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https://www.sciencedirect.com/science/article/pii/S002239991830583X
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Citations details for our article:
Rzeszutek, M., & Gruszczyńska, E. (2018). Posttraumatic growth among people living
with HIV: A systematic review. Journal of Psychosomatic Research. 114, 81-91.
DOI: 10.1016/j.jpsychores.2018.09.006.
1
RUNNING HEAD: Posttraumatic growth & HIV/AIDS
Posttraumatic growth among people living with HIV:
A systematic review
Marcin Rzeszutekª*, Ewa Gruszczyńskab
ªFaculty of Psychology, University of Warsaw, Stawki 5/7, 00-183, Warsaw, Poland.
Tel: +48 22 55 49 805, Fax: +48 22 63 57 991, e-mail: marcin.rzeszutek@psych.uw.edu.pl
bFaculty of Psychology, University of Social Sciences and Humanities, Chodakowska 19/31,
03-815 Warsaw, Poland. Tel: +48 22 517-98-56, Fax: +48 22 517 96 25, e-mail:
egruszczynska@swps.edu.pl
*To whom correspondence should be addressed
Marcin Rzeszutek
ªFaculty of Psychology, University of Warsaw, Stawki 5/7, 00-183, Warsaw, Poland, Tel: +48
22 55 49 805, Fax: +48 22 63 57 991, e-mail: marcin.rzeszutek@psych.uw.edu.pl
Conflict of interest/Ethical statement
Disclosure of potential conflicts of interest: the author declares that he has no conflict of
interest.
Ethical approval: This article does not contain any studies with human participants or animals
performed by any of the authors.
2
Abstract
Objectives. The aim of this systematic review was to analyse, synthesise and review existing
results on posttraumatic growth (PTG) among PLWH. In particular, we investigated the
relationship of PTG with sociodemographic, HIV-related clinical variables, positive and
negative psychological correlates as well as HIV-related social issues among PLWH.
Method. A literature search was performed on Web of Science, PsyARTICLES, MedLine,
Proquest and Scopus databases using appropriate descriptors for positive changes among
PLWH. Articles were analysed by title, abstract, and full text.
Results. We accepted a set of 24 articles for systematic review and analysis. Consistent
findings were obtained with respect to the positive association between psychological and
social correlates (optimism, resilience, positive reappraisal coping, positive affect, self-efficacy
and social support) and PTG among PLWH. PTG was also negatively related to various
aspects of HIV-related distress (depression, substance use, PTSD symptoms, HIV stigma). On
the contrary, sociodemographic and especially HIV-related clinical variables were mostly
unrelated to PTG among PLWH.
Conclusions. The self-reported PTG among PLWH may be related to psychological variables
rather than to objective characteristics of HIV infection itself. Nevertheless, several aspects of
research on PTG among PLWH require modification, both theoretically and methodologically.
Keywords: Posttraumatic growth; HIV/AIDS; systematic review.
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Posttraumatic growth among people living with HIV:
A systematic review
Two decades have passed since Tedeschi and Calhoun (1996) devised the concept of
posttraumatic growth (PTG), which initiated a significant shift in trauma studies from
concentrating merely on the negative consequences of traumatic events to considering also
positive changes that may occur among people struggling with such events (Linley & Joseph,
2004). These changes encompass more satisfying interpersonal relationships, finding new
possibilities in life, greater appreciation of life, openness to spiritual issues and enhanced
perception of personal strength (Tedeschi, & Calhoun, 1996). In the meantime, alternative
terms have emerged to describe positive changes after aversive life events, such as stress-
related growth (Park et al., 1996), thriving (Carver, 1998), benefit finding (BF; Tennen, &
Affleck, 2002) and adversarial growth (Linley, & Joseph, 2004). Similarly to aforementioned
concepts, PTG does not arise only as a consequence of experiencing traumatic stressors,
leading to trauma-related disorders (e.g. posttraumatic stress disorder, PTSD; American
Psychological Association, 2013), but also as a result of being confronted with highly stressful
life events. However, in contrast to above mentioned, alternative terms, in order to such
defined growth to occur, this event must be serious enough to evoke transformational changes,
which does not mean a return to balance or the level of functioning before the crisis (Tedeschi,
& Calhoun, 2004).
PTG has become one of the leading research areas of the positive psychology field
(Seligman, & Csikszentmihalyi, 2000) and resulted in a plethora of studies on positive changes
among various populations after experiencing trauma (see e.g. Helgeson et al., 2006; Prati, &
Pietrantoni, 2009). A controversial, and yet still understudied research areas, is the analysis of
PTG in the context of the trauma related to struggling with life-threatening illness (Barskova,
& Oesterreich, 2009; Casellas-Grau et al., 2017; Sawyer et al., 2010).
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The analysis of PTG in the context of illness-related trauma requires some clarification
– that is, distinguishing PTG from other concepts associated with coping with disease (e.g.
illness adjustment), as well as specifying the specific nature of this potentially trauma-related
growth. First, PTG arising from struggling with disease is different from illness adjustment,
which may also entail some positive outcomes (Bostock et al., 2009). This latter term,
described in many models of psychological adaptation to disease (see de Ridder et al., 2008)
and referring to the stress and coping model of Lazarus and Folkman (1984), assumes a
regaining of control over the disease and life and, therefore, to a greater or lesser extent, a
return to pre-disease equilibrium (Samson, & Siam, 2008). In contrast, PTG describes
transformational changes, which go beyond the process of adaptation to the disease (Casellas-
Grau et al., 2017). Adaptation, therefore, would be a return to the level of well-being
characteristic of an individual (Diener et al., 2016), while PTG would include not only
quantitative but also qualitative transformations in functioning. This conceptual distinction is
important, as some authors use these terms interchangeably or apply the term “posttraumatic
growth” to any positive constructs related to coping with illness or illness adaptation (e.g.
Bostock et al., 2009; Updegraff et al., 2002).
The diagnosis and living with a potentially fatal somatic disease together constitute a
strong stressor, which has been classified as meeting the criterion of a traumatic event
necessary for the development of posttraumatic stress disorder (PTSD; APA, 1994; Kangas,
Henry, & Bryant, 2002; Moye, & Rouse, 2014). However, the nature of medical illness-related
trauma is complex and provokes much controversy (Kagee, 2008). Edmondson (2014)
proposed the Enduring Somatic Threat model of PTSD for analysing PTSD symptoms strictly
in the context of this type of traumatic stressor. The traumatic load accompanying seriously ill
patients has a complex etiology and dynamics. Although usually initiated at the moment of
diagnosis, it also results from a later struggle with a disease, including the often painful
awareness of a justified life threat, severity of somatic symptoms and their treatment, and
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sometimes various social stressors (Mundy, & Baum, 2004). In other words, trauma
experienced by such patients applies not only to the historical moment of diagnosis but is a
continuous process induced by an interaction of somatic, psychological and social factors,
leading to present and future stressors, including potential death. This distinguishes it from the
traditionally understood traumatic stressor as an external event operating in the past (see APA,
1994, 2013). Among the authors studying PTG in the medical context, there is no agreement on
the critical moment that can potentially trigger PTG or on how much time must elapse between
this event and the appearance of possible positive changes. Most researchers assume that this
critical moment constitutes receiving an official medical diagnosis, which has been observed
mainly in the context of cancer (Stanton et al., 2006). However, other authors have found that
positive changes may occur at different stages of the disease, sometimes many years after
diagnosis, which has been observed especially with chronic disease with a high level of
unpredictability, such as HIV/AIDS (Sawyer et al., 2010).
Psychological research among people living with HIV (PLWH) has been dominated by
findings highlighting only the negative consequences of living with HIV infection, pointing to
various aspects of HIV-related distress (e.g. Ciesla, & Roberts, 2001; Israelski et al., 2007).
However, the great progress in the treatment of HIV/AIDS has not only extended the life
expectancy of PLWH (Samji et al., 2013), but changed the nature of this disease from an fatal
condition to a chronic medical problem (Deeks et al., 2013). Thus, authors have increasingly
begun to focus on various positive psychological correlates among PLWH (Ironson et al.,
2008; Moskowitz et al., 2017). One area of this topic is research on determinants and
consequences of PTG in this patient group (Sawyer et al., 2010). However, the studies
conducted so far have presented a rather fragmentary and inconsistent picture of this
phenomenon for this group of patients among PLWH, especially when it comes to its clinical
and psychological correlates (Sawyer et al., 2010).
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Aim of the review
Taking the above into consideration, the main aim of this systematic review was to
synthesise, analyse and review existing results on PTG among HIV/AIDS patients. This review
was based mainly on Tedeschi and Calhoun’s (1996, 2004) model of PTG and the related
assessment tool (see PTG Measures) as the most frequent approach. We also referred to studies
dealing with already mentioned PTG-related constructs in order to capture a broader picture of
HIV-related socio-medical and psychosocial factors associated with PTG. Thus, the aim of our
review was threefold:
1. To investigate the relationship of PTG with sociodemographic and HIV-related clinical
variables among PLWH.
The insofar studies conducted have showed that gender and age are the most important
sociodemographic characteristics related to PTG (Helgeson et al., 2006; Prati, & Pietrantoni,
2009). However, among PLWH there may be significant differences in this respect due to
infection pathways, disease progress and treatment, as well as to a link between these
characteristics and social status (Sawyer et al., 2010). This raises the question of possible
specificity of the PTG-related clinical (see CD4 count, viral load, time since HIV diagnosis,
treatment adherence, AIDS phase) and social context (see also socioeconomic status, ethnicity)
in this patient group.
2. To investigate the relationship of PTG with positive and negative psychological correlates as
well as HIV-related social issues among PLWH.
Taking into an account the current advancement in the PTG research (Jayawickreme, &
Blackie, 2014), we adopted an empirically-driven approach to identify the most frequent
psychological correlates of PTG among PLWH. Specifically, when reviewing the articles two
judges independently coded all the examined correlates of PTG and divided them into
constructs describing positive (optimism, resilience, positive reappraisal coping, positive
affect, self-efficacy) and negative (depression, substance use, PTSD symptoms) aspects of
7
functioning. They also identified the HIV-related social issues (HIV stigma and social support)
as a separate topic. Finally, the judges checked whether sociodemographic and clinical
variables were controlled in the analyses regarding these correlates to examine the plausibility
of the results obtained.
3. To provide research directions for future studies on PTG among PLWH.
Our focus was to report on the state of the art of PTG in this patient group, not an in-depth
critical analysis of the theoretical issues regarding the construct of posttraumatic growth itself.
However, in the discussion section we also referred to some controversies related to the PTG
operationalisation (Jayawickreme, & Blackie, 2014), especially in the context of chronic illness
(Casellas-Grau et al., 2017).
Method
Literature search strategy
This systematic review was conducted in accordance with the PRISMA guideliness
(Moher et al., 2009; see also Appendix) . A literature search was performed on 31 May 2018
using Web of Science, PsyARTICLES, MedLine, Proquest and Scopus databases. We used the
following keywords related to PTG: posttraumatic growth, stress-related growth, adversarial
growth, benefit finding and thriving, in conjunction with the health-related keywords, HIV and
AIDS. In Boolean algebra, the query had the following form:(“PTG” OR “posttraumatic
growth” OR “stress-related growth” OR “adversarial growth” OR “thriving” OR “benefit
finding”) AND (“HIV” OR “AIDS”). Furthermore, we searched only for papers wiritten in
English, but we did not apply any restrictions to the year of publication.
Study selection criteria
Apart from being written in English, the studies had to meet three criteria to be included
in the systematic review:
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(1) Type of study – we included only peer-reviewed, quantitative, emprical articles. We
excluded other systematic reviews or metanalyses, editorials, letters, and qualitative case
reports.
(2) Participants – we included studies dealing with HIV/AIDS patients, with no restriction on
age or stage of the disease. We also included studies in which the samples were composed of
HIV/AIDS patients and patients with other chronic illnesses. We eliminated those articles
which concentrated on caregivers of PLWH or their family members.
(3) Quality of study – we included only studies with clearly described PTG measurement,
comparable with other in the field, i.e. based on self-descriptive questionnaires directly
referring to the disease-related transformational changes in functioning.
Results
The database searches yielded a total of 2,567 abstracts: 449 hits on WoS, 7 hits on
PsycARTICLES, 53 hits on MedLine, 1986 hits on ProQuest and 72 hits on Scopus. These
were used to hand search references, which gave 30 additional records. The first part of the
review dealt with screening the abstracts for their fulfilment of the study selection criteria.
Each abstract was screened by two independent reviewers. After eliminating duplicates, 1,281
abstracts were left from five databases (see Figure 1). Subsequently, those records were
eliminated, which not meet full studied selection criteria, starting with the type of study and
participants. After accumulating 28 potentially relevant records, they were reviewed in detail to
check their methodological quality with respect to quantitative methods (Pluye et al., 2011).
Four studies were rejected. One study was excluded due to very small sample size (N = 45),
which was significantly lower compared to the sample sizes of other included studied to this
review. Three studies were rejected due to differently conceptualized PTG measurement, which
made them unsuitable for further comparisons. As a result, 24 articles were finally accepted for
systematic review. The PRISMA flow diagram illustrates the process of the articles selection
(see Figure 1).
9
[Insert Figure 1 about here]
The information from the eligible 24 articles is presented in Tables 1–5, grouped
according to the aims of our review and to the PTG conceptualisation and tool for measuring it.
In particular, Tables 1 and 2 present the relationship between PTG and sociodemographics, as
well as HIV-related clinical variables. Tables 3–5 illustrate the relationship between PTG and
psychosocial aspects of the functioning of PLWH; they include selected positive psychological
correlates (optimism, resilience, positive reappraisal coping, positive affect, self-efficacy),
HIV-related distress (depression, substance use, PTSD symptoms) and HIV-related social
issues (HIV stigma, social support). In each table, we specify the nature of the relationship
between PTG and a particular variable, where ‘+’ indicates a statistically significant positive
relationship, ‘−’ means statistically significant negative relationship and ‘0’ points to the lack
of a significant relationship. The vast majority of the analysed studies (75%) were cross-
sectional. Only six studies presented longitudinal results on PTG in this patient group.
[Insert Tables 1–5 about here]
Posttraumatic growth measures
Most of the analysed articles (17/24, i.e., 71%) were based on Tedeschi and Callhoun’s
(1996, 2004) model of PTG and as a consequence used the Posttraumatic Growth Inventory
(PTGI; Tedeschi, & Calhoun, 1996). The PTGI comprises of 21 items to assess five domains of
growth, such as Relating to Others, New Possibilities, Personal Strength, Spiritual Change and
Appreciation of Life. The sum of all items constitutes the global PTG level. Each item is
assessed on a six-point scale, with values ranging from 0 (I did not experience this change as a
result of my crisis) to 5 (I experienced this change to a very great degree as a result of my
crisis). The psychometric properties of the PTGI, including especially its validity, are a subject
of a long debate in the literature (e.g. Frazier et al., 2009; Jayawickreme, & Blackie, 2014),
which topic will be also discussed further in this review.
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Five articles (21%) assessed the benefit finding (BF) and used the Benefit-Finding
Scale (BFS; Antoni et al., 2001). This tool consists of 17 items to measure perceived benefits
across a variety of domains, arising from experience of particular disease: its diagnosis and
treatment. Responses are provided on the scale ranging from not at all (1) to extremely (5). The
psychometric properties of this tool were discussed in some meta-analytic reviews (Helgeson et
al., 2006).
Two articles (8%) assessed benefit finding or stress-related growth measured with the
Psychological Thriving Scale (PTS). This 24-item questionnaire was developed by Abraido-
Lanza et al. (1998) and it is a combination of items derived from the Stress-Related Growth
Scale (Park et al., 1996) and PTGI (Tedeschi, &Calhoun, 1996). Participants are asked to
assess the degree to which they experienced each benefit as a result of their illness using a five-
point response scale ranging from 0 (this has not happened to me) to 4 (a great deal). Like in
BFS, the psychometric properties of this tool were discussed in some meta-analytic reviews
(Helgeson et al., 2006).
Posttraumatic growth and sociodemographic variables
All 24 reviewed articles provided the sociodemographic characteristics of the sample,
with information about participants’ gender, age and socioeconomic status. However, only
seven studies included participants’ gender in the main statistical analysis (see Table 1). In five
studies (5/7; 71%), HIV-infected women reported higher PTG compared to HIV-infected men,
whereas in two studies, no statistically significant gender differences were noted. The
participants’ age was analysed in 11 articles, and 10 of them (91%) showed no age differences
in PTG among PLWH. Only one study reported a positive association between PTG and age.
Three studies out of four (75%) affirmed no relationship between the level of education and
PTG, and two studies out of four (50%) showed no link between employment status and PTG
level. Four studies out of six reviewed in the context of ethnicity and PTG (66%) suggested
higher PTG among African American participants compared to White participants, whereas one
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study reported higher PTG among Hispanic participants compared to White and African
American participants. One study did not show a direct effect of ethnicity, but revealed its
moderation effect on relationship between PTG and negative affectivity measures (depression,
negative affect and anxiety): it was significantly negative only for White comparing with
African American PLWH.
Posttraumatic growth and HIV-related clinical variables
As in the case of sociodemographic variables, only 13 articles incorporated HIV-related
clinical variables into the statistical analysis. The HIV-related clinical variables were relatively
weakly associated with PTG (see Table 2). In three out of five studies (60%) there was no
relationship between CD4 count and PTG. One study demonstrated a positive relationship
between these variables, but only among Hispanic patients and those with low levels of
optimism. An association between PTG and viral load was examined in three studies: in one
study a null relationship was obtained, while two others documented a complex connection
between them. With respect to time since HIV diagnosis, 12 studies, which are 50% of all
identified studies, indicated lack of a statistically significant relationship between these
variables. Six studies out of eight documented (75%) no relationship between years of ART
treatment and/or treatment adherence and PTG, while two other studies observed a positive
link between these variables. Finally, three articles out of five (60%) did not find a difference
in PTG between HIV+ and HIV/AIDS patients. Conversely, Littlewood et al. (2008) observed
higher PTG among HIV/AIDS patients, while Rzeszutek (2017) found that PTG was higher
only among HIV+ participants, compared to HIV/AIDS patients.
Posttraumatic growth and positive psychological correlates
All together fourteen articles investigating this issue were identified (see Table 3). Two
studies explored the link between optimism and PTG. Milam (2004) observed a positive
relationship between optimism and PTG only in the cross-sectional part of his study – over
time this relationship was insignificant. However, in a second study, Milam (2006) found a
12
positive longitudinal association between these variables, using the same assessment tools and
with a very similar sample size. 60% (3/5) of the cross-sectional studies showed a positive
association between resilience as a personality trats and PTG among PLWH. On the contrary,
two longitudinal studies demonstrated no (Garrido-Hernansaiz, & Alonso-Tapia, 2017) or even
a negative association between these two constructs (Garrido-Hernansaiz et al., 2017). Four
studies out of five (80%) indicated a positive correlation between coping through positive
reappraisal and PTG, while one study found no such relationship. In three studies (3/3; 100%)
a positive association between positive affect and PTG was found. Finally, in all two analysed
studies, a positive relationship between self-efficacy and PTG among PLWH was observed.
Posttraumatic growth and HIV-related distress
Thirteen studies examined the relationship between PTG and HIV-related distress.
Among them, 12 noted a significant association between various aspects of HIV-related
distress and PTG (see Table 4). Seven studies out of nine (78%) showed the negative
relationship between depression and PTG, while two studies found no such relationship. Two
studies out of three (66%) provided evidence for the negative link between substance use and
PTG, while one study found no such relationship. Interesting results were found for PTSD
symptoms and PTG. Namely, two studies out of four analysed (50%) reported a positive
association between these variables. One study found no relationship between PTSD symptoms
and PTG, while another observed the negative link between these constructs, however, only
among HIV-infected women.
Posttraumatic growth and HIV-related social issues
A negative relationship between HIV-related stigma and PTG was shown in three cross-
sectional studies (75%), whereas one longitudinal study showed the opposite effect (see Table
5). All six studies reviewed in this context documented a positive relationship between social
support and PTG among PLWH, i.e. social support promoted positive changes in this patient
group.
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Discussion
The main aim of this systematic review was to investigate PTG among PLWH in
relation to the socio-medical and psychological correlates among this group of patients.
Starting with an assessment of the consistency of the gathered empirical data, it can be noted
that the vast majority of studies (71%) were based on Tedeschi and Calhoun’s (1996, 2004)
model of PTG and its assessment tool (PTGI). Only seven studies were based on other PTG-
related constructs, such as benefit finding or stress-related growth, but still used tools that can
be regarded as comparable to PTGI, at least as far as a unitary PTG score is considered.
Consistency between the theoretical and measurement models of PTG was an important
selection criterion for two reasons. First, it minimises the interpretation bias resulting from
treating substantially different data as comparable. Second, it allows for a more in-depth
understanding of PTG, both universally and specifically in this group of patients.
When it comes to the sociodemographic correlates of PTG among PLWH, it seems that
in light of prior research, only two play some role – namely, gender and ethnicity. The higher
PTG among HIV-infected women compared to HIV-infected men is consistent with literature
on gender differences in PTG (Vishnevsky et al., 2010). However, in all the identified studies
(see Table 1), a significant underrepresentation of women has been observed, from two to even
six times less than men (e.g. Cieślak et al., 2009; Kamen et al., 2016; Milam, 2004; Zeligman
et al., 2017). Thus, although this ratio is rather typical for studies on PLWH population (Bor et
al., 2015), one should be careful about drawing a strong conclusion with regard to gender
differences in PTG, and future studies ought to be based on a more gender-balanced ratio of
participants. In addition, Hispanic and especially African American ethnicity was positively
related to PTG among PLWH. On one hand, this may indicate a need to examine cross-cultural
factors – a topic grossly neglected in the PTG literature (Pals, & McAdams, 2004). On the
other hand, this may lead some authors to formulate possible explanatory mechanisms, which
would require further studies. Namely, the minority stress theory suggesting that people from
14
minority populations may be exposed to increase and more frequent stress resulting in
negative health consequences, but this may also provide chances for growth (Fekete et al.,
2016). The HIV-infected African Americans still face substantial economic and social
disparities and this greater adversity may stimulate more PTG (Pellowski et al., 2013).
The HIV-related clinical variables were relatively poorly associated with PTG among
PLWH (Table 2). If some medical parameters (e.g. CD4, viral load) describing HIV infection
progression may at all be related to psychological growth, this relationship would depend on
other variables, such as ethnicity or personality (Milam, 2004, 2006). Only three studies out of
nine showed the positive role of treatment duration or adherence in PTG (Milam, 2006;
Łuszczyńska et al., 2007, 2012). This resonates with the inconclusive results regarding PTG
following a struggle with life-threatening illness, which suggested no (Widows et al., 2005),
positive (Rahman et al. 2012) or negative (Mols et al., 2009) relationship between PTG and
these particular variables. Out of all HIV-clinical variables, there was a rather consistent picture
with regard to the lack of relationship between time since HIV diagnosis and PTG among
participants. There is no consensus in the general PTG literature on the time required for
growth to appear after trauma (Linley & Joseph, 2004), which is especially visible in research
on PTG in the case of health-related trauma: studies reported a positive (Sears et al., 2003),
negative (Guns et al. 2016) or no relationship (Bellizzi, & Blank, 2006) between time elapsed
since illness diagnosis and PTG. Tedeschi and Calhoun (1996, 2006) underlined that PTG is
not a static outcome but an ongoing, complex process, rather unlikely to develop shortly after a
traumatic event, which may somehow explain the inconclusive findings concerning the role of
time in the development of PTG. Łuszczyńska et al. (2012) clarified that PTG shortly after the
diagnosis of a potentially terminal illness may act as a palliative response to a life threat, and
only in the long term may be associated with more profound positive life changes. More
specifically, some studies observed the stability of these positive changes among cancer
patients, i.e. growth measured soon after diagnosis was still related to lower distress and
15
depression eight years later after controlling for the patient’s baseline assessment (Carver, &
Antoni, 2004). It is also important to mention again the uniqueness of illness-related trauma
(Edmondson, 2014), which often constitutes a complex process which challenges different
aspects of a patient’s life at different stages of the disease. This creates the problem of defining
the critical point which may trigger growth development (Barskova & Oesterreich, 2009). For
example, in this review, Littlewood et al. (2008) observed higher PTG among AIDS patients,
whereas Rzeszutek (2017) found higher PTG among HIV+ patients only, and three other
studies noted no differences between HIV+ and HIV/AIDS patients. Nevertheless, the
aforementioned inconclusive results can also be explained by the fact that PTGI was developed
as an operationalisation of positive changes after vast categories of traumatic events and,
therefore, may not sufficiently capture the above-mentioned distinctiveness of health-related
trauma (Casellas-Grau et al., 2017). In addition, PTG as operationalised by Tedeschi and
Calhoun (1996, 2004) refers also to the qualitative positive changes observed among trauma
survivors, but is measured only by purely quantitative inventory (Frazier et al., 2009).
More homogeneous findings were obtained with respect to the association between
psychological correlates and PTG among PLWH. The majority of reviewed studies found a
negative association between PTG and depression or substance use among PLWH. An
analogous trend was observed in other trauma survivors (Bensimon, 2012; Helgeson et al.,
2006; Prati & Pietrantoni, 2009). This may suggest that psychological factors outweighed the
role of clinical variables as PTG correlates not only among PLWH, but also in other patient
groups. However, such an assumption should be considered as premature. Casellas-Grau et al.
(2017) observed in a systematic review on PTG among cancer patients that PTG still lies
mainly in the interest of psychologists, and is neglected by medical journals, which was also
visible in our review. Perhaps a more complex assessment of objective health status may shed
more light on the role of psychological versus clinical factors related to PTG among various
somatically ill patients.
16
Similarly, most studies showed that PTG was inversely related to perceived HIV-related
stigma and positively associated with social support. This latter variable was determined to be
one of the most important PTG correlates among various populations after trauma (Prati, &
Pietrantoni, 2009). Less agreement was reached with regard to the relationship between HIV-
related PTSD symptoms and PTG, where two studies showed the positive (Cieślak et al., 2009;
Nightingale et al., 2011), one negative (Rzeszutek et al., 2016) and another one the lack of a
direct association between these variables (Rzeszutek et al., 2017a). This corresponds to
inconclusive findings in the literature on the link between PTG and PTSD among various
trauma survivors (Tedeschi, & Calhoun, 2004). The latest meta-analytic review showed
curvilinear association between PTSD symptoms and PTG (Shakespeare-Finch & Lurie-Beck,
2014), which highlights the need for more longitudinal studies on PTG in cases of life-
threatening illness.
Limitations and future research directions
This systematic review is not free of limitations, which should be mentioned along with
some recommendations for future research on PTG among PLWH. First, although we adopted
clear study selection criteria, some bias was possible. More specifically, concentrating only on
quantitative results may hinder the possibility of obtaining a more comprehensive picture of
PTG in this patient group. Perhaps future studies could combine quantitative and qualitative
literature, especially as this latter type of research is also part of HIV/AIDS literature (e.g.
Siegel et al., 2000). Second, the reviewed literature was very heterogeneous with regard to
potential PTG issues, such as different statistical control of HIV-related clinical variables (see
e.g. various amounts of time from HIV diagnosis), as well as insufficient clarification of the
growth-inducing event (HIV diagnosis, AIDS phase, ongoing struggle with disease/stigma,
etc.). This suggests a necessity for a sharper focus on a homogeneous sample of PLWH with
respect to clinical data and perceived trauma relating to PTG. Furthermore, all reviewed studies
were based on retrospective, self-reported PTG measures only. It is vital to conduct interviews
17
with family and friends about the real changes in participants’ functioning, so as to avoid the
typical bias in retrospective PTG assessments representing, at least to a certain degree, positive
illusions of trauma survivors (Frazier et al., 2009). In addition, 75% of the studies were cross-
sectional, reflecting the fundamental problem of PTG research and precluding estimation of
valid size effects as they should describe the contribution of variables under study to the
process of change as defined by PTG (Anusic, & Yap, 2014). At present, it is unclear whether
these effects would indeed relate to this contribution or would rather relate to operational and
procedural confounders (see for instance a possibility of gender invariance; Jane et al., 2007).
It can only be concluded that these variables are related to the PTG assessment and as such
should be included and controlled in the future research. Therefore, longitudinal studies are
critical for examining PTG mechanisms, including both its mediators and moderators and
testing also other than just linear relationships. Additionally, it is important to elaborate on to
what extent PTG is a distinct theoretical construct and to what extent it shares variance with
similar psychological concepts (e.g. well-being, personality; Jayawickreme & Blackie, 2014).
Furthermore, further research will translate into higher quality of studies that may indeed be
interpreted in terms of substantially valid size effects. Finally, this systematic review was based
on a small number of studies (N = 24), many of them are likely not to have sufficient statistical
power to detect small effects and most did not control for important confounding variables
when analysed psychological correlates of PTG. This suggests that research on PTG among
PLWH is still in its infancy. Therefore, further research is needed on this phenomenon in this
patient group to differentiate between universal and HIV-specific correlates of PTG as well as
to elaborate on PTG as a construct distinct from others describing a spectrum of well-being.
Conclusion
18
The examined studies, although still very few in number, suggest that the self -reported
PTG among PLWH may be related more to psychological variables, rather than to
characteristics of HIV infection itself. Nevertheless, several aspects of the research on PTG
among PLWH require modification, both theoretically and methodologically. In addition, more
comprehensive interdisciplinary studies are needed to fully capture the health-related PTG
mechanisms and outcomes in this patient group.
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Figure 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)
flow diagram (from: Moher, Liberati, Tezlaff, & Altman, 2009).
31
Identifcation
Screening
Eligibility
Included
Records identied through
database searching
(n=2567)
(
Records screened
(n=1281)
Full-text articles assessed
for eligibility
(n=902)
Total full-text articles
excluded
(n=878):
Systematic reviews,
metanalyses, qualitative
studies, editorials or
letters
(n=436)
Caregivers or other
family members as
participants
(n=438)
Unclear PTG
measurement, small
sample size
Records excluded
following
title and abstract
screening
Records after duplicates
removed (n=1281)
Studies included in review
(n=24)
Additional records identied
through other sources
(n=30)
(
Table 1. The relationship between PTG and sociodemographic variables.
Study Study design Sample size Analysed variable PTG construct and
measurement
Relationship between
PTG and analysed
variable
Gender
Milam (2004) Longitudinal T1: 835
T2: 434
Male (M) = 727
Female (F) = 108
PTG-Posttraumatic
Growth Inventory
(PTGI)
T1: + (F > M)
T2: 0
Milam (2006) Longitudinal T1: 886
T2: 412
Male = 363
Female = 49 PTG-PTGI + (F > M)
Littlewood et al. (2008) Cross-sectional 221 Male = 123
Female = 98
Benefit finding - Benefit
Finding Scale (BFS) +F > M
Cieślak et al. (2009) Cross-sectional 90
Male = 57
Female = 30 (3
participants did not
provide information about
their gender)
PTG-PTGI 0
Kamen et al. (2016) Cross-sectional 334 Male = 247
Female = 87 PTG-PTGI +F > M
Rzeszutek et al. (2016) Cross-sectional 250 Male = 206
Female = 44 PTG-PTGI +F > M
Ogińska-Bulik & Kraska
(2017) Cross-sectional 64 Male = 39
Female = 25 PTG-PTGI 0
Age
Milam (2004) Longitudinal T1: 835
T2: 434 M = 38.4; SD = 7.8 PTG-PTGI T1: –
T2: 0
Łuszczyńska et al. (2007) Cross-sectional 104 M = 34.7; SD = 8.9 Benefit finding - BFS +
Littlewood et al. (2008) Cross-sectional 221 M = 40.0; Range = 22-59 Benefit finding - BFS 0
Cieślak et al. (2009) Cross-sectional 90 M = 41.6; SD = 9.5 PTG-PTGI 0
Łuszczyńska et al. (2012) Cross-sectional 80 M = 39.4; SD = 7.9 PTG-PTGI and
Benefit finding - BFS 0
Rzeszutek et al. (2016) Cross-sectional 250 M = 39.4; SD = 11.2 PTG-PTGI 0
32
Rzeszutek et al. (2017a) Longitudinal T1: 110
T2: 73 T2: M = 38.8; SD = 12.6 PTG-PTGI 0
Rzeszutek et al. (2017b) Cross-sectional 470 M = 40.0; SD = 10.7 PTG-PTGI 0
Rzeszutek (2017) Longitudinal
T1: 129
T2: 106
T3: 82
T3: M = 40.5; SD = 11.5 PTG-PTGI 0
Ogińska-Bulik & Kraska
(2017) Cross-sectional 64 M = 38.2; SD = 9.1 PTG-PTGI 0
Garrido-Hernansaiz &
Alonso-Tapia (2017) Longitudinal T1: 145
T2: 119 T2: M = 32.7; SD = 8.3 PTG-PTGI 0
Socioeconomic status
Siegel & Shrimshaw
(2007) Cross-sectional 138 Education
(8% higher education) Benefit finding - PTS 0
Littlewood et al. (2008) Cross-sectional 221
Education
(27% higher education)
Employment status
(33% employed)
Benefit finding - BFS 0
Kamen et al. (2016) Cross-sectional 334 Employment status
(14.4% employed) PTG-PTGI 0
Garrido-Hernansaiz &
Alonso-Tapia (2017) Longitudinal T1:145
T2: 119
Education
(54.6% higher
education).
PTG-PTGI 0
Ethnicity
Milam (2004) Longitudinal T1: 835
T2: 434
African American (AA)
(17%) and Hispanic (H)
(36.8%) vs. White (W)
(39.5%)
PTG-PTGI T1: + AA and H > W)
T2: 0
Siegel et al. (2005) Cross-sectional 138 African American (38%)
vs White (28%)
Stress-related growth -
PTS + AA > W
Milam (2006) Longitudinal T1:886
T2: 412
Hispanic (40.3%) vs.
White (38.8%) and
African American
(14.8%)
PTG-PTGI + H > AA and W
33
Littlewood et al. (2008) Cross-sectional 221 African American (42%)
vs White (46%) Benefit finding-BFS + AA > W
Fekete et al. (2016) Cross-sectional 167 African American (47%)
vs White (53%) PTG-BFS
0
but interaction PTG x
psychological
adjustment: + for W
only
Kamen et al. (2016) Cross-sectional 334
African American
(32.6%), Hispanic
(38.6%) vs White (5.7%)
PTG-PTGI + AA and H > W
Note: T1, 2 or 3 – consecutive assessments in longitudinal studies; ‘+’ indicates a statistically significant positive relationship, ‘−’ indicates a
significant negative relationship, ‘0’ indicates a statistically insignificant relationship; M-male, F-female; AA- African-American, H – Hispanic,
W-White.
34
Table 2. The relationship between PTG and HIV-related clinical variables.
Study Study design Sample size Analysed variable PTG construct and
measurement
Relationship between
PTG and analysed
variable
CD4 count
Milam (2004) Longitudinal
T1: 835
T2: 434 M = 407.55; SD = 273.16 PTG-PTGI 0
Milam (2006) Longitudinal
T1: 886
T2: 412
T1: M = 434.6; SD =
260.2
T2: M = 472.8; SD =
272.4)
PTG-PTGI
+, but only among
Hispanic patients and
those with low optimism
Littlewood et al. (2008) Cross-sectional 221 M = 500.00 (no SD
provided) Benefit finding-BFS 0
Rzeszutek et al. (2017b) Cross-sectional 470 M = 593.12; SD = 228.63 PTG-PTGI 0
Rzeszutek (2017) Longitudinal
T1: 129
T2: 10
T3: 82
T3: M = 645.73; SD =
256.23 PTG-PTGI 0
Viral load
Milam (2004) Longitudinal
T1: 835
T2: 434 M = 60,520.47; SD
=247,808.61 PTG-PTGI T1: -, T2: 0
Milam (2006) Longitudinal T1: 886
T2: 412
T1: log M = 5.1; SD =
4.0
T2: log M = 4.3; SD =
4.0
PTG-PTGI
-, but only for
participants with low
pessimism
Littlewood et al. (2008) Cross-sectional 221 37% participants had an
undetectable viral load Benefit finding-BFS 0
35
Time since HIV diagnosis
Milam (2004) Longitudinal
T1: 835
T2: 434 T2: M = 6.39; SD = 4.24 PTG-PTGI 0
Siegel et al. (2005) Cross-sectional 138 M = 7.30; SD = 4.00 Stress-related growth-
PTS 0
Milam (2006) Longitudinal
T1: 886
T2: 412 T2: M = 6.40; SD = 4.20 PTG-PTGI 0
Littlewood et al. (2008) Cross-sectional 221 M = 7.00 (no data on SD
was provided) Benefit finding-BFS 0
Nightingale et al. (2011) Cross-sectional 114 M = 10.90; SD = 5.70 PTG-PTGI 0
Łuszczyńska et al. (2012) Cross-sectional 80 M = 10.48; SD = 6.14 PTG-PTGI and Benefit
finding-BFS 0
Murphy et al. (2013) Cross-sectional 74 M = 7.89; SD = 6.70 PTG-PTGI 0
Rzeszutek et al. (2016) Cross-sectional 250 M= 7.29; SD = 6.88 PTG-PTGI 0
Rzeszutek et al. (2017a) Longitudinal
T1: 110
T2: 73 T2: M= 6.42; SD = 6.63). PTG-PTGI 0
Rzeszutek et al. (2017b) Cross-sectional 470 M = 7.90; SD = 6.99 PTG-PTGI 0
Rzeszutek (2017) Longitudinal
T1: 129
T2: 106
T3: 82 T3: M = 7.39; SD = 5.72 PTG-PTGI 0
Garrido-Hernansaiz &
Alonso-Tapia (2017) Longitudinal
T1: 145
T2: 119 T2 = 38.78 days after
diagnosis; SD = 8.25) PTG-PTGI 0
36
Years of treatment/adherence
Milam (2004) Longitudinal
T1: 835
T2: 434 79.5% participants was
on ART PTG-PTGI 0
Milam (2006) Longitudinal
T1: 886
T2: 412 75.7% participants was
on ART PTG-PTGI 0
Łuszczyńska et al. (2007) Cross-sectional 104 100% of participants was
on ART Benefit finding-BFS +
Littlewood et al. (2008) Cross-sectional 221 78% participants was on
ART Benefit finding-BFS 0
Łuszczyńska et al. (2012) Cross-sectional 80 M = 9.78; SD = 3.56 PTG-PTGI and Benefit
finding-BFS +
Rzeszutek et al. (2017b) Cross-sectional 470 M = 6.11; SD = 5.65 PTG-PTGI 0
Rzeszutek (2017) Longitudinal
T1: 129
T2: 106
T3: 82 T3: M = 5.76; SD = 4.88 PTG-PTGI 0
Garrido-Hernansaiz &
Alonso-Tapia (2017) L Longitudinal
T1: 145
T2: 119 T2: 71% participants was
on ART PTG-PTGI 0
HIV/AIDS status
Milam (2004) Longitudinal
T1: 835
T2: 434
46.4% of the initial
sample of participants
were in AIDS phase
PTG-PTGI 0
Siegel et al. (2005) Cross-sectional 138 51% of participants were
diagnosed with AIDS
Stress-related growth-
PTS 0
Littlewood et al. (2008) Cross-sectional 221 39% of participants were
diagnosed with AIDS Benefit finding-BFS AIDS > HIV+
Rzeszutek et al. (2017b) Cross-sectional 470 16% of participants were
diagnosed with AIDS PTG-PTGI 0
Rzeszutek (2017) Longitudinal T1: 129 20% of the final sample PTG-PTGI HIV+ > AIDS
37
T2: 106
T3: 82 of participants were
diagnosed with AIDS
Note: T1, 2 or 3 – consecutive assessments in longitudinal studies; ‘+’ indicates a statistically significant positive relationship, ‘−’ indicates a
significant negative relationship, ‘0’ indicates a statistically insignificant relationship. AIDS: patients diagnosed with AIDS; HIV+: patients
diagnosed with HIV, but not in AIDS phase.
38
Table 3. The relationship between PTG and positive psychological correlates.
Study Study design Sample
size Analysed variable PTG construct and
measurement
Statistically controlled
sociodemographic and
HIV-related clinical
variables
Relationship
between PTG
and analysed
variable
Milam (2004) Longitudinal T1: 835
T2: 434 Optimism PTG-PTGI
Gender, age,
socioeconomic status,
ethnicity, CD4 count, viral
load, time since HIV
diagnosis, treatment
T1: +
T2:0
Milam (2006) Longitudinal T1: 886
T2: 412 Optimism PTG-PTGI
Ethnicity, CD4 count,
viral load, time since HIV
diagnosis, treatment
+
Murphy et al. (2013) Cross-sectional 74 Resilience PTG-PTGI - +
Xiaonan et al. (2017) Cross-sectional 141 Resilience PTG-PTGI - +
Rzeszutek et al. (2017a) Longitudinal T1: 110
T2: 73 Resilience PTG-PTGI Age, time since HIV
diagnosis +
Garrido-Hernansaiz &
Alonso-Tapia (2017) Longitudinal T1: 145
T2: 119 Resilience PTG-PTGI -0
Garrido-Hernansaiz et al.
2017 Longitudinal T1: 144
T2: 87 Resilience PTG-PTGI --
Siegel et al. (2005) Cross-sectional 138 Positive
reappraisal coping
Stress-related growth-
PTS
Ethnicity, socioeconomic
status +
Carrico et al. (2006) Cross-sectional 264 Positive
reappraisal coping Benefit finding-BFS 24-h cortisol output +
Rzeszutek et al. (2017a) Longitudinal T1: 110
T2: 73
Positive
reappraisal coping PTG-PTGI Age, time since HIV
diagnosis 0
Ye et al. (2017a) Cross-sectional 60 Positive
reappraisal coping PTG-PTGI -+
Garrido-Hernansaiz et al.
2017 Longitudinal T1: 144
T2: 87
Positive
reappraisal coping PTG-PTGI -+
Siegel et al. (2005) Cross-sectional 138 Positive affect Stress-related growth- Ethnicity, socioeconomic +
39
PTS status
Siegel & Shrimshaw
(2007) Cross-sectional 138 Positive affect Benefit finding-PTS Ethnicity, socioeconomic
status +
Rzeszutek (2017) Longitudinal
T1: 129
T2: 106
T3: 82
Positive affect PTG-PTGI
Gender, age, education,
employment, relationship
status, CD4 count, time
since HIV diagnosis,
HIV/AIDS status,
treatment
+
Łuszczyńska et al. (2007) Cross-sectional 104 Self-efficacy Benefit finding-BFS Adherence, physical
functioning +
Cieślak et al. (2009) Cross-sectional 90 Self-efficacy PTG-PTGI Gender, age +
Note: T1, 2 or 3 – consecutive assessments in longitudinal studies; ‘+’ indicates a statistically significant positive relationship, ‘−’ indicates a
significant negative relationship, ‘0’ indicates a statistically insignificant relationship.
40
Table 4. The relationship between PTG and HIV-related distress.
Study Study design Sample
size Analysed variable PTG construct and
measurement
Statistically controlled
sociodemographic and
HIV-related clinical
variables
Relationship
between PTG
and analysed
variable
Milam (2004) Longitudinal T1: 835;
T2: 434 Depression PTG-PTGI
Gender, age,
socioeconomic status,
ethnicity, CD4 count, viral
load, time since HIV
diagnosis, treatment
-
Siegel et al. (2005) Cross-sectional 138 Depression Stress-related growth-
PTS
Ethnicity, socioeconomic
status -
Milam (2006) Longitudinal T1: 886
T2: 412 Depression PTG-PTGI
Ethnicity, CD4 count,
viral load, time since HIV
diagnosis, treatment
-
Carrico et al. (2006) Cross-sectional 264 Depression Benefit finding-BFS 24-h cortisol output -
Siegel & Shrimshaw
(2007) Cross-sectional 138 Depression Benefit finding-PTS Ethnicity, socioeconomic
status -
Littlewood et al. (2008) Cross-sectional 221 Depression Benefit finding: BFS
Gender, ethnicity,
HIV/AIDS status,
adherence
-
Łuszczyńska et al. (2012) Cross-sectional 80 Depression PTG-PTGI and Benefit
finding- BFS
Gender, age, education,
treatment, time since HIV
diagnosis
0
Garrido-Hernansaiz &
Alonso-Tapia (2017) Longitudinal T1: 145
T2: 119 Depression PTG-PTGI -0
Chang et al. (2018) Cross-sectional 221 Depression PTG-PTGI --
Milam (2004) Longitudinal T1: 835
T2: 434
Substance use PTG-PTGI Gender, age,
socioeconomic status,
ethnicity, CD4 count, viral
load, time since HIV
T1: -, T2: 0
41
diagnosis, treatment
Milam (2006) Longitudinal T1: 886
T2: 412 Substance use PTG-PTGI
Ethnicity, CD4 count,
viral load, time since HIV
diagnosis, treatment
-
Littlewood et al. (2008) Cross-sectional 221 Substance use Benefit finding-BFS
Gender, ethnicity,
HIV/AIDS status,
adherence
0
Cieślak et al. (2009) Cross-sectional 90 PTSD symptoms PTG-PTGI Gender, age +
Nightingale et al. (2011) Cross-sectional 114 PTSD symptoms PTG-PTGI Time since HIV diagnosis +
Rzeszutek et al. (2016) Cross-sectional 250 PTSD symptoms PTG-PTGI
Gender, age, time since
HIV diagnosis
- but only
among HIV+
women
Rzeszutek et al. (2017a) Longitudinal T1: 110
T2: 73 PTSD symptoms PTG-PTGI Age, time since HIV
diagnosis 0
Note: T1, 2 or 3 – consecutive assessments in longitudinal studies; ‘+’ indicates a statistically significant positive relationship, ‘−’ indicates a
significant negative relationship, ‘0’ indicates a statistically insignificant relationship.
42
Table 5. The relationship between PTG and HIV-related social issues.
Study Study design Sample
size Analysed variable PTG construct and
measurement
Statistically controlled
sociodemographic and
HIV-related clinical
variables
Relationship
between PTG
and analysed
variable
Murphy et al. (2013) Cross-sectional 74 HIV stigma PTG-PTGI --
Zeligman et al. (2016) Cross-sectional 126 HIV stigma PTG-PTGI --
Kamen et al. (2016) Cross-sectional 334 HIV stigma PTG-PTGI Gender, ethnicity -
Garrido-Hernansaiz et al.
2017 Longitudinal T1: 144
T2: 87 HIV stigma PTG-PTGI -+
Łuszczyńska et al. (2007) Cross-sectional 104 Social support Benefit finding- BFS Adherence, physical
functioning +
Cieślak et al. (2009) Cross-sectional 90 Social support PTG-PTGI Gender, age +
Zeligman et al. (2016) Cross-sectional 126 Social support PTG-PTGI -+
Kamen et al. (2016) Cross-sectional 334 Social support PTG-PTGI Gender, ethnicity +
Rzeszutek et al. (2017a) Longitudinal T1: 110
T2: 73 Social support PTG-PTGI Age, time since HIV
diagnosis +
Rzeszutek (2017) Longitudinal
T1: 129
T2: 106
T3: 82
Social support PTG-PTGI
Gender, age, education,
employment, relationship
status, CD4 count, time
since HIV diagnosis,
HIV/AIDS status,
treatment
+
Note: T1, 2 or 3 – consecutive assessments in longitudinal studies; ‘+’ indicates a statistically significant positive relationship, ‘−’ indicates a
significant negative relationship, ‘0’ indicates a statistically insignificant relationship.
43
Appendix:
Preferred Reporting Items for Systematic Reviews (PRISMA checklists). From: Moher D,
Liberati A, Tetzlaff J, Altman DG, The PRISMA Group (2009). Preferred Reporting Items for
Systematic Reviewsand Meta-Analyses: The PRISMA Statement. PLoS Med 6(7): e1000097.
doi:10.1371/journal.pmed1000097
Section/topic # Checklist item Reported
on page
#
TITLE
Title 1 Identify the report as a systematic
review, meta-analysis, or both.
1
ABSTRACT
Structured
summary
2 Provide a structured summary
including, as applicable: background;
objectives; data sources; study
eligibility criteria, participants, and
interventions; study appraisal and
synthesis methods; results;
limitations; conclusions and
implications of key findings;
systematic review registration
number.
1
INTRODUCTION
Rationale 3 Describe the rationale for the review
in the context of what is already
known.
2-4
Objectives 4 Provide an explicit statement of
questions being addressed with
reference to participants,
interventions, comparisons,
outcomes, and study design
(PICOS).
5
METHODS
Protocol and
registration
5 Indicate if a review protocol exists, if
and where it can be accessed (e.g.,
Web address), and, if available,
provide registration information
including registration number.
N/A
Eligibility
criteria
6 Specify study characteristics (e.g.,
PICOS, length of follow-up) and
report characteristics (e.g., years
considered, language, publication
status) used as criteria for eligibility,
giving rationale
6-7 and Figure 1
Information
sources
7 Describe all information sources
(e.g., databases with dates of
coverage, contact with study authors
to identify additional studies) in the
search and date last searched
6-7 and Figure 1
Search 8 Present full electronic search strategy 6-7 and Figure 1
44
for at least one database, including
any limits used, such that it could be
repeated.
Study selection 9 State the process for selecting studies
(i.e., screening, eligibility, included
in systematic review, and, if
applicable, included in the meta-
analysis).
6-7 and Figure 1
Data collection
process
10 Describe method of data extraction
from reports (e.g., piloted forms,
independently, in duplicate) and any
processes for obtaining and
confirming data from investigators.
6-7 and Figure 1
Data items 11 List and define all variables for
which data were sought (e.g.,
PICOS, funding sources) and any
assumptions and simplifications
made.
6-7 and Figure 1
Risk of bias in
individual
studies
12 Describe methods used for assessing
risk of bias of individual
studies (including specification of
whether this was done at the study or
outcome level), and how this
information is to be used in any data
synthesis.
6-7 and Figure 1
Summary
measures
13 Describe the methods of handling
data and combining results of
studies, if done, including measures
of consistency (e.g., I2) for each
meta-analysis.
N/A
Synthesis of
results
14 Describe the methods of handling
data and combining results of
studies, if done, including measures
of consistency (e.g., I2
) for each meta-analysis.
N/A
Risk of bias
across studies
15 Specify any assessment of risk of
bias that may affect the cumulative
evidence (e.g., publication bias,
selective reporting within studies).
6-7 and Figure 1
Additional
analyses
16 Describe methods of additional
analyses (e.g., sensitivity or
subgroup analyses, meta-regression),
if done, indicating which were pre-
specified.
N/A
RESULTS
Study selection 17 Give numbers of studies screened,
assessed for eligibility, and
included in the review, with reasons
for exclusions at each stage, ideally
with a flow diagram.
6-10, Figure 1
45
Study
characteristics
18 For each study, present
characteristics for which data were
extracted (e.g., study size, PICOS,
follow-up period) and provide the
citations.
6-10, Figure 1
Risk of bias
within studies
19 Present data on risk of bias of each
study and, if available, any
outcome level assessment (see item
12).
N/A
Results of
individual
studies
20 For all outcomes considered
(benefits or harms), present, for each
study: (a) simple summary data for
each intervention group (b) effect
estimates and confidence intervals,
ideally with a forest plot.
Tables 1-5
Synthesis of
results
21 Present results of each meta-analysis
done, including confidence intervals
and measures of consistency
N/A
Risk of bias
across studies
22 Present results of any assessment of
risk of bias across studies (see Item
15).
N/A
Additional
analysis
23 Give results of additional analyses, if
done (e.g., sensitivity or
subgroup analyses, meta-regression
[see Item 16]).
N/A
DISCUSSION
Summary of
evidence
24 Summarize the main findings
including the strength of evidence
for each main outcome; consider
their relevance to key groups (e.g.,
healthcare providers, users, and
policy makers).
11-14
Limitations 25 Discuss limitations at study and
outcome level (e.g., risk of bias), and
at review-level (e.g., incomplete
retrieval of identified research,
reporting bias).
14-15
Conclusions 26 Provide a general interpretation of
the results in the context of
otherevidence, and implications for
future research.
15
FUNDING
Funding 27 Describe sources of funding for the
systematic review and othersupport
(e.g., supply of data); role of funders
for the systematic
review.
N/A
46