups. Participants checked the events that took place sincethe last reporting and specified any events that did not fit the cat-egories. The total number of positive daily events was computed bysumming the checked and specified positive events. After complet-ing the checklist, participants rated on a 7-point scale ‘‘how muchthese events together” made them feel that they had gained emo-tional support, closeness or affection, friendship or companionship,and trust. A composite gain score was created by summing the gainratings.

2.3.3. State attachment anxiety and avoidanceParticipants’ state attachment anxiety and avoidance were

assessed, using a 13-item scale (Simpson, 1990), adapted fromthe Adult Attachment Questionnaire (Hazan & Shaver, 1987).Participants reported how they felt at the moment about roman-tic relationships, using a 7-point scale (1-strongly disagree to 7-strongly agree). Cronbach’s alpha averaged .74 (SD = 0.04) foranxiety and .81 (SD = 0.05) for avoidance across the eight datapoints. The within-person correlation between the two scoresranged from relatively small (r = .31, n.s.) to relativelyhigh (r = .61, p < .001), with a mean of .46 across the eight datapoints.

3. Results

3.1. Preliminary analyses

Table 1 shows the means and standard deviations for all keyvariables. To examine the pattern of attachment fluctuation overthe 4-week period at the within-person level, an unconditionalHierarchical Linear Modeling (HLM, Raudenbush & Bryk, 2002)growth model was run, separately for attachment anxiety andavoidance. Neither analysis revealed a significant effect of TIME;neither anxiety nor avoidance showed a trend toward long-termchange over the 4-week period.

3.2. Co-varying relationships between state attachment variables anddaily interpersonal experience

The next set of analyses focused on the co-varying relation-ships between state attachment anxiety and avoidance and daily

interpersonal events, using the HLM technique (Nezlek, 2005).2

Since there were no long-term changes in state anxiety or avoid-ance, TIME was dropped from the HLM model for this analysis.The numbers of negative and positive events, as well as perceptionsof interpersonal loss and gain, were entered into the HLM model astime-varying covariates, predicting concurrent state attachmentvariables.3 To control for the intercorrelation between anxietyand avoidance at each data point, the attachment variable notbeing predicted at the time was entered into the model as a controlvariable. Positive and negative mood also were entered into theHLM model as control variables to control for mood biases on selfreport. The variables were group-mean centered so that individualdifferences in the scores did not contribute to the estimate ofslopes.

Table 2 reports maximum likelihood estimates on the co-vary-ing relationships between the attachment variables and dailyinterpersonal experiences. b0j represents the mean of the predictedattachment variable (anxiety or avoidance) for participant j acrossthe eight data points, b1j to b4j reflect the co-varying relationshipbetween life events variables and the predicted attachment vari-able for participant j at time i, controlling for the other attachmentvariable and mood, and rij reflects random measurement error andits variance represents residual variance in the data points for par-ticipant j.

As shown, anxiety co-varied with the number of negative dailyinterpersonal events, perception of interpersonal loss associatedwith these events, and perception of interpersonal gain associatedwith positive daily interpersonal events. Each of the latter threevariables independently predicted anxiety. The more negativeinterpersonal events one had, or the more interpersonal loss oneperceived from these events, the more anxious one felt aboutattachment relationships. In contrast, the more interpersonal gainone perceived from positive daily events, the less anxious one felt.Overall, these results indicate that state attachment anxiety fluctu-ated concurrently with daily interpersonal events, in relation toboth their subjective meanings and number. These co-varying rela-tionships were obtained after the mood effect was removed, sug-gesting that they were not merely by-products of mood change.The slope of the number of positive events was not significant.

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Table 2Results of HLM predicting state attachment anxiety and state attachment avoidance from the numbers of negative and positive interpersonal events and perception ofinterpersonal loss and gain, controlling for mood and the intercorrelation between the attachment dimensions.

Coefficient t Effect size

State attachment anxietyAverage state attachment anxiety (b0j) 3.07 15.61***

Number of negative daily interpersonal events (b1j) 0.09 2.99** 0.49Number of positive daily interpersonal events (b2j) 0.02 1.22Interpersonal loss (b3j) 0.02 2.14* 0.37Interpersonal gain (b4j) �0.02 �2.40* 0.41State attachment avoidance (b5j) 0.19 2.20* 0.38Positive mood (b6j) 0.17 3.02** 0.49Negative mood (b7j) 0.16 3.32** 0.52

State attachment avoidanceAverage state attachment avoidance (b0j) 3.81 18.53***

Number of negative daily interpersonal events (b1j) �0.03 �1.02Number of positive daily interpersonal events (b2j) �0.03 �1.90� 0.33Interpersonal loss (b3j) 0.003 0.46Interpersonal gain (b4j) �0.01 �1.22State attachment anxiety (b5j) 0.12 2.11* 0.36Positive mood (b6j) �0.04 �0.76Negative mood (b7j) 0.06 1.40

Note: N = 30. Coefficients were unstandardized. Effect sizes were computed with the formula: r =ffiffiffiffiffiffiffiffiffiffi

t2

t2þdf

q(Rosenthal & Rosnow, 1984), dfbetween individual = 29, and reported only

for the significant effects.* p < .05,** p < .01,*** p < .001,� p < .10.

514 F. Zhang / Journal of Research in Personality 43 (2009) 511–515

State attachment avoidance showed less co-variation with dailyinterpersonal events, co-varying only marginally with the numberof positive events. The latter result, nevertheless, suggests that themore positive events participants experienced, the less avoidantthey became toward attachment relationships.

4. Discussion

The present results replicated and extended Davila and Sargent’s(2003) findings. Consistent with their results, the present studyshows that state attachment anxiety fluctuates with perceptionsof interpersonal loss associated with negative interpersonal events.Specifically, anxiety increases with increase in perceived interper-sonal loss from negative events. The present results extend theirwork by showing that anxiety also fluctuates with the perceptionof interpersonal gain from positive interpersonal events. While neg-ative interpersonal experience increased anxiety from baseline, po-sitive interpersonal experiences decreased anxiety. Positiveinterpersonal experiences, especially when they involved perceivedgains in interpersonal trust and support, resulted in less anxiety andless uncertainty about attachment relationships. The present re-sults suggest that both positive and negative interpersonal experi-ences play a distinct role in influencing attachment anxiety.

Unlike Davila and Sargent’s results, in the present study, attach-ment anxiety fluctuated with the total number of negative inter-personal events. This result was possibly due to the fact that theevents measured were mundane interpersonal events, which aremore variable than Davila and Sargent’s measure. The predictedrelationship between anxiety and the total number of positiveevents was not significant, however. The present findings suggestthat an individual’s attachment anxiety is related to the numberof negative interpersonal events experienced, above and beyondone’s perception of loss associated with these events. The morenegative interpersonal events people reported, the more anxiousthey were about their attachment relationships.

Taken together, the findings suggest that state attachment anx-iety fluctuates in relation to everyday life events—at any given mo-ment, the individual’s level of attachment anxiety is closely related

to recent positive and negative interpersonal experiences, both interms of their quantity and their subjective meaning.

Two possible mechanisms may account for these relationships.One is the activation mechanism proposed by Baldwin and col-leagues (1995, 1996). Baldwin et al. proposed that a person maydevelop multiple attachment representations as a result of rela-tionship experiences with multiple attachment figures, and theserepresentations may be activated in different situations, resultingin fluctuations in the person’s attachment state (Baldwin & Fehr,1995; Baldwin et al., 1996). Alternatively, it could be that the co-varying relationships reflect an ongoing appraisal process. Ratherthan activating varying attachment representations as Baldwinsuggested, people may form provisional assessments of attach-ment relationships using on-line information about self and others.Because what is online is influenced by feedback from recent inter-personal experiences, the person may reach different conclusionsabout attachment relationships at different times, thus showingfluctuations in state attachment security. Future research shouldbe done to tease apart these two possibilities.

Contrary to Davila and Sargent (2003)’s results, the presentstudy did not find the co-varying relationship between attachmentavoidance and the perception of interpersonal loss. Avoidance co-varied only marginally with the total number of positive dailyevents and did not co-vary significantly with either perceptionsof interpersonal loss and gain or the total number of negative dailyevents. These results suggest that avoidance may be influenced lessby mundane interpersonal experiences than by the major lifeevents that Davila and Sargent measured. The present results alsocontrast, interestingly, with the current results for anxiety. Consis-tent with the alternative hypothesis, avoidance appeared to co-vary less with daily experiences than anxiety, indicating thatavoidance may be less susceptible to the influence of daily experi-ences. Caution is warranted in these interpretations, however, be-cause the present study observed participants only for eight datapoints. This limited number of observation per participant maynot produce sufficient statistical power to detect the covariationbetween avoidance and daily events (in fact, avoidance showedless within-person variability than anxiety in the present study,averaging 0.45 (SD = 0.21), measured by the within-person stan-

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F. Zhang / Journal of Research in Personality 43 (2009) 511–515 515

dard deviation, compared to 0.58 (SD = 0.32) for anxiety,t(29) = 2.16, p < .05). More data points are needed to draw firmconclusions. Furthermore, it is possible that daily events other thanthe ones measured in the present study may influence avoidance,for example, events that directly affected a person’ sense ofself-reliance or interdependence may drive the within-personvariability in avoidance. Such possibilities are worth investigatingin future research. Finally, it is also worth comparing in futureresearch the influence of mundane experiences that are associatedwith major events with those that are not on attachment change.

Despite these limitations, the present research fills an impor-tant gap in the existing literature on the within-person variabilityin attachment. The findings underscore the importance of under-standing adult attachment styles as dynamic processes unfoldingcontinuously.

Acknowledgments

I am grateful to Arlene Vadum as well as anonymous reviewersfor their valuable comments on drafts of this manuscript. This re-search was funded by a Faculty Development Grant awarded tothe author by Assumption College.

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