Post-traumatic growth mediates the relationship between valences of trauma centralisation and health-related quality of life

Abstract

Emotions arising from health-related trauma can be complex (as positive and negative feelings are possible) and can influence the way patients perceive themselves and the world. Health outcomes can also be affected by the valence of emotions. We hypothesised that post-traumatic growth is the mediating link between the valences of event centrality and health-related quality of life among people living with HIV. Three hundred (male = 194 and female = 106; mean age = 35.30 years) people living with HIV in Nigeria completed measures of relevant variables. Mediation analysis was performed using path analysis and structural equation modelling. Results showed that post-traumatic growth mediated the association between positive event centrality and health-related quality of life in the physical health symptoms and treatment impact domains. Post-traumatic growth also mediated the association between negative event centrality and health-related quality of life in the physical health symptom and relationship domains. In light of these findings, it might be concluded that fostering post-traumatic growth among people living with HIV by clinicians could be helpful in enhancing the health-related quality of life of people living with HIV.

Keywords

HIV is a chronic, life-threatening, and trauma-inducing health condition associated with poor health functions (American Psychiatric Association [APA], 2013; Hays et al., 2000; Neigh et al., 2016). The chronicity of HIV is underscored by its incurable nature. One factor that makes HIV life-threatening is when it is not properly managed, which could make it degenerate into AIDS. The high level of poverty, poor health systems, and corruption in Africa have exacerbated the incidence of HIV/AIDS on the continent (Onwujekwe et al., 2020). The direct experience of a diagnosis like HIV is consistent with Criterion A (1) of the diagnostic criteria for Post-traumatic Stress Disorder (PTSD) as stipulated by the APA (2013), in the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5). Trauma is known to originate from events external to the individual (e.g., war or internal events [e.g., chronic health conditions]) (Edmondson, 2014). Most people living with life-threatening health conditions, such as HIV, experience trauma resulting from being diagnosed with the condition, which is worsened by the severity of the disease, treatment-related stress, stigma, and discrimination associated with the health condition (Rzeszutek & Gruszczyńska, 2018). Unlike the healthy population, people living with HIV (PLWH) are also known to have a history of traumatic experiences, such as child abuse and sexual assault (Keuroghlian et al., 2011). All these trauma-arousing factors negatively impact the health-related quality of life (HRQoL) of PLWH (Onu et al., 2019).

HRQoL is the extent to which a patient’s health condition and treatment affect their life functions (Schipper et al., 1996). It is an important indicator of health and treatment outcomes, often employed as a supplementary measure of morbidity and mortality (Centre for Disease and Control [CDC], 2020). HRQoL is a multidimensional concept involving physical, relationship, cognitive, and treatment impact domains (Lalanne et al., 2016). Improving HRQoL is one of the major foci of health practitioners and policymakers in the management of chronic health conditions (Perwitasari et al., 2017). Clinicians use HRQoL as an indication of disease progression, in the evaluation of health intervention programmes, and in the allocation of health management resources (Reis et al., 2012). Nevertheless, the patterns of thinking about oneself and health among PLWH are yet to be investigated.

Experiencing traumatic events usually contribute significantly to the survivor’s life story, influencing their self-definition/self-concept (Reiland & Clark, 2017). The extent to which a traumatic experience is defined as a major part of the survivor’s identity is known as event centrality (EC; Berntsen & Rubin, 2007). Trauma survivors may construe traumatic events positively or negatively, with regard to how they perceive these events to have defined their identity or their life story (Broadbridge, 2018). Hence, positive event centrality (PEC) is used in describing the construing of traumatic events as positively central to one’s identity, while negative event centrality (NEC) describes the construing of traumatic events as negatively central to one’s identity. Assessing whether a significant event in one’s life is defined in a positive or negative emotional valence is important in the management and improvement of health functions of people.

Broadbridge (2018) developed measures of NEC and PEC as two opposite constructs to enable survivors of traumatic events to indicate whether they centralise such event(s) in a negative or positive emotional valence. Differentiating among positive and negative valence improves the original neutral conception of EC, often assessed with the Centrality of Event Scale (CES; Berntsen & Rubin, 2007), which does not specify whether the event is centralised in negative or positive emotional valence. As a result, some studies (e.g., Blix et al., 2016; Boals & Schuettler, 2011; Groleau et al., 2013) that relied on CES as a measure of EC found it to be associated with increased positive and negative health outcomes and, therefore, understood EC to be an ambivalent and paradoxical concept. The development of separate measures of PEC and NEC, therefore, calls for further studies in order to understand the specific contribution of each valence to the health functions of trauma survivors (Broadbridge, 2018). To the best of our knowledge, only one study (Onu et al., 2020) has investigated the role of NEC, as a separate construct, in understanding HRQoL and found that NEC was negatively associated with all dimensions of HRQoL. However, the study did not consider the contribution of PEC in HRQoL. Other studies only considered the association between EC and HRQoL.

For example, Park et al. (2010) reported that EC was negatively associated with HRQoL among persons living with cancer. In studies involving PLWH, Onu et al. (2017, 2019) reported that EC was negatively associated with all domains of HRQoL except physical health. Earnshaw et al. (2013), however, reported that increased centralisation of HIV identity predicted a significant decrease in the physical health domain of HRQoL. HIV centrality was associated with poor wellbeing. Quinn and Chaudoir (2009) similarly reported that PLWH who centralised their self-concepts and identities around their HIV status experienced poor health and wellbeing.

It is also important to understand the pathway that explains how PEC and NEC are associated with the HRQoL of PLWH. This could be useful in the development of effective interventions that improve the HRQoL of PLWH. The centralisation of trauma associated with HIV may trigger mental processes, resulting in a perceived positive psychological change known as post-traumatic growth (PTG) (Tedeschi & Calhoum, 1996). PTG is defined as a subjective experience of positive psychological change reported by individuals who are struggling with adversarial events, trauma, or highly challenging life situations (Tedeschi & Calhoun, 2004). It involves being left in a positive psychological state as a result of one’s struggle with an adverse situation. This positive psychological state includes improved personal relationships, higher appreciation of life, increased spirituality, identification of new possibilities, and increased personal strength (Tedeschi & Calhoun, 2004). Traditionally, most studies have tended to focus more on the negative mental health in the aftermath of HIV trauma, with little attention given to the positive aspects of the traumatic experience. PTG is a very important construct in understanding how trauma survivors recover. However, PTG has received little research attention, especially with regard to PLWH (Garrido-Hernansaiz et al., 2017).

Studies exploring the association between EC and PTG are scarce. Several studies (e.g., Blix et al., 2016; Boals & Schuettler, 2011; Brooks et al., 2017; Groleau et al., 2013; Wamser-Nanney et al., 2019) have reported a significant positive association between EC and PTG among trauma survivors. However, some studies (e.g., Onu et al., 2019; Sim et al., 2015; Tanyi et al., 2014) have consistently found significant positive associations between PTG and HRQoL. Consistent predictors of outcome variables have been known to be adequate mediators (Frazier et al., 2004).

The possible mediating influence of PTG on PEC/NEC–HRQoL association can also be inferred from the organismic valuing theory of PTG (Joseph & Linley, 2005), which argues that traumatic events can trigger the survivor’s inherent tendency to evaluate and comprehend stress in a positive, meaningful way. According to this theory, when stress is so comprehended, it results in PTG, which ultimately leads to the improved wellbeing of the survivor. This can therefore be applied to this study to mean that PEC/NEC emanating from HIV may be the source of PTG development, which is then associated with the HRQoL of the client. This study is therefore designed to investigate the relationship between each valence of EC (PEC and NEC) and HRQoL and also to find out if PTG mediated the associations between them. We, therefore, hypothesised that PTG will mediate the association between PEC and HRQoL and between NEC and HRQoL (see conceptual model in Figure 1).

Figure 1.

Conceptual model – PTG as a mediator of the relationship between PEC/NEC and all domains of HRQoL.

Method

Participants

Three hundred PLWH (64.7% male and 35.3% female; mean age = 35.30 years, standard deviation [SD] = 7.14) participated in the study. They were outpatients conveniently drawn from the Federal Teaching Hospital, Abakaliki, Ebonyi State, Nigeria. All participants could read and understand the English language. They were diagnosed with HIV for at least 12 months (see Table 1 for participants’ details).

Table 1.

Descriptive statistics table.

		Frequency	Percentage
Gender	Male	194	64.7
Gender	Female	106	35.3
Marital status	Single	215	71.7
	Married	59	19.7
	Widow	4	1.3
	Widower	2	.7
	Separated	4	1.3
	Divorced	16	5.3
Educational level	Secondary education	207	69.0
Educational level	HND to PhD	93	31.0
Occupation	Public/civil servant	91	30.3
	Self-employed/business	156	51.9
	Unemployed	53	17.7
Religion	Christianity	261	87.0
	Islam	18	6.0
	Others	21	7.0
Other conditions	Comorbidity	90	30.0
Other conditions	Non-comorbidity	210	70.0
CD4 count	Below 200	94	31.3
CD4 count	Above 200	206	68.7

HND: Higher National Diploma.

Instruments

Centrality of Events Scale – positive and negative

This is a two-factor structure scale that assesses the extent to which an event is construed to be negatively or positively central to one’s identity (Broadbridge, 2018). An example of items of the positive subscale is ‘I feel that this event has become a positive part of my identity’, while an example of items of negative subscale is ‘I feel that this event has become a negative part of my identity’. To reflect the patients’ specific health conditions, we asked the participants to focus on their HIV condition as the ‘event’ being referred to in the instrument. Each item is rated on a 5-point Likert-type scale format, ranging from 1 (totally disagree) to 5 (totally agree), with higher scores in each of the valences indicating higher EC for the valence. Onu et al. (2020) reported that CES yielded a two-factor structure of acceptable fit indices (χ² = 93.26; comparative fit index (CFI) = 0.98; goodness-of-fit index (GFI) = 0.97; root mean square error of approximation (RMSEA) = .08 [0.07–0.10]). While PEC yielded an alpha reliability coefficient of .88, NEC yielded an alpha reliability coefficient of .90 in this study.

Post-traumatic Growth Inventory–Short Form

This is a10-item, 5-domain scale (i.e., two items for each domain) developed by Cann et al. (2011) to assess positive life changes resulting from traumatic experience known as PTG. The domains are: relating to others (e.g., ‘I have a greater sense of closeness with others’), new possibilities (e.g., ‘I am able to do better things with my life’), personal strength (e.g., ‘I know I can handle difficult things’), spiritual change (e.g., ‘I have a better understanding of spiritual matters’) and appreciation of life (e.g., ‘I changed my priorities about what is important in life’). All items are rated on a 5-point Likert-type scale format, ranging from 1 (very small degree) to 5 (very great degree), with higher scores indicating higher PTG. It has been reported that Post-traumatic Growth Inventory–Short Form (PTGI–SF) was primarily developed to measure the total score of PTG, given that the vast majority of studies in the literature have focused on the total score of PTG rather than the scores in each of the domains. PTG–SF has an adjusted correlation of .90 with the original 21-item PTGI (Cann et al., 2011). We found a total alpha reliability coefficient of .81 in this study.

Patient-reported outcome quality of life–HIV

This is a 38-item, 4-domain measure used to assess the HRQoL of PLWH (Lalanne et al., 2016). The four domains are: physical symptoms (PHS; e.g., ‘During the last two weeks, because I am HIV positive, I have had difficulty with strenuous physical activities’), relationship to others (REL; e.g., ‘During the last two weeks, because I am HIV positive, I have felt restricted in my relationship with my family or friends’), cognitive symptoms (COG; e.g., ‘During the last two weeks, because I am HIV positive, I have been sad’) and treatment impacts (TRT; e.g., ‘During the last two weeks, because I am HIV positive, the number of pills I take per day has bothered me’). Items are rated on a 5-point Likert-type scale format ranging from 0 (never) to 4 (always). The procedure for scoring the patient-reported outcome quality of life (PROQOL) has been described elsewhere (see Lalanne et al., 2016). The higher the score for the value in each of the domains, the better the HRQoL in that domain. The developers of the scale reported a minimum alpha reliability coefficient of .77 across all domains (Lalanne et al., 2016). We found an alpha range of .81–.92 across all domains of the PROQOL in this study.

Procedure

Each client was given a consent form to complete before participating in the study. Clients were included if they (1) were outpatients diagnosed with HIV and have been on treatment for at least 1 year, (2) were literate in English, and (3) had given their consent to participate in the study. Data collection took place between January and March 2020. PLWH attending the hospital facility were invited. On obtaining their informed consent, participants responded to the self-administered questionnaires. The questionnaires took each client about 18 min to complete. Participants’ medical records were also obtained from their medical files (as approved orally by each participant and by the research ethics committee) to ascertain their CD4 count and also verify other demographic information as reported in the questionnaires (see Table 1 for participant characteristics).

Ethical considerations

The research ethics committee of the Federal Teaching Hospital, Abakaliki, Ebonyi State approved this study (approval no. FTHA/REC/VOL2/2019/158). The purpose of the study was explained to participants. Each participant was assured of their confidentiality. They were also informed of their freedom to withdraw from the study at any point. They responded to the questionnaires in the hospital’s Waiting Hall for PLWH, where only PLWH wait to see their doctors on their clinic days. The response rate was 94.1%.

Data analysis

We adopted a cross-sectional design in this study. Bivariate correlation analysis was conducted using SPSS version 25. The mediation analysis was conducted using IBM AMOS 24.

To test our mediation hypotheses, we adopted the product of coefficients approach, which means that the mediated effect is estimated by the product of a and b, ab. Thus, the mediated effect reveals the extent to which the independent variable X is associated with the mediator (M) and the extent to which the mediator is associated with the dependent variable Y. Figure 1 shows a model of simple mediation.

An a priori power analysis was also conducted using G*Power 3.1 (Faul et al., 2009) to test the relationships among valences of centralisation of HIV trauma, PTG and HRQoL using a two-tailed test, a medium effect size (d = 0.15), and an alpha of .05. The result showed that a total of 119 participants were required to achieve a power of 0.95. Throughout the analysis, the path model was adjusted by age and CD4 count. A p-value of .05 or less was regarded as statistically significant.

Results

The bivariate correlations in Table 2 showed that age was negatively associated with PHS and REL. CD4 count had a positive association with PHS, REL, and TRT domains of HRQoL. PTG had a positive association with the PHS, REL, and TRT domains of HRQoL. PTG was negatively associated with the COG domain of HRQoL. PEC had a positive association with HRQoL across all domains, while NEC had a negative association with HRQoL across all domains.

Table 2.

Bivariate correlation matrix of demographics, post-traumatic growth, valences of centralisation of HIV trauma, and health-related quality of life.

Serial number	Variable	M	SD		1	2	3	4	5	6	7	8
1	Age	35.467	7.067	1	−0.266**	0.042	0.007	−0.001	−0.354**	−0.228**	0.115**	0.018
2	CD4 count	0.675	0.469		1	0.053	−0.057	0.094**	0.270**	0.199**	0.015	0.120**
3	PTG	32.715	5.212			1	−0.326**	0.363**	0.230**	0.088**	0.109**	−0.080*
4	NEC	21.610	5.230				1	−0.826**	−0.252**	−0.091**	−0.225**	−0.068*
5	PEC	16.972	5.368					1	0.242**	0.066*	0.155**	−0.016
6	PHS	99.689	0.164						1	0.530**	0.253**	0.173**
7	REL	99.591	0.178							1	0.616**	0.398**
8	COG	99.554	0.180								1	0.445**
9	TRT	99.655	0.131									1

SD: standard deviation; PTG: post-traumatic growth; PEC: positive event centrality; NEC: negative event centrality; PHS: physical health symptom dimension of health-related quality of life; REL: relationship dimension of health-related quality of life; COG: cognitive dimension of health-related quality of life; TRT: treatment impact dimension of health-related quality of life.

Gender dummy coded (‘0’= male and ‘1’= female).

p < .05; **p < .001.

PEC, PTG, and HRQoL

Results presented in Table 3 indicate that the total effect of PEC on PHS was significant (β_total = 0.207, standard error [SE] = 0.052, p = .001), the direct effect (PEC and PHS) was not significant (β_direct = 0.147, SE = 0.052, p = .354), and the indirect effect (IE) was significant, indicating a mediation effect. PTG mediated the relationship between PEC and PHS (IE = 0.60, 95% confidence interval [CI] = lower limit [LL] = 0.024 to upper limit [UL] = 0.111).

Table 3.

Mediation of post-traumatic growth in the relationship between valences of centralisation of HIV trauma and health-related quality of life.

		Estimate	SE	LLCI	ULCI	Remark
PEC
PEC-PHS
	Total effect (c)	0.207**	0.052	0.104	0.306
	Direct effect (c’)	0.147	0.052	0.047	0.250
	Indirect effect (ab)	0.060*	0.024	0.020	0.111	Mediated
PEC-REL
	Total effect (c)	0.037	0.058	−0.074	0.148
	Direct effect (c’)	0.012	0.062	−0.115	0.125
	Indirect effect (ab)	0.025	0.023	−0.014	0.074	No mediation
PEC-COG
	Total effect (c)	0.108	0.052	−0.001	0.208
	Direct effect (c’)	0.109	0.059	−0.011	0.220
	Indirect effect (ab)	−0.001	0.023	−0.045	0.046	No mediation
PEC-TRT
	Total effect (c)	−0.048	0.052	−0.148	0.051
	Direct effect (c’)	0.000	0.055	−0.112	0.105
	Indirect effect (ab)	−0.049*	0.024	−0.099	−0.004	Mediated
NEC
NEC-PHS
	Total effect (c)	0.227**	0.052	−0.323	−0.118
	Direct effect (c’)	0.174	0.052	−0.272	−0.070
	Indirect effect (ab)	0.053*	0.021	−0.097	−0.017	Mediated
NEC-REL
	Total effect (c)	−0.073	0.056	−0.183	0.038
	Direct effect (c’)	−0.054	0.058	−0.169	0.059
	Indirect effect (ab)	−0.018	0.019	−0.059	0.018	No mediation
NEC-COG
	Total effect (c)	−0.178*	0.050	−0.276	−0.077
	Direct effect (c’)	−0.186**	0.055	−0.290	−0.075
	Indirect effect (ab)	0.008	0.020	−0.031	0.048	No mediation
NEC-TRT
	Total effect (c)	−0.045	0.057	−0.151	0.065
	Direct effect (c’)	−0.100	0.057	−0.204	0.023
	Indirect effect (ab)	0.055*	0.022	0.015	0.105	Mediated

SE: standard error; PEC: positive event centrality; NEC: negative event centrality; PHS: physical health symptom dimension of health-related quality of life; REL: relationship dimension of health-related quality of life; COG: cognitive dimension of health-related quality of life; TRT: treatment impact dimension of health-related quality of life; LLCI: lower limit confidence interval; ULCI: upper limit confidence interval.

The best fit of the model was achieved with χ² = 100.49, df = 12, CMIN/DF = 8.37, p = .06, GFI = 0.957, NFI = 0.943, CFI = 1.00, TLI = 1.00, RMSEA = 0.061 (95% CI = [0.235, 269]).

p < .05; **p < .001.

On the relationship dimension of HRQoL (REL), the results showed that the total effect of PEC on REL was not significant (β_total = 0.037, SE = 0.058, p = .001). The direct effect of PEC on REL was not significant (β_direct = 0.012, SE = 0.062, p = .001), while the IE was significant (i.e., included zero) (IE = 0.025, 95% CI = LL = −0.014 to UL = 0.074), indicating that there was no mediation.

With regard to the cognitive dimension of HRQoL (COG), the results also showed that the total effect of PEC on COG, the direct effect of PEC and COG, and the IE were all not significant (β_total = 0.012, SE = 0.062, p = .853; β_total = 0.108, SE = 0.052, p = .058, and IE = −0.001, 95% CI = LL = −0.045 to UL = 0.046, respectively). On the fourth dimension of HRQoL (TRT), the total effect of PEC on TRT was not significant (β_total = −0.048, SE = 0.052, p = .001), while the direct effect of PEC on TRT was significant (β_direct = 0.000, SE = 0.055, p = .001). The confidence intervals of the IE were significant (i.e., did not include zero). PTG therefore mediated the relationship between PEC and TRT (IE = −0.049, 95% CI = LL = −0.099 to UL = −0.004).

NEC, PTG, and HRQoL

On the part of the negative valence of event centralisation (NEC) in association with the PHS, the results in Table 3 indicate that the total effect of NEC on PHS was significant (β_total = 0.227, SE = 0.052, p = .001), while the direct effect was not significant (β_direct = 0.174, SE = 0.052, p = .001). But the confidence intervals of the IE did not include zero (i.e., was significant), indicating that PTG mediated the relationship between NEC and PHS (IE = 0.053, 95% CI = LL = −0.097 to UL = −0.017).

Both the total effect of NEC on REL and the direct effect of NEC on REL were not significant (β_total = −0.073, SE = 0.056, p = .001 and β_direct = −0.054, SE = 0.058, p = .001). However, the IE was significant (i.e., included zero) in the confidence interval (IE = −0.018, 95% CI = LL = −0.059 to UL = 0.018), indicating the absence of mediation.

On the COG dimension of HRQoL, both the total effect of NEC on COG and the direct effect of NEC on COG were significant (β_total = −0.178, SE = 0.050, p = .034 and β_total = −0.186, SE = 0.020, p < .001), while the confidence intervals of the IE were significant because it included zero (IE = 0.008, 95% CI = LL = −0.031 to UL = 0.048), indicating the absence of mediation.

Concerning the TRT dimension of HRQoL, the total effect of NEC on TRT was not significant (β_total = −0.045, SE = 0.057, p = .001), the direct effect of NEC and TRT was also not significant (β_direct = −0.100, SE = 0.057, p = .001), but the confidence interval of the IE was significant (did not include zero) (IE = 0.055, 95% CI = LL = 0.022 to UL = 0.105), indicating a mediation effect. PTG therefore mediated the relationship between NEC and HRQoL in the TRT dimension of HRQoL.

Discussion

PEC and HRQoL

We examined the mediating role of PTG on the relationship between the negative and positive valences of EC and the HRQoL of PLWH in Nigeria. We found that PEC was positively associated with the PHS domain of HRQoL. To the best of our knowledge, this is the first study to explore this aspect of the EC–HRQoL association. The findings of this study suggest that when HIV-related trauma is construed in a positive emotional valence, it may contribute to improved physical health function. Clinicians and counsellors in HIV care facilities could, therefore, encourage clients’ positive mentation of their health experiences for improved physical health functions.

NEC and HRQoL

Consistent with previous studies (e.g., Brener et al., 2013; Earnshaw et al., 2013; Onu et al., 2017, 2019, 2020; Quinn & Chaudoir, 2009), NEC was negatively associated with PHS and the cognitive domain HRQoL (COG). This finding suggests that when HIV-related trauma is construed in a negative emotional valence by PLWH, it could result in poor physical and mental health functions. Onu et al. (2017) had suggested that PLWH experience poor HRQoL associated with their earlier negative thoughts about their health condition. In light of these findings, clinicians caring for PLWH may need to be more sensitive to clients expressing disease-specific negative self-definitions, in order to address it timely (Onu et al., 2020).

PEC and PTG

PEC was positively associated with PTG. Hence, the centralisation of HIV trauma into the client’s memory in a positive emotional valence is associated with experiencing PTG. This is consistent with the organismic valuing theory of PTG (Joseph & Linley, 2005), which postulates that PTG is an outcome of a positive evaluation of traumatic events by the trauma survivor. Clinicians and counsellors caring for PLWH may draw knowledge from this finding to encourage their clients to positively evaluate their traumatic health condition. This may enhance their positive mental health.

NEC and PTG

NEC was negatively associated with PTG. Therefore, when traumatic experiences associated with HIV are centralised in the client’s memory in a negative emotional valence, such client would less likely experience PTG. Clinical efforts towards enhancing PTG among PLWH also need to include controlling the extent to which clients express disease-specific negative self-definition.

PTG and HRQoL

PTG was positively associated with the PHS and TRT domains of HRQoL. Thus, the more PLWH experienced PTG, the better their HRQoL in the PHS and TRT domains. Earlier studies (e.g., Onu et al., 2016, 2019; Sim et al., 2015; Tanyi et al., 2014) had reported similar findings, suggesting that PTG has a positive influence on the HRQoL of PLWH. Experiencing growth in response to stress associated with HIV may enhance clients’ health functions, especially in the PHS and TRT domains.

PEC, PTG, and HRQoL

PTG mediated the association between PEC and HRQoL in the PHS and TRT domains. This indicates that the positive appraisal of HIV trauma is associated with improved HRQoL through its association with increased PTG. This finding, therefore, suggests that increased PTG is a mediating pathway explaining PEC–HRQoL association among PLWH. Fostering PTG among PLWH who have positively focused their thoughts on their health condition and identity may therefore serve as an effective approach to improving their health.

NEC, PTG, and HRQoL

PTG also mediated the association between NEC and HRQoL in the PHS and REL domains. This suggests that the negative appraisal of HIV trauma is associated with poor HRQoL through its negative association with PTG. This further implies that increased PTG is a mediating pathway explaining the NEC–HRQoL association among PLWH in Nigeria. Fostering PTG among PLWH who have negative self-definition seems pertinent in reducing the impact of NEC on their health and wellbeing.

Although previous studies have implicated numerous demographic and clinical variables in the HRQoL of PLWH (Degroote et al., 2014), our findings reveal a hidden mental process that may explain who among PLWH may experience poor or improved HRQoL. With the growing evidence of poor HRQoL among PLWH, there is a need to increase efforts in protecting this vulnerable group through empirical studies that inform intervention. The findings of this study, therefore, beckon the attention of health workers who are involved in managing PLWH in Nigeria (and perhaps elsewhere) to orient their programmes towards understanding and highlighting those psychosocial factors and pathways (such as trauma centrality and PTG) that have implications on the health and wellbeing of PLWH. Programmes aimed at improving their health and wellbeing should therefore explore the patients’ patterns of cognitive construal of the trauma associated with the disease and the growth emanating from the trauma in order to fully address their health concerns.

PEC did not significantly predict the REL, COG, and TRT domains of HRQoL. NEC did not significantly predict REL and TRT domains of HRQoL. PTG was not found to be significant in the REL and COG aspects of HRQoL. PTG did not also mediate PEC–HRQoL association in the REL and COG domains. PTG did not mediate NEC–HRQoL association in the COG and TRT domains. One possible explanation for these findings is that HRQoL is a dynamic concept such that its relationship with other health outcome variables may vary with concept measures, specific health conditions, and the racial/cultural demographics of the sample. Future studies should, therefore, investigate this further.

We recognise some limitations in this study. This study design was a cross-sectional collection of data through the use of subjective self-report measures. Recall bias and social desirability bias are usually associated with self-report measures. Causal inferences cannot, therefore, be made from these findings. A longitudinal study could overcome these challenges. Our data were gender-skewed (64.7% male and 35.3% female) and were also collected in only one hospital. These factors limit the extent of the generalisability of our findings. Future researchers could incorporate a more gender-balanced sample and also collect data in more than one hospital facility. Another limitation of this study, which future studies might focus on, is our inability to explore how the domains of PTG mediate the PEC/NEC–HRQoL association.

Conclusion

This study demonstrated the importance of PTG as a mediating variable in the link between the positive and negative valences of EC and HRQoL among PLWH. Results showed that (1) PEC was positively associated with HRQoL (PHS domain), (2) NEC was negatively associated with HRQoL (PHS and COG domains), (3) PEC was positively associated with PTG, and (4) NEC was negatively associated with PTG. The associations between each valence of EC and HRQoL were also mediated by PTG. These findings suggest that EC may not be a double-edged sword or a paradoxical variable that predicts both positive and negative health outcomes in the same direction, as suggested by previous studies (e.g., Blix et al., 2016; Boals & Schuettler, 2011; Groleau et al., 2013). It seems that the pattern of association between EC and health outcomes may be a function of the valence of emotion (negative or positive) upon which trauma survivors integrate their traumatic experiences.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Desmond Uchechukwu Onu

References

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.).

Berntsen

Rubin

D. C.

(2007). When a trauma becomes a key to identity: Enhanced integration of trauma memories predicts posttraumatic stress disorder symptoms. Applied Cognitive Psychology, 21(4), 417–431.

Blix

Birkeland

M. S.

Solberg

Ø.

Hansen

M. B.

Heir

(2016). The launching and ensnaring effects of construing a traumatic event as central to one’s identity and life story. Applied Cognitive Psychology, 30(4), 526–531.

Boals

Schuettler

(2011). A double-edged sword: Event centrality, PTSD and posttraumatic growth. Applied Cognitive Psychology, 25(5), 817–822.

Broadbridge

C. L.

(2018). Is the centralization of potentially traumatic events always negative? An expansion of the Centrality of Events Scale. Applied Cognitive Psychology, 32(3), 315–325.

Brooks

Graham-Kevan

Lowe

Robinson

(2017). Rumination, event centrality, and perceived control as predictors of post-traumatic growth and distress: The Cognitive Growth and Stress model. British Journal of Clinical Psychology, 56(3), 286–302.

Cann

Calhoun

L. G.

Tedeschi

R. G.

Triplett

K. N.

Vishnevsky

Lindstrom

C. M.

(2011). Assessing posttraumatic cognitive processes: The event-related rumination inventory. Anxiety, Stress, & Coping, 24(2), 137–156.

Centre for Disease and Control. (2020). Health-related quality of life concept. https://www.cdc.gov/hrqol/concept.htm

Degroote

Vogelaers

Vandijck

D. M.

(2014). What determines health-related quality of life among people living with HIV: An updated review of the literature. Archives of Public Health, 72(1), Article 40.

10.

Edmondson

(2014). An enduring somatic threat model of posttraumatic stress disorder due to acute life-threatening medical events. Social and Personality Psychology Compass, 8(3), 118–134.

11.

Earnshaw

V. A.

Smith

L. R.

Chaudoir

S. R.

Amico

K. R.

Copenhaver

M. M.

(2013). HIV stigma mechanisms and well-being among PLWH: A test of the HIV stigma framework. AIDS and Behavior, 17(5), 1785–1795.

12.

Faul

Erdfelder

Buchner

Lang

A. G.

(2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 42(4), 1149–1160.

13.

Frazier

P. A.

Tix

A. P.

Barron

K. E.

(2004). Testing moderator and mediator effects in counseling psychology research. Journal of Counseling Psychology, 51(1), 115–134.

14.

Garrido-Hernansaiz

Murphy

P. J.

Alonso-Tapia

(2017). Predictors of resilience and posttraumatic growth among people living with HIV: A longitudinal study. AIDS and Behavior, 21(11), 3260–3270.

15.

Groleau

J. M.

Calhoun

L. G.

Cann

Tedeschi

R. G.

(2013). The role of centrality of events in posttraumatic distress and posttraumatic growth. Psychological Trauma: Theory, Research, Practice, and Policy, 5(5), 477–485.

16.

Hays

R. D.

Cunningham

W. E.

Sherbourne

C. D.

Wilson IBWUAW Cleary

P. D.

McCaffrey

D. F.

Fleishman

J. A.

Crystal

Collins

Eggan

Shapiro

M. F.

(2000). Health-related quality of life in patients with human immunodeficiency virus infection in the United States: Results from the HIV Cost and Services Utilization Study. American Journal of Medicine, 15(108), 714–722.

17.

Joseph

Linley

P. A.

(2005). Growth following adversity: Theoretical perspectives and implications for clinical practice. Clinical Psychology Review, 26(8), 1041–1053.

18.

Joseph

Linley

P. A.

(2006). Growth following adversity: Theoretical perspectives and implications for clinical practice. Clinical Psychology Review, 26(8), 1041–1053.

19.

Keuroghlian

A. S.

Kamen

C. S.

Neri

Lee

Liu

Gore-Felton

(2011). Trauma, dissociation, and antiretroviral adherence among persons living with HIV/AIDS. Journal of Psychiatric Research, 45(7), 942–948.

20.

Lalanne

Chassany

Carrieri

Marcellin

Armstrong

A. R.

Lert

Spire

Dray-Spira

Duracinsky

(2016). A reduced factor structure for the PROQOL–HIV questionnaire provided reliable indicators of health-related quality of life. Journal of Clinical Epidemiology, 72, 116–125.

21.

Neigh

G. N.

Rhodes

S. T.

Valdez

Jovanovic

(2016). PTSD co-morbid with HIV: Separate but equal, or two parts of a whole? Neurobiology of Disease, 92, 116–123.

22.

Onu

D. U.

Ifeagwazi

C. M.

Orjiakor

T. C.

(2017). Intensified thinking. Nigerian Journal of Psychological Research, 13(1), 7–12.

23.

Onu

D. U.

Ugwu

D. I.

Kator

S. I.

(2020). Negative centralisation of HIV/AIDS’ trauma and health-related quality of life: Do Posttraumatic stress symptoms explain the link? African Journal of AIDS Research, 19(3), 206–213.

24.

Onu

D. U.

Ugwu

D. I.

Orjiakor

C. T.

(2019). Events centrality moderates the relationship between posttraumatic growth and health-related quality of life among people living with HIV. Journal of the Association of Nurses in AIDS Care, 30(6), 668–674.

25.

Onwujekwe

Orjiakor

C. T.

Hutchinson

McKee

Agwu

Mbachu

Balabanova

(2020). Where do we start? Building consensus on drivers of health sector corruption in Nigeria and ways to address it. International Journal of Health Policy and Management, 9(7), 286–296.

26.

Park

C. L.

Chmielewski

Blank

T. O.

(2010). Post-traumatic growth: Finding positive meaning in cancer survivorship moderates the impact of intrusive thoughts on adjustment in younger adults. Psycho-oncology, 19(11), 1139–1147.

27.

Perwitasari

D. A.

Urbayatun

Faridah

I. N.

Masyithah

(2017). Relationship of therapeutic outcome with quality of life on type 2 diabetes mellitus patients in Abdul Azis Singkawang hospital. IOP Conference Series: Materials Science and Engineering, 259, 1–7.

28.

Quinn

D. M.

Chaudoir

S. R.

(2009). Living with a concealable stigmatized identity: The impact of anticipated stigma, centrality, salience, and cultural stigma on psychological distress and health. Journal of Personality and Social Psychology, 97(4), 634–651.

29.

Reiland

S. A.

Clark

C. B.

(2017). Relationship between event type and mental health outcomes: Event centrality as mediator. Personality and Individual Differences, 114(1), 155–159.

30.

Reis

R. K.

Santos

C. B.

Gir

(2012). Quality of life among Brazilian women living with HIV/AIDS. AIDS Care, 24, 626–634.

31.

Rzeszutek

Gruszczyńska

(2018). Posttraumatic growth among people living with HIV: A systematic review. Journal of Psychosomatic Research, 114(14), 81–91.

32.

Schipper

Clinch

J. J.

Olweny

C. L.

(1996). Quality of life studies. In Spilker

(Ed.), Quality of life and pharmacoeconomics in clinical trials (pp. 11–23). Lippincott-Raven Publishers.

33.

Sim

B. Y.

Lee

Y. W.

Kim

S. H.

(2015). Post-traumatic growth in stomach cancer survivors: Prevalence, correlates and relationship with health-related quality of life. European Journal of Oncology Nursing, 19(3), 230–236.

34.

Tanyi

Szluha

Nemes

Kovács

Bugán

(2014). Health-related quality of life, fatigue, and posttraumatic growth of cancer patients undergoing radiation therapy: A longitudinal study. Applied Research in Quality of Life, 9(3), 617–630.

35.

Tedeschi

R. G.

Calhoun

L. G.

(1996). The Posttraumatic Growth Inventory: Measuring the positive legacy of trauma. Journal of Traumatic Stress, 9(3), 455–471.

36.

Tedeschi

R. G.

Calhoun

(2004). Posttraumatic growth: A new perspective on psychotraumatology. Psychiatric Times, 21(4), 58–60.

37.

Wamser-Nanney

(2019). Event centrality: Factor structure and links to posttraumatic stress disorder symptom clusters. Journal of Traumatic Stress, 32(4), 516–525.