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The role of resilience in daily
experiences of posttraumatic
growth, aect, and HIV/AIDS
stigma among people living
with HIV
Małgorzata Pięta * & Marcin Rzeszutek
This study investigated the intraindividual variability in daily posttraumatic growth (PTG) versus
posttraumatic depreciation (PTD), positive and negative aect (PA and NA), and HIV/AIDS stigma
among people living with HIV (PLWH). In particular, we examined whether this variability derives
from participants’ resilience operationalized on a trait level. The participants included 67 PLWH, who
completed a baseline questionnaire on resilience, measured with the Brief Resilience Scale. Following
this, they completed the shortened versions of the following inventories over ve consecutive days:
the Posttraumatic Growth and Posttraumatic Depreciation Inventory V Expanded version Inventory,
the Positive and Negative Aect Schedule – Expanded Form, and the Berger HIV Stigma Scale.
Hierarchical linear modeling (HLM) was utilized to analyze the study results. We observed signicant
intraindividual variability in PTG, PTD, PA, NA, and perceived HIV/AIDS stigma. Resilience was
related to PTG, PTD, PA, and NA but not to stigma. Moreover, higher resilience was associated with
higher, stabler PA and lower, stabler NA. Our results highlight the need of further studies on the
daily functioning of PLWH. Specically, while health status is important, it does not appear to be
the predominant source of everyday distress for PLWH. Consequently, psychological counselling for
PLWH should concentrate more on the life of the person as a whole and not only on coping with HIV
infection.
Stories of growth aer trauma and adversity are common throughout human history and across various cul-
tures and historical epochs1. Similarly, despite the relatively recent emergence of posttraumatic growth (PTG)
as a research area2,3, studies on PTG have proliferated quickly, creating a vast body of evidence supporting the
meaningful, positive changes following traumatic or adverse life events that have been suggested historically1.
Nevertheless, while the interest in PTG has contributed to signicant development of this eld, several questions
remain unanswered concerning the objective manifestations and stability of PTG as well as the mechanisms
underlying positive changes4. Specically, various limitations of classic PTG study designs and their assessment
have prevented a thorough explanation of these phenomena5. e most commonly used PTG measures, such
as the Posttraumatic Growth Inventory (PTGI)2, tend to evaluate PTG almost exclusively based on self-reports
and retrospection6. Additionally, PTG evaluation based on participants’ subjective recollections is a cognitively
demanding procedure prone to signicant biases, especially when studied only cross-sectionally7. Nevertheless,
the extensive critique of previous PTG research has inspired a search for methodological advancements in this
eld and multimethod approaches for studying and measuring PTG5.
First, the inclusion of parallel items that reect negative changes in standard PTG tools has been suggested as
a way to overcome positivity bias in PTG measures that focus exclusively on growth8,9. is led to the emergence
of a new construct of posttraumatic depreciation (PTD), revealing some counteractive patterns of posttraumatic
change, such as the simultaneous occurrence of PTG and PTD, as well as dierent predictors shared among
various populations aer trauma10,11. Second, the use of longitudinal study designs has been proposed to answer
questions regarding potential PTG dynamics over time4. Finally, to overcome the limitations of retrospective
PTG reports and related biases, authors have increasingly advised more ecological, daily PTG assessments6. In
particular, intensive longitudinal measurement using experience sampling methods or electronic daily diaries
OPEN
Faculty of Psychology, University of Warsaw, Stawki 5/7, 00-183, Warsaw, Poland. *email: mj.pieta@uw.edu.pl
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has been suggested as a way to verify whether PTG manifests in people’s everyday lives aer trauma or is only
a retrospective, illusory belief among trauma survivors12–14. In other words, a new type of PTG measurement
could elucidate short- and long-term PTG dynamics, oering key insights for implementing PTG-focused clini-
cal interventions6,15.
Moreover, the noted limitations in this eld have also led to several ambiguities concerning how to identify
PTG predictors16. One such ambiguity concerns the relationship between PTG and resilience. We do not know
if the constructs’ overlap or whether PTG is supported or inhibited by the baseline resilience levels of individuals
who have experienced traumatic life events17,18. Although resilience can be considered a PTG-promoting factor,
it may also reinforce resistance to negative emotions and promote “bouncing back” to baseline levels of function-
ing aer trauma rather than growth13,19. ese processes have been particularly understudied in the context of
the daily manifestations of resilience and its impact on psychological well-being during stress and adversity20,21.
Psychological resilience can be understood as a stable trait or an ability that supports both the maintenance and
generation of positive emotions during stressful situations19,22. Still, since it occurs within the PTG context, few
studies have used intensive measurement methods to track daily manifestations of resilient functioning during
stress or trauma (e.g.,6,23–26). Similarly, no previous research has examined the daily within-person variability of
PTG and its association with baseline resilience levels in trauma-aected populations. Parallel measurement of
PTG and resilience may provide a better understanding of this association and its clinical implications for specic
populations following health-related trauma, including people living with HIV (PLWH)27.
Investigating PTG among PLWH may shed new light on the process of adaptation to HIV infection28. Several
studies have demonstrated the link between PTG, better mental health, and increased adherence to treatment
among PLWH (see metanalysis27). However, to better understand this process, it is necessary to explore the
mutual association between PTG and resilience in this clinical sample29–31. In particular, the extent to which
these constructs overlap with each other or the degree to which they inuence one another in this sample are
unknown30,31. Consequently, some authors have suggested the need to analyze environmental variables, such as
HIV/AIDS stigma29,32, especially based on daily assessments33.
e daily life experiences of PLWH remain a relatively understudied research area34–36. However, for individu-
als experiencing chronic but manageable and non-acute stress conditions, such as living with HIV, monitoring of
their aective states is crucial34. Vulnerable clinical populations are subjected to dynamic stress circumstances,
such as HIV/AIDS stigma, which should be monitored in these patients’ daily lives33. A particularly interest-
ing question is whether daily uctuations in PLWH’s positive and negative well-being are associated with their
baseline levels of various stable personal characteristics33,34. Accordingly, we focused on assessing the role of
psychological resilience in the daily lives of PLWH in this study.
Specically, this study aimed to investigate intraindividual variability in daily PTG and PTD levels, self-
reported aect (PA/NA), and HIV/AIDS stigma intensity among PLWH. Additionally, we sought to examine
whether this variability on a state level derives from resilience on a trait level, which was measured on the rst day
of the study. To the best of our knowledge, no previous studies have examined such factors among PLWH using
this particular study design and these specic variables, from which we derived our hypotheses. us, our study
is mainly explorative. However, based on research on the daily psychosocial functioning of PLWH (e.g.34–37),
the association between resilience measurements and intraindividual uctuations in aective well-being in the
general population20,21, and research on HIV/AIDS stigma38, we formulated the following hypotheses:
Hypothesis 1. PLWH experience intra-individual variability in their daily reported levels of PTG and PTD,
PA and NA, and perceived HIV/AIDS stigma.
Hypothesis 2. e intra-individual variability in PLWH’s daily reported levels of PTG and PTD, PA and NA,
and perceived HIV/AIDS stigma measured at the state level is related to resilience at the trait level.
Methods
Participants and procedure. Sixty-seven patients who had been diagnosed with HIV were included in
this study. e measurements were conducted at the beginning of 2021 as part of a larger project, for which
the data collection was nalized at the beginning of 2022. Of the patients who provided their contact informa-
tion on the paper-and-pencil survey, 67 who did not drop out from any measurements were chosen for further
participation and analysis in this study, from whom 14 (20.9%) were women. e mean age of the participants
was 40.76 (SD = 11.28). 32 (47.8%) participants stayed in a stable relationship. e minority, i.e., 15 (22.4%)
participants, was heterosexual and the rest of the sample was of homosexual orientation. 13 (19.4%) PWLH
had an ongoing problem with substance misuse. 40 (59.7%) participants received higher education, 25 (37.3%)
identied with secondary education, while 2 (3%) persons had primary or vocational schooling. More than a
half of participants (43; 64.2%) had regular employment, while the rest was unemployed (11; 16.4%), received a
pension (10; 14.9%) or retired (3; 4.5%). 11 (16.4%) participants described their nancial situation as very good,
28 (41.8%) stated it was good, 11 (29.9%)—medium. 6 (9%) participants described their situation as bad, and 2
(3%) as very bad. 9 (13.4%) PLWH entered the AIDS stage. 5 (7.5%) participants had a detectable viral load. e
mean ARV treatment time among the study sample was 7.07years (SD = 5.89). Table1 presents the demographic
characteristics of the study sample.
Participants were recruited from Warsaw’s largest healthcare clinic for PLWH. During the initial measurement
session, participants completed a paper-and-pencil version of the psychometric questionnaires (see Measures),
including the sociomedical survey. ey were also asked to provide their email address or telephone number for
further contact during the diary part of the study. Only participants who agreed to provide their contact infor-
mation were included in this further part of the study. Participants were informed that involvement in the study
was voluntary and that no remuneration would be provided. Medical doctors also assessed patients for further
eligibility criteria, such as being at least 18years old, having a medical HIV infection diagnosis, having undergone
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antiretroviral treatment, and having no cognitive disorders. e viral suppression and entering the AIDS phase
of HIV infection, were controlled throughout a one-year period as part of a larger longitudinal project. ese
two health parameters remained stable among study participants that received complex healthcare in specialized
HIV clinic in Warsaw, Poland. e whole project consisted of three classical and three diary measurements that
took place in aermath of the rst stage described in the article.
In the preliminary stage of this study, patients’ characteristics, such as their socio-demographic and medical
data, and resilience levels were measured at a trait level (see the following two subsections). For the electronic
daily diary measurements, we prepared shortened electronic versions of the questionnaires measuring state-like
variables (PTG and PTD, PA and NA, and HIV/AIDS stigma) using a special online platform. Participants were
asked to complete electronic diaries for ve consecutive days (Monday to Friday). e diaries were provided
by e-mail at the end of each study day. Links were sent to participants at 6:00 PM, followed by a reminder at
9:00 PM. On each study day, these links stayed active until 1:00 AM the following day, at which point they were
deactivated. Participants were invited to contact the study organizers via email or telephone throughout the
whole study period if they needed any technical help accessing the diaries.
e study methodology was approved by the ethical committee of the Faculty of Psychology of the University
of Warsaw, and the study was carried out in accordance to relevant guidelines and regulations. Informed verbal
consent was obtained from all participants. Informed verbal consent was obtained from all participants and this
procedure was approved by the ethics committee of University of Warsaw.
Materials
Trait‑level measurement. e Brief Resilience Scale (BRS). e Polish adaptation of the Brief Resilience
Scale (BRS) scale19 was used in this study as the paper-and-pencil measurement of the participants’ trait-level
resilience. BRS is a six-item scale that employs a ve-point Likert response, ranging from 1 (strongly disagree) to
5 (strongly agree). e Cronbach’s alpha for the total resilience score was satisfactory (see Table2).
State‑level measurement. Shortened version of the posttraumatic growth and posttraumatic depreciation
inventory: expanded version (PTGDI‑X). PTG and PTD were measured with a 10-item scale, ve of which
measured each construct in the 50-item PTG and PTD Inventory (PTGDI-X)39. We chose 10 items, one from
each of ve subscales of PTG and PTD measures, which most strongly loaded on the relevant global PTG and
PTD factors. Responses ranged from 0 (I did not experience this change) to 5 (I experienced this change to a
great degree). Higher scores indicate more intense PTG or PTD levels. We did not count the subscale indicators.
Instead, we calculated the global PTG and PTD scores, which reect the sum of all items in the PTG and PTD
domains, respectively. Participants were instructed to focus on daily positive and negative experiences in their
Table 1. Participants’ demographic characteristics (n = 67). M mean value, SD standard deviation, n number
of participants in a category.
n%
Gender Wom en 14 20.9
Men 53 79.1
Age 23–73 M = 40.76; SD = 11.28
Relationship In a stable relationship 32 47.8
Education
Primary 1 1.5
Vocational 1 1.5
Secondary 25 37.3
Higher 40 59.7
Employment
Regular employment 43 64.2
Unemployed 11 16.4
Pension 10 14.9
Retired 3 4.5
Subjective nancial status
Very good 11 16.4
Good 28 41.8
Medium 20 29.9
Bad 6 9.0
Very bad 2 3.0
Sexual orientation
Heterosexual 15 22.4
Homosexual 46 68.7
Other 6 9.0
Addiction Ongoing use 13 19.4
AIDS Diagnosed 9 13.4
Viral load Detectable 5 7.5
ARV treatment In years 0.50–30 M = 7.07; SD = 5.89
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lives aer receiving their HIV diagnosis, such as “I felt that I have numerous opportunities” or “I felt that I cannot
change much in my life.” We used this state-level measure of PTG and PTD following the recommendation by
Blackie etal.6. e Cronbach’s alphas for the global PTG and PTD scores were satisfactory (see Table2).
e shortened version of the positive and negative aect schedule‑expanded form (PANAS‑X). Participants
reported the aective states they experienced during a study day using a ve-point Likert scale ranging from 1
(not at all) to 5 (strongly). A list of 12 feelings and emotions was provided. We chose an equal number of items
from the PA and NA subscales, with six for PA (e.g., “satised,” “energetic”) and six for NA (e.g., “angry,” “wor-
ried”), which were also strongly loaded on the PA and NA scales40. e Cronbach’s alpha coecients obtained in
this study were satisfactory (see Table2).
e Berger HIV stigma scale (HSS). e shortened version of the Polish adaptation of the HIV/AIDS stigma
inventory (Berger HIV Stigma Scale [HSS])41 was used to measure daily experiences of stigma. As for the previ-
ous measures, the most representative, strongly loaded items from with subscale were selected. is electronic
inventory consisted of ve items, such as “I felt that others who know or may know about my HIV infection may
have had a bad opinion about me.” Answers were provided using a Likert scale ranging from 1 (strongly disagree)
to 4 (strongly agree). In this study, the total HIV/AIDS score was used. e Cronbach’s alpha for the total stigma
score was satisfactory (see Table2).
Data analysis. During our preliminary analysis, we calculated the descriptive statistics. Next, hierarchical
linear modeling (HLM) was used to assess the participants’ intra-individual variability in PTG and PTD, PA
and NA, and stigma levels over ve consecutive days as well as its relationship to interindividual dierences in
resilience, which were measured using the scales described in the previous subsections. HLM (known as multi‑
level modeling) is a statistical method that uses ordinary least square (OLS) regression-based analysis to measure
the hierarchical structure of data42. Hierarchically structured results are nested data, where groups of units are
clustered together in a specic pattern, which vary at more than one level.
PTG and PTD, PA and NA, and levels of HIV/AIDS stigma over ve consecutive days were analyzed as
dependent variables. Each dependent variable was analyzed in a separate model. e measurements—for exam-
ple, time variables in days—were analyzed as covariates and xed eects. Random eects for intercepts and
temporal eects were also included. Each model was analyzed twice: with and without resilience levels included
Table 2. Descriptive statistics of analyzed variables among participants. M mean value, SD standard deviation,
min minimum value, max maximum value, S skewness, K kurtosis; α Cronbach’s α reliability coecient.
Day Variables M SD min max S K α
Day 1
Resilience 21.35 5.97 9.00 30.00 − 0.45 − 0.76 0.92
Positive aect 2.78 0.89 1.00 4.67 0.18 − 0.20 0.88
Negative aect 2.08 0.93 1.00 5.00 0.11 0.67 0.91
PTG 2.98 1.07 0.00 5.00 − 0.70 0.53 0.76
PTD 1.21 1.16 0.00 4.20 0.10 0.18 0.82
Stigma 1.78 0.77 1.00 4.00 0.16 0.67 0.91
Day 2
Positive aect 2.86 0.90 1.00 4.67 − 0.23 − 0.38 0.86
Negative aect 1.94 0.90 1.00 5.00 0.59 0.53 0.89
PTG 2.97 1.06 0.00 4.80 − 0.84 0.80 0.75
PTD 1.03 1.05 0.00 4.00 0.21 0.89 0.79
Stigma 1.74 0.77 1.00 4.00 0.09 0.76 0.92
Day 3
Positive aect 2.82 0.82 1.00 4.67 0.08 − 0.23 0.83
Negative aect 1.97 0.84 1.00 4.83 0.52 0.13 0.87
PTG 2.99 1.02 0.00 5.00 − 0.33 0.01 0.73
PTD 1.02 0.94 0.00 4.00 0.94 0.63 0.70
Stigma 1.67 0.72 1.00 4.00 0.18 0.24 0.89
Day 4
Positive aect 2.97 0.80 1.00 4.83 − 0.63 0.57 0.83
Negative aect 2.02 1.05 1.00 5.00 0.24 0.61 0.93
PTG 3.03 1.00 0.80 5.00 − 0.42 − 0.39 0.71
PTD 1.17 1.15 0.00 4.00 0.01 − 0.02 0.82
Stigma 1.70 0.78 1.00 4.00 0.15 0.92 0.92
Day 5
Positive aect 2.94 0.90 1.00 4.50 − 0.07 − 0.67 0.87
Negative aect 2.02 0.97 1.00 5.00 0.26 0.18 0.92
PTG 2.99 1.02 0.00 4.40 − 0.94 0.06 0.74
PTD 1.17 1.08 0.00 5.00 0.39 0.24 0.80
Stigma 1.66 0.76 1.00 4.00 0.14 0.87 0.92
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as a covariate. is solution allowed for comparisons regarding the variance in results acquired across consecu-
tive days when resilience was and was not considered. e models that included resilience also included also the
xed eects of resilience and resilience over time.
Ethical approal. 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.
Results
Table2 presents descriptive statistics for the analyzed variables. All variables were measured with adequate
reliability. e values of skewness and kurtosis did not exceed a range of − 1.0 to 1.0; therefore, HLM based on
ordinary least square method could be applied. No substantial dierences between mean values acquired in the
consecutive measurements were observed.
e main analysis was performed using the HLM. e results of this analysis are depicted in Table3.
No statistical eect of time was observed which means that there were no statistical dierences between the
consecutive days in general. Statistically signicant positive relationships were found between resilience levels,
average PTG levels, and PA over ve consecutive days. Also, signicant negative relationships were found between
resilience levels, average NA levels, and PTD over ve consecutive days. No statistically signicant relationship
was found between resilience levels and average stigma levels. e values of estimated variance fell aer resilience
was included in calculating PA and NA. A corresponding eect was not observed in our analysis of PTG, PTD,
and stigma. Additionally, resilience levels were important in determining the dynamics of aect changes, such
that higher resilience was associated with higher, stabler PA and lower, stabler NA. In contrast, resilience levels
were related to PTG and PTD’s daily intensity (see above), but they did not aect the stabilization of day-to-day
Table 3. Relationships between resilience, time, and daily levels of PTG or PTD, positive aect, negative aect,
and HIV/AIDS stigma among participants.
Dependent variable
Resilience included
Estimate p
PTG
No Time − 0.006 0.840
Time variance 0.017 0.063
Yes
Time 0.007 0.949
Resilience 0.065 0.003
Resilience × time − 0.001 0.883
Time variance 0.018 0.052
PTD
No Time 0.033 0.931
Time variance 0.020 0.040
Yes
Time − 0.041 0.734
Resilience − 0.059 0.009
Resilience × time 0.002 0.710
Time variance 0.021 0.032
Positive aect
No Time 0.043 0.124
Time variance 0.003 0.616
Yes
Time 0.158 0.124
Resilience 0.068 0.001
Resilience × time − 0.006 0.220
Time variance 0.002 0.650
Negative aect
No Time − 0.006 0.839
Time variance 0.015 0.068
Yes
Time − 0.102 0.364
Resilience − 0.051 0.008
Resilience × time 0.005 0.358
Time variance 0.011 0.093
Stigma
No Time − 0.027 0.082
Time variance 0.006 0.045
Yes
Time − 0.023 0.690
Resilience − 0.015 0.339
Resilience × time 0.000 0.910
Time variance 0.006 0.045
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changes. e values of estimates of variance dropped aer adding resilience in case of positive aect and negative
aect are presented at Figs.1 and 2).
Discussion
e results of our study mostly supported our rst hypothesis, as we observed signicant intraindividual variabil-
ity in daily PTG and PTD, PA and NA, and perceived HIV/AIDS stigma levels among participants. Our ndings
contribute to the literature on PLWH’s daily functioning, an understudied subject, as our analysis was not limited
to coping with HIV infection but rather examined the everyday lives of PLWH35,43–45. Previous studies on this
topic have focused on rather narrow aspects of PLWH’s function, predominantly HIV symptoms, substance use
and abuse, or adherence to treatment38. In other words, those studies were conducted under the implicit assump-
tion that PLWH are entirely preoccupied with their HIV-positive status and its associated distress46. However,
great progress in treatment has changed HIV infection from a fatal to a chronic, manageable health condition47.
us, health status remains important but is not necessarily the main cause of PLWH’s stress and well-being
issues35. Despite sharing a source of distress—their HIV-positive status—PLWH’s psychological functioning may
uctuate daily, and these uctuations may be associated with signicant individual dierences in their psycho-
logical functioning over time36,48. Studies employing an intensive longitudinal study design, assessing behaviors
as they occur in real time in an individual’s natural surroundings, may increase ecological validity and provide
a unique opportunity to monitor individual dierences among this patient group12,35.
Within the PTG literature, our study is the rst to identify daily manifestations of this positive phenomenon
in the clinical population. Previously, only Blackie etal.6 showed signicant within-person variability in daily
state-level PTG among a sample of college students aer adverse life events. Measuring PTG daily could oer
important insights on the longstanding debate regarding PTG’s real versus illusory nature, which has been
predominantly assessed via retrospective questionnaires4,7,14. It remains unknown whether any stable changes
(positive or negative) really occur aer trauma or whether these changes can occur in daily life and be identi-
ed retrospectively through self-reports. More studies assessing PTG daily are needed to prove whether PTG
is just a trait-like tendency to retrospectively declare positive changes following adversity or whether it can be
operationalized as a state-like term that manifests in trauma survivors’ day-to-day behaviors6,13.
e results of the current study also supported our second hypothesis to an extent. On the one hand, we
found respectively positive and negative relationships between resilience levels and average PTG and PTD levels
among participants. A similar association was observed for aective well-being: a positive relationship with PA
and a negative relationship with NA. However, we noted that resilience levels were important for aect alone, and
higher resilience was linked to higher, stabler PA and lower, stabler NA. Concerning PTG and PTD, we found no
such stabilization of day-to-day changes as a result of resilience. Further, we observed no relationship between
daily HIV/AIDS stigma intensity and resilience. Our ndings contribute to the long-term debate on the status of
psychological resilience (e.g.18,19,49,50). In particular, whether resilience should be operationalized and measured as
a static trait or as a dynamic state remains unknown, as do the consequences of these operationalizations for the
association between resilience and well-being across various samples following stressful and adverse life events20.
ese ambiguous ndings are partially linked to the measurement limitations of resilience studies, which have
mainly employed cross-sectional designs and focused only on signicant life challenges. Almost no research has
been conducted on the association between resilience and daily stressors and well-being outcomes20. Previously,
only Ong etal.21 found that psychological resilience assessed on the trait level is related to intraindividual vari-
ability in daily emotional responses to stress among older adults, with higher trait resilience predicting faster
recovery from daily stress due to a high level of positive emotions. Moreover, Ong etal.21 claimed that, although
positive emotions are a fundamental feature of trait resilience, they cannot be reduced to a simple byproduct of
resilience50. ey found that resilient individuals oen adopt positive emotion-eliciting coping strategies, such
as benet nding and positive reappraisal, which regulate their negative aective experiences50. Overall, high
resilience seems to give individuals greater access to momentary positive emotional resources, which are also
stabler over time, thus protecting them better from daily stress compared to less resilient people21. Additionally,
resilience may inuence levels of emotional complexity, promoting greater dierentiation, control, and separa-
tion between PA and NA when experiencing stress in daily life51,52.
Finally, our study is the rst to observe the relationship between resilience assessed on the trait level and PTG
operationalized daily. us, it oers an important contribution to the ongoing debate on the association between
resilience and PTG, particularly among PLWH, an issue that has elicited mixed views (see:29–31). Moreover, the
lack of a link between trait-level resilience and daily stigma may suggest that HIV/AIDS stigma is a dynamic and
transient phenomenon that is not rooted in the individual, stable characteristics of PLWH but rather associated
with external social conditions33. In other words, regardless of intrinsic factors, for PLWH stigma is highly situ-
ational or environmental. is nding may suggest possible interventions, such as focusing less on addressing
a person’s individual traits and more on providing positive social support and improving the patient’s external
environment as well as removing the social stigma and harmful prejudice associated with living with HIV.
Strengths and limitations. is study had several strengths, including its two modes of variable measure-
ment (trait- and state-level measurement), intensive longitudinal design, and clinical sample of PLWH. How-
ever, a few limitations should be noted. First, although we employed an intensive, longitudinal design, this study
was correlational, so we cannot draw any cause-and-eect explanations. Second, this study’s highly explanatory
character complicates any discussion of its implications for the wider context of PLWH’s lives. ird, we con-
trolled for a relatively small amount of sociodemographic and HIV-related clinical variables, and our sample was
heterogenous with regard to HIV infection duration. Further, we restricted our research to a sample of PLWH
who were receiving complex medical care and following ART treatment. Consequently, our participants should
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be viewed as highly functional PLWH. Future studies should focus on more heterogeneous samples of PLWH
with respect to their socioeconomic characteristics and HIV infection progression.
Figure1. Variance in positive aect in ve consecutive days without and with controlling for baseline resilience
level.
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Calls for further research. e results of our study suggest the need for further advancements in PTG
operationalization and measurement, which should focus on identifying the daily manifestations of PTG in real
life and its intraindividual variability5,6. Such research could determine whether PTG is simply a trait-like ten-
Figure2. Variance in negative aect in ve consecutive days without and with controlling for baseline
resilience level.
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dency to retrospectively declare positive changes following adversity or if it can be operationalized as a state-like
phenomenon that manifests in trauma survivors’ day-to-day behaviors. In this study, we already outlined some
potential associations between resilience and daily PTG or PTD uctuations. However, further scientic inquiry
is necessary to dierentiate between the stable and situational factors that may promote or hinder stable positive
changes amid adversity.
From the perspective of PLWH, our results call for further studies on the still-neglected subject of PLWH’s
daily functioning that are not only focused on coping with HIV infection but also consider various areas of
functioning35. In particular, aective functioning may prove to be indicative of more stable individual dier-
ences in psychological functioning associated with some of the major mental health challenges PLWH face36.
Consequently, researchers should employ intensive longitudinal designs to better identify dynamic individual
dierences in PLWH’s well-being.
Data availability
All data generated or analyzed during this study are included in this published article (and its supplementary
information les).
Received: 17 March 2022; Accepted: 13 January 2023
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Acknowledgements
is project was funded by the National Science Centre PRELUDIUM 19 (grant no. 2020/37/N/HS6/00046).
Author contributions
M.P. (Conceptualization, Methodology, Resources, Soware, Data Curation, Validation Formal analysis Investiga-
tion, Writing, Project administration, Funding acquisition).M.R. (Conceptualization supervision, Methodology,
Writing supervision, Visualization, Supervision).
Competing interests
e authors declare no competing interests.
Additional information
Supplementary Information e online version contains supplementary material available at https:// doi. org/
10. 1038/ s41598- 023- 28187-x.
Correspondence and requests for materials should be addressed to M.P.
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