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Rzeszuteketal. Health Qual Life Outcomes (2021) 19:105
https://doi.org/10.1186/s12955-021-01752-6
RESEARCH
Daily emotional inertia andlong-term
subjective well-being amongpeople living
withHIV
Marcin Rzeszutek1* , Ewa Gruszczyńska2 and Ewa Firląg‑Burkacka3
Abstract
Objective: The aim of this study was to verify if subjective well‑being (SWB) modifies the autoregressive effect of
daily emotions and if this emotional inertia predicts long‑term changes in SWB among people living with HIV (PLWH).
Methods: The 131 participants had medically confirmed diagnoses of HIV and were undergoing antiretroviral
therapy. They assessed their SWB (satisfaction with life, negative affect, positive affect) twice with an interval of one
year. They also took part in a five‑day online diary study six months from their baseline SWB assessment and reported
their daily negative and positive emotions.
Results: Results showed that baseline SWB did not modify the emotional carryover effect from one to another. Addi‑
tionally, after control for baseline SWB, emotional inertia did not predict SWB one year later. However, such an effect
was noted for the mean values of daily reported emotions, indicating their unique predictive power over SWB itself.
Conclusions: This may suggest that emotional inertia does not necessarily provide better information than more
straightforward measures of affective functioning.
Keywords: Emotional inertia, Affect, Well‑being, HIV/AIDS
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Background
ere has been a long-standing dispute regarding subjec-
tive well-being (SWB) adaptation in response to experi-
encing various stressful life events [1–4], including the
specific case of coping with chronic illness [5]. One of
such illness that requires complex psychosocial adjust-
ment and fosters dynamic changes in various compo-
nents of SWB is HIV/AIDS [6]. Great progress in the
treatment of HIV infection has changed HIV/AIDS from
a definitely terminal illness to a chronic, but manage-
able medical condition [7]. Consequently, for an increas-
ing number of PLWH, their health status is still salient,
but it is not necessarily the main source of their daily
concerns [8, 9]. It has also been found that despite the
same source of distress (i.e., HIV infection), stress level
in PLWH can vary from day to day, leading to signifi-
cant individual differences in psychological adjustment
in this patient group over time [6]. Some authors link
these differences with specific problems in the emotional
functioning of many PLWH. is has been referred to
as emotion dysregulation expressed as ineffective self-
regulation of affective states and difficulties in controlling
emotion-driven behaviors on a daily basis [8, 10], being
one of the main sources of depression and low quality of
life of PLWH in the long term [11]. It has been observed
that emotion dysregulation among PLWH may arise from
struggling with daily (mainly internalized) HIV-related
stigma [8, 12]. In our study, we wanted to examine the
above issues from a different perspective that, to the best
of our knowledge, has never been applied to this clinical
group. Namely, we focused on the relationship between
Open Access
*Correspondence: marcin.rzeszutek@psych.uw.edu.pl
1 Faculty of Psychology, University of Warsaw, Stawki 5/7, 00‑183, Warsaw,
Poland
Full list of author information is available at the end of the article
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Rzeszuteketal. Health Qual Life Outcomes (2021) 19:105
everyday emotional inertia, which may be a proxy of
emotional dysregulation, and long-term SWB among the
PLWH.
ere is an extensive literature on how emotions are
related to individuals’ psychological well-being [13–15].
However, it is important to emphasize that the domi-
nant theoretical and methodological assumption of
most research in this area is a perspective neglecting
within-person dynamics [for a meta-analysis see 16], as
emotions are operationalized as single states that can
be experimentally turned on and off, or relatively stable
individual differences in experiencing particular emo-
tions. is occurs despite the fact that classical authors
have underlined that emotions are not static entities but
are characterized by inherent dynamics in time [17, 18].
In line with this reasoning, some researchers claim that
the above-mentioned static perspective may provide
only a limited picture of the emotion–well-being rela-
tionship [19]. erefore, in the last decade, more and
more authors postulate a paradigm shift in research on
emotions towards emphasizing the temporal dynamics
of emotions derived from data collected in natural con-
ditions [20]. For instance, in some studies based on the
models of emotions as emergent processes [21], it has
been observed that short-term affect dynamics can con-
currently and prospectively be related to psychopatho-
logical symptoms [22, 23].
One such phenomenon of affect dynamics is emo-
tional inertia. e term was coined by Suls etal. [24] to
describe how an individual’s current emotional state may
be predicted from his/her previous emotional states.
Particularly, the scope of emotional inertia indicates the
autocorrelation of emotional trajectories [19, 25]. It was
found that high emotional inertia may be a sign of a lack
of emotional flexibility and deficits in effective emotion
regulation, and thus can predict psychopathology [26].
e studies on emotional inertia, while still very scarce,
have left some issues unanswered. First, while the asso-
ciation of emotional inertia with maladjustment has been
thoroughly explored [19, 25], the link between emotional
inertia and positive aspects of well-being has been highly
neglected [26]. Second, to the best of our knowledge,
almost all studies on emotional inertia have been con-
ducted in non-clinical settings, and the scarce research
on clinical populations has been limited to psychiatric
patients only [25].
e strength of emotional inertia is expressed by the
autocorrelation between successive emotional states
of the same person [19, 25]. It has been found that high
emotional inertia may indicate emotional inflexibility
and deficits in effective emotion regulation, and thus
may predict psychopathology [26]. Studies on emotional
inertia, while still very scarce, leave several questions
unanswered. First, they mainly concern the relationship
between emotional inertia and maladjustment [19, 25],
neglecting the positive aspects of well-being [26]. Sec-
ond, almost all studies on emotional inertia have been
conducted in non-clinical settings, and few studies in
clinical populations have been limited to psychiatric
patients [25].
Current study
Taking the aforementioned research gaps into considera-
tion, the aim of our study was to examine if in the clini-
cal sample with chronic somatic disease (HIV/AIDS):
(a) SWB modifies the autoregressive effect of daily emo-
tions, replicating the effect reported in other samples;
and (b) daily emotional inertia predicts SWB after con-
trol for baseline SWB and mean values of daily reported
emotions. We wanted to examine whether SWB changes
across one year can be predicted from the daily emo-
tional carryover effect. Additionally, we assumed that the
inertia effect is stronger for affective than cognitive com-
ponents of SWB and stronger for negative emotion iner-
tia than positive emotion inertia.
Method
Participants
e sample consisted of 131 participants with con-
firmed diagnoses of HIV infection. e majority were
men (85.5%), with a university degree (64%) and sta-
ble employment (75%). Fifty percent of participants
declared that they were single. e mean age was
39.3 ± 10.3years, with an average duration of HIV infec-
tion of 7.2 ± 6.2years (ranging from 1 to 30years). All the
participants had been on antiretroviral treatment for at
least one year (the mean was 5.8 ± 6.3years), and 14%
were diagnosed with AIDS. e average CD4 count was
586.199 ± 264.282.
e participants were recruited during a control visit to
an outpatient clinic where they were receiving antiretro-
viral treatment. e additional inclusion criteria included
a lack of illness-related cognitive disorders and no cur-
rent diagnosis of substance dependence. For practi-
cal reasons, access to the Internet was also required.
Participation was voluntary and participants were not
remunerated.
Out of 153 participants available for the study, 22
provided no diary data and were excluded from further
analysis. Additionally, 96 persons took part in the final
well-being assessment, representing a 37% dropout rate.
However, it could be regarded as missing at random (Lit-
tle’s MCAR test: χ2 = 9.72, df = 7, p = 0.205). us, all the
analyses were conducted for N = 131, using all the avail-
able data.
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Rzeszuteketal. Health Qual Life Outcomes (2021) 19:105
Procedure
e procedure included traditional longitudinal design
with a burst of intensive longitudinal design. e par-
ticipants took part in two measurements of subjective
well-being, separated by 12 months. e same group
completed online daily diary measures of their end-of-
day positive and negative emotions during five consecu-
tive days, from Monday till Friday, starting six months
after the first measurement of well-being.
e study protocol was approved by the local ethics
committee, and informed consent was obtained from all
the participants. e longitudinal part of the study was
done with a paper-and-pencil approach; the participants
were contacted in person by the research assistants at an
outpatient clinic during their scheduled control visits.
e diary part of the study was conducted online, with
time-stamped questionnaires sent via e-mail each even-
ing as hyperlinks, accessible from Internet-connected
PCs, smartphones, and tablets. Access to the online
measurement was restricted to a limited time daily, and
when the questionnaires were sent back, there was no
possibility to look at or review previous answers.
Measures
Subjective well-being was assessed with two question-
naires to measure its cognitive and affective components:
the Satisfaction with Life Scale (SWLS) [27] and the Posi-
tive and Negative Affect Schedule (PANAS-X) [28]. e
SWLS consists of five items describing personal satisfac-
tion with one’s life as a whole. e participants evaluated
each item on a 7-point scale ranging from 1 (strongly dis-
agree) to 7 (strongly agree). erefore, a higher total score
on this scale indicates a higher level of satisfaction with
life. Cronbach’s alpha coefficient in the studied sample
was 0.87.
Positive and negative affect (PA, NA) refer to the affec-
tive component of subjective well-being. is was evalu-
ated using 20 descriptions of feelings and emotions: 10
for positive affect and 10 for negative affect from the
PANAS-X by Watson and Clark [28]. e participants
rated their generally experienced affective states on a
5-point response scale from 1 (not at all) to 5 (strongly).
Cronbach’s alpha coefficients obtained in this study were
0.91 for the positive affect scale and 0.89 for the negative
affect scale.
Daily positive and negative emotions were also assessed
using the PANAS-X, but with a shorter version that
included 12 items: six for positive emotions (relaxed,
excited, energetic, calm, glad, satisfied) and six for nega-
tive emotions (angry, concerned, unhappy, worried, tired,
discouraged). e participants evaluated how they felt
right now (that is, at the end of each day) and provided
their answers on a 5-point scale from 1 (not at all) to 5
(strongly). e multilevel reliability (omega coefficient)
is 0.81 and 0.80 for within-person level for negative and
positive emotions, respectively, and 0.94 for between-
person level for both valences.
Data analysis
e analysis was based on a multilevel autoregressive
model in which data on emotional inertia was obtained
from a two-level model, with days nested in persons,
leading to 655 measurement points [29]. Each model
contained a random intercept and a random slope with
latent person-mean centering [30, 31]. Specifically, at the
within-person level of this model, the degree to which
emotions reported at Day i were predicted by emotions
reported at Day i − 1 was evaluated. At the between-
person level of this model, person-specific intercept and
slope values were estimated. e intercept represents
individual differences in the average level of emotions
reported during the diary study, whereas slope represents
individual differences in inertia (i.e., in day-to-day auto-
correlation of emotions). Random intercept and random
slope were allowed to covary across participants. In this
analysis, only diary data were used.
In the next stage of the between-person part of the
model, the cross-level interaction was added to examine
the relationship between inertia and baseline well-being
indicators (SWL, NA and PA, all centered around grand
mean). A separate model was tested for each indicator.
Finally, linear regression was performed with well-
being indicators at Time 2 as dependent variables and
random intercept and random slope as explanatory vari-
ables after control for baseline well-being and selected
demographic variables (sex, age, education, relationship
status and employment status) and clinical variables
(duration of HIV infection, duration of antiretroviral
treatment, CD4 count, and AIDS stage). With Bayesian
estimation, and under the assumption of a missing at ran-
dom pattern, all the available data in a way optimal for
modeling were used [31]. e analyses were conducted
with IBM SPSS version 25 and Mplus version 8.2.
Results
Descriptive statistics andpreliminary analysis
Table 1 presents descriptive statistics of the variables
used in the study. For negative and positive emotions,
they represent values aggregated across persons and
days. Subjective well-being indicators at Time 2 were
related only to some demographic and clinical variables.
For SWL significant correlate was education (β = 0.32,
p < 0.001), whereas for PA relationship status (β = 0.34,
p < 0.00) and CD4 count (β = −0.25, p = 0.008). No sig-
nificant correlates for NA at Time 2 were found. us, in
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Rzeszuteketal. Health Qual Life Outcomes (2021) 19:105
the regression analysis models, only selected control vari-
ables are included, depending on the explained variable.
Average emotional inertia andits relationship
withbaseline subjective well‑being
As shown in Table2, the average emotional inertia for
NA and PA is positive and significant, which suggests
an expected carryover effect from one day to the next.
Specifically, a higher level of negative emotions the day
before was associated with a higher level of this emotion
on the following day. e same pattern was observed for
positive emotions. e explained variance expressed by
within-level R-square averaged across clusters was 25%
and 22% for NA and PA, respectively.
Additionally, subjective well-being did not modify this
carryover effect. Satisfaction with life and positive affect
were significantly related only to random intercept, indi-
cating that people who had a higher SWL and PA also
reported a higher average level of positive emotions and
lower average level of negative emotions during the diary
part of the study.
Emotional inertia aspredictor ofsubjective well‑being
Table3 shows the results of regression models longitu-
dinally predicting subjective well-being from emotional
inertia after control for baseline well-being, average level
of emotions reported during daily dairy and selected
sociodemographic and clinical variables. For all the sub-
jective well-being indicators, neither PA nor NA iner-
tia predicts well-being change within one year among
PLWH. In each model, the baseline level of well-being is
significantly associated with the outcome. Additionally,
an average PA reported during diary assessment is a posi-
tive predictor of SWL and PA and a negative predictor
of NA, which means that it uniquely predicts well-being
Table 1 Descriptive statistics for the study variables
M—mean; SD—standard deviation; NE, PE—Daily negative and positive
emotions, respectively; SWL—Satisfaction with life; NA, PA—Negative and
Positive aect, respectively; subscripts 1 and 2 denote rst and second
measurement
Variable M SD Min–Max Skewness Kurtosis
Daily emotions
NE 2.04 0.84 1–5 0.98 0.32
PE 2.91 0.89 1–5 − 0.08 − 0.55
Subjective Well‑being
SWL_1 20.87 6.38 5–35 − 0.30 − 0.61
SWL_2 19.34 5.79 5–35 0.20 − 0.06
NA_1 2.19 0.88 1–4.5 0.69 − 0.38
NA_2 2.10 0.74 1–3.9 0.55 − 0.88
PA_1 3.36 0.73 1–4.7 − 0.43 − 0.07
PA_2 3.30 0.72 1.6–4.6 0.14 − 0.61
Table 2 Results of multilevel autoregressive models estimating emotional inertia and its associations with baseline level of subjective
well‑being model results
Standardized results are within-level standardized estimates averaged over clusters. All the results provided for well-being indicators are standardized. ***p < .001
Model Daily negative emotions Daily positive emotions
Est 95%CI Est 95%CI
LL UL LL UL
Autoregressive only
Raw
mean 2.01*** 1.79 2.14 2.90*** 2.75 3.06
inertia .45*** .34 .55 .38*** .24 .52
Standardized
mean 1.74*** 0.95 3.62 1.26*** 0.66 2.21
inertia .44*** .35 .53 .38*** .23 .51
Satisfaction with life
mean − .44*** − .72 − .18 .54*** .36 .93
inertia .03 − .25 .32 .08 − .19 .38
Negative aect
mean .23 − .04 .48 − .21 − .46 .01
inertia .16 − .16 .51 .01 − .33 .24
Positive aect
mean − .31*** − .61 − .03 .48*** .29 .84
inertia − .26 − .59 .00 − .22 − .51 .02
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Rzeszuteketal. Health Qual Life Outcomes (2021) 19:105
above and beyond its baseline values. For an average daily
NA, this is the case only for NA.
Discussion
e results of our study were inconsistent with our
research hypothesis. We observed that SWB does not
modify daily emotional inertia and that daily emotional
inertia does not predict one year changes in SWB with
regard to any of its components (SWL, NA, and PA). As
far as these separate SWB elements are concerned, we
found an interesting pattern illustrating that only mean
values of collected daily PE and NE added significantly to
prediction of long-term SWL (only mean values of daily
PA), long-term PA (only mean values of daily PA), and
long-term NA (both daily PA and NA), after control for
baseline level of each of these components.
In trying to interpret the aforementioned, unexpected
null result regarding the emotional inertia, it is vital to
underline that contemporary research on this phenom-
enon focused on its link predominantly with negative
measures of well-being or psychopathology [for meta-
analysis, see 16], which may lead to bias in extrapolating
these findings on positive indicators of well-being [26].
It can therefore be assumed that, in the light of current
knowledge emotional inertia should be treated less as a
predictor of broadly operationalized well-being and more
as merely a correlate of maladjustment or psychopathol-
ogy only [26, 32]. Lastly, the null result obtained in our
study could also stem from the fact that we focused on
emotional inertia as a predictor of SWB change and not
on a cross-sectional relationship between these con-
structs, a design that dominates in emotional inertia
research [16]. However, among PLWH, SWB did not
moderate autoregressive effect of both valences of daily
emotions, thus this finding was also not replicated.
In this context, it is worthwhile to mention that some
authors are generally more skeptical about the utility of
emotional inertia and other modern conceptualizations
of emotional regulation expressed by complex dynamic
measures (e.g., emotion variability, emotional instability)
in predicting psychological well-being or psychopathol-
ogy [33, 34]. Specifically, a recent meta-analysis con-
ducted by Dejonckheere etal. [34] showed that dynamic
affect measures entail very limited added value over
mean levels of positive and negative affect in the process
of predicting individual differences in well-being (i.e., life
satisfaction, depressive symptoms, and borderline symp-
toms). When there is a control for the mean level of PA
and NA, which was the case in our study, a lack of unique
explanatory power of these dynamic constructs is likely
to be observed. us, the effects of these dynamic meas-
ures of affect should always be adjusted for an average
emotional intensity [33].
e obtained results should also be discussed in the
context of the specificity of the studied sample. Dis-
tress associated with a serious chronic health condition
affects many areas of daily functioning, but long-term
patterns of affective adaptation to such conditions tend
to follow the hedonic treadmill model [4], i.e., "stability
despite loss" [35]. It was found that despite daily emotion
Table 3 Results of linear regression models predicting subjective well‑being one year later from emotional inertia after control for
well‑being baseline level
All the provided results are the within-level standardized estimates averaged over clusters. For Satisfaction with life and Daily negative emotions model:
education = .20, 95% CI (.08, .31), p < .001. For Satisfaction with life and Daily positive emotions model: education = .19, 95% CI (.07; .31), p < .001. For Positive aect
and Daily negative emotions model: relationship status = .20, 95% CI (.09, .31), p < .001; CD4 count = − .17, 95% CI (− .27, − .06), p < .001. For Positive aect and Daily
positive emotions model: relationship status = .20, 95% CI (.09, .32), p < .001; CD4 count = − .14, 95% CI (− .25, − .04), p = .005. Education was coded 1—having a
university degree, 0—not having a university degree. Relationship status was coded 1—being in a stable intimate relationship, 0—being single
***p < .001, **p < .01, *p < .05
Model Satisfaction with life Negative affect Positive affect
Est 95% CI Est 95% CI Est 95% CI
LL UL LL UL LL UL
Daily negative emotions
Baseline .40*** .28 .50 .18** .05 .31 .41*** .29 .51
NE mean − .45 − .79 .02 .65** .14 .95 − .30 − .75 .14
NE inertia .01 − .49 .49 − .004 − .49 .43 − .03 − .48 .48
R2.47*** .22 .92 .52*** .10 .94 .40*** .22 .88
Daily positive emotions
Baseline .35*** .22 .47 .19*** .06 .31 .37*** .24 .48
PE mean .57*** .22 .88 − .43*− .94 − .01 .55*** .10 .86
PE inertia − .08 − .44 .26 .13 − .27 .52 − .10 − .50 .24
R2.54*** .26 .94 .29*** .06 .94 .56*** .26 .95
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Rzeszuteketal. Health Qual Life Outcomes (2021) 19:105
dysregulation due to HIV stigma [8, 11] PLWH also dis-
play remarkably stable PA and NA many years after HIV
diagnosis, which is not associated with HIV-related bio-
markers [36–38].
us, dysregulation, even if present, did not necessarily
lead to long-term changes in well-being, which is similar
to our results.
However, one may assume that among PLWH some
atypical values of emotional inertia could be found, but
it seems unlikely. On average, the inertia level and direc-
tion tend to be similar to values already reported in other
samples [16]. Moreover, our participants showed a sub-
stantial variability in this regard; there were some for
whom high emotional carryover from one day to the next
one could be found, and others for whom this value was
close to zero. us, there is no reason to consider that
the obtained results reflect highly specific processes not
observable in other groups.
To sum up, in the studied sample of PLWH there was
a significant inertia for both positive and negative emo-
tions. However, it did not depend on the baseline level
of well-being, nor was it a predictor of its change, both
in terms of satisfaction with life and long-term affective
functioning.
Strengths andlimitations
Our study has several unique strengths: it is a theory-
driven, longitudinal assessment of study variables from
two temporal modes (i.e., daily fluctuations and long-
term changes). Also, taking into account the complexity
of the study design (and especially the clinical sample
of PLWH, which had never previously been investi-
gated in the context of emotional inertia), the number
of participants can be regarded as sufficient. In terms
of limitations, the daily diaries consisted of only a few
days; this might affect the validity of the inertia indi-
cator. Additionally, we probably could not have avoided
a selection bias typical of extensive study designs, with
significant burden over the participants, as our sam-
ple consisted of highly functional PLWH with well-
controlled HIV infection. us, it is also important to
consider the broader socio-cultural context relevant
to research on the well-being of PLWH [38]. In short,
it concerns mainly illness perception, minority stress,
and stigmatization at both individual and societal
level, which are associated with objective and subjec-
tive determinants of access to treatment [39]. In Poland
most of the funding from the National HIV Preven-
tion and AIDS Control Program [40] goes to treatment
rather than prevention and education, and access to
mental health care for the HIV/AIDS population is still
very limited. erefore, it would be worthwhile addi-
tionally control the results for depression symptoms.
Nonetheless, every person diagnosed with HIV has
guaranteed access to free antiretroviral treatment,
compliant with the current World Health Organiza-
tion guidelines. In this sense, the study sample is fully
homogeneous, although may differ significantly from
samples with more limited access to treatment.
Conclusions
e results of our study show that more caution is
needed in implementing novel theoretical constructs
regarding emotion regulation and related complex and
dynamic measures. As promising as they can be, the
uniqueness of these constructs’ explanatory power over
more straightforward emotion indicators is still waiting
to be proven. Until then, there is a risk of multiplying
redundant findings, especially when there is a publica-
tion selection bias in favor of positive results. is bias
may create an illusion of progress in emotion research,
but in fact it is reinventing the wheel [37]. Overall, it
seems that while emotional inertia is somehow related
to dysfunctional patterns of affect in psychopathol-
ogy [15], it does not exert a significant effect within
the more normative range of affective functioning
[36], including among PLWH [41]. ese latter results
should be taken into an account in developing interven-
tions to improve the quality of life of PLWH, especially
if the targeted mediating factor is an effective emotion
regulation. For example, future studies should con-
centrate on the exploration of emotional inertia in the
context of daily HIV/AIDS stigma. If emotional inertia
does not predict PLWH’s well-being, the open question
is whether it could be responsible for the mechanism
of stigma-related emotion dysregulation in this patient
group on a daily basis [8].
Abbreviations
PLWH: People living with HIV; SWB: Psychological well‑being; PA: Positive
affect; NA: Negative affect.
Acknowledgements
The authors thank medical doctors from Warsaw’s Hospital for Infectious
Diseases for help in participants’ recruitment process.
Authors’ contributions
MR was the main investigator, who designed the study, collected the data,
wrote the paper and participating in data analysis. EG participated in the study
design, analysed and interpreted of the data and revised the final draft. EW‑B
participated also in study design and prepared of draft version of manuscript.
All authors read and approved the final manuscript.
Funding
This study was founded by the National Science Center, Poland, research
project no. 2016/23/D/HS6/02943.
Availability of data and materials
The datasets used and/or analysed during the current study available from the
corresponding author on reasonable request.
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Rzeszuteketal. Health Qual Life Outcomes (2021) 19:105
Declarations
Ethics approval and consent to participate
All procedures performed in studies involving human participants were in
accordance with the ethical standards of the institutional and/or national
research committee and with the 1964 Helsinki declaration and its later
amendments or comparable ethical standards. This study was approved by
the ethics committee of the Faculty of Psychology, University of Finance and
Management in Warsaw. All participants sing informed consent.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1 Faculty of Psychology, University of Warsaw, Stawki 5/7, 00‑183, War‑
saw, Poland. 2 Faculty of Psychology, SWPS University of Social Sciences
and Humanities, Chodakowska 19/31, 03‑815 Warsaw, Poland. 3 Warsaw’s
Hospital of Infectious Diseases, Wolska 37, 01‑201 Warsaw, Poland.
Received: 14 October 2020 Accepted: 18 March 2021
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