Effects of (In)Congruency in Fertility Motivation on Fertility Desire and Intention Among Couples Living with HIV: A Dyadic Approach

doi:10.21203/rs.3.rs-2253191/v1

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Effects of (In)Congruency in Fertility Motivation on Fertility Desire and Intention Among Couples Living with HIV: A Dyadic Approach

https://doi.org/10.21203/rs.3.rs-2253191/v1

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Fertility decision-making plays a negligible role in completing fertility goals among couples living with HIV. Furthermore, being commonly matched concerning fertility motivation also seems essential for fertility desire/intention. However, there is a lack of previous studies that report on intra-couple similarities or dissimilarities on the sequence of motivation-desire-intention on fertility. We aimed to document the effects of (in)congruency in fertility motivation linked to intention via desire among couples living with HIV. The actor-partner interdependence model (APIM) and Dyadic Response Surface Analysis were the analytical tools used in this research. Couples living with HIV were selected from the antiretroviral therapy center clinic in Kunming, China between October and December 2020. A total of 314 couples were enrolled in this cross-sectional study. Only significant actor effects of fertility motivation on intention, which was partly mediated by desire based on the APIM, was observed in the wives. Husbands tended to dominate the fertility motivation. Furthermore, congruency was observed in the level of significance of the models between fertility desire and intention and between those of wife and husband. To complete the fertility goal, counseling should simultaneously assist the husband and wife to attain stronger positive fertility intention through a desire by targeting similar fertility motivations in both partners.

Biological sciences/Psychology

Health sciences/Diseases

Health sciences/Health care

(In)congruency

Dyadic Data Analysis

Traits-Desires-Intentions-Behavior model

Couples Living with HIV

Couples’ fertility decision-making is likely to change in the HIV context which is marked by psychosocial adjustment for both the husbands and wives. A systematic review found that 42.0% of people living with HIV wanted to have children ¹. In low- and middle-income countries, fertility desires/intentions ranged from 8–84% ^2–4. In high-income countries, the prevalence was lower (32–58%) 5, 6. One prevailing factor that may contribute to fertility intention is positive motivation. In previous research that examined the fertility of expectant couples, positive fertility motivations were the most often reported reason for positive fertility desire under antiretroviral treatment (ART), as well as prevention of mother-to-child HIV transmission efficacy ^7,8.

Traits-desires-intentions-behavior Framework

Our study was based on the Traits-Desires-Intentions-Behavior (TDIB) model ⁹. It states that the four main steps of fertility decision-making are fertility motivation, desire, intention, and behavior. Fertility motivation is the feeling or faith of happiness, wellbeing, identity, social control, and continuity of offspring in the family ¹⁰. Fertility desire was defined as the desire/willingness to have a child or another child at the present. Fertility desire reflects a wish to achieve a childbearing goal by a sort of action. Fertility intention consists of a particular choice to seek a reproductive objective and a plan for putting that fertility decision into action ¹¹. Stable motivational dispositions affect reproductive behavior by influencing the desire and intention to have a child ¹¹. HIV-positive Canadian women supported the TDIB model ¹². Higher desire and purpose lead to more child-bearing. Knowing the relationship between HIV-positive couples' objectives, such as happiness, well-being, identity, and continuity, fertility desire, and intention might help prevent mental health problems. There is a lack of social support for reproductive goals. Understanding the process from stable motivational dispositions to fertility intention enhances the knowledge of HIV-positive women's reproductive decision-making, barriers, and public health policies and services to complete their fertility goal ¹³.

Congruence In Fertility Motivation Between Husband And Wife

Within husband and wife, there is a dyadic process in the content of reproduction. Couples’ fertility motivation can influence fertility desire/intention of his/her spouse. From a U.S. national survey, motive congruence of parenthood between partners interdependence in dyadic processes posits that, in the context of reproduction, a person's results are entwined with the fertility intention and ideas of the other individual ¹⁴. HIV-positive couples have the unusual challenge of managing their fertility within the HIV setting. The combination of both partners' desire/intention to have children, as opposed to the influence of each partner's unique fertility motivation, may thus be crucial to understanding both partners' fertility desire/intention. However, little is known regarding the possible link between a couple's concordance or discordance on fertility motivation, such as happiness, well-being, and identity, and the consequences for childbearing desire/intention. Partners in fertility were likely to have comparable fertility desires ¹⁵. A prior study posited that similarity between partners has advantages for both individuals and their fertility behavior among couples living with HIV (CLWH) ¹⁶. More resemblance on fertility decision-making between couples is good since it enables them to comprehend each other better ¹⁷. Individuals with similar motivations are more likely to exhibit similar desires and intentions in response to a reproductive event ⁷, such as the commencement of HIV transmission worries associated with the pregnancy if they have identical motivations. Indeed, factors such as increased dyadic motivation have been observed to influence the reproductive intentions of couples in early ART among HIV-positive East Africans ¹⁸. When a partner lacks a comparable motive to one's own, this disparity may be indicative of a negative fertility goal since it generates inconsistency and does not legitimize one's choice ¹⁹. The incongruence of the partner's reproductive motive elicits and combats unpleasant feelings through this mechanism.

Objective Of The Current Study

The objective of the current study was to document the effects of (in)congruency in fertility motivation linked to intention via desire among couples living with HIV using the actor-partner interdependence model (APIM) and Dyadic Response Surface Analysis (DRSA). To achieve this objective, we divided the analysis into three parts: the causal pathway; degree of husband-wife congruence of fertility motivations; and congruency effect of fertility motivation between wives and husbands on fertility desire/intention.

Study Design and Setting

This was a cross-sectional study of a sample of couples seeking childbearing motivation in China between October and December 2020 in an ART clinic of the Third People’s Hospital in Kunming, China. This hospital is the biggest tertiary care center serving HIV patients. Couples who met the following criteria were invited to participate in this study: aged 18–45 years for females, 18–50 years for males, and able to read and write in Chinese. Couples who informed consent were requested to fill out the questionnaire separately in a quiet place, which took about 15–30 minutes to complete. In total, 314 heterosexual CLWH agreed to participate and completely fill out the instruments. All methods were carried out in accordance with relevant guidelines and regulations.

Variables

Demographic Characteristics

The questionnaire assessed ethnicity, age, educational attainment, occupation, religion, income, and registered residence of the subjects.

Fertility Motivation

Fertility motivation was measured by the Parenthood Subscale of the People Living With HIV Scale (see SUPPLEMENTAL APPENDIX Table 1) ²⁰. The scale is widely used as a self-report instrument. It consists of 11 items designed to measure HIV-related fertility motivation. Items are rated on a 5-point Likert scale ranging from 1 (definitely disagree) to 5 (definitely agree). Total subscale scores ranged from 11 to 55. Higher scores indicated greater levels of fertility motivation. The Chinese version of this scale was validated and is widely used among people living with HIV in China. For this study, Cronbach’s alpha coefficients of the motivation for husband and wife were 0.84 and 0.87, respectively.

Fertility Desire

General desire to have another child was assessed using the following question: ‘‘Do you want to have another child at the present?’’ The possible responses were “yes”, “not sure”, or “no” ²¹.

Fertility Intention

Fertility intention was measured by a single item ²², “How likely are you going to have another child within the next three years?” on a five-point scale that ranged from definitely not to definitely yes.

Statistical Analysis

The descriptive statistics and bivariate correlations for all psychometric variables were computed. Normal distributions were evaluated by assessing estimates of skewness and kurtosis, and acceptable normality was determined using cutoffs of − 3/+3 ²³. We applied two dyadic models to explore the congruency effect of fertility motivation and desire/intention, including the APIM and DRSA based on the TDIB model. All models were analyzed using the lavaan package for R ²⁴.

Actor-Partner Interdependence Model (APIM)

The first part was to assess the effects of fertility motivation on intention mediated by desire using the APIM ²⁵. Figure 1 summarizes our APIM according to the TDIB model. Actor causation pathway was proposed for wives in the upper part and for husbands in the lower part. The partner effects for wives and husbands of spouses’ fertility motivation on fertility intention via desire are shown by the crossing lines. Fertility motivation is a latent variable loading with four latent variables: happiness; well-being; identity; and continuity. Each of these variable loads refer to its own observed variable from hw1 to ch3. Fertility motivation influences fertility intention directly and through fertility desire. The crossing arrows indicate influences on the partner. Finally, the errors from predicting fertility intention of the wife and husband are correlated.

Frequencies of Fertility Motivation Discrepancies and Congruence Between Husband and Wife

The second section determined whether it was the husband or wife who dominated fertility motivation. For each couple, the difference in the motivation factor scores was determined and the standard deviation (SD) in the difference was obtained. The wives’ ratings were deducted from the husbands’ ratings. The couple’s fertility motivation was dominated by the husband if the husband-wife score difference was larger or smaller than the SD of − 0.5. If the difference was larger than the SD of 0.5, fertility motivation was dominated by the wife. Otherwise, there was congruence in fertility motivation.

Effects of Congruency

The third section tested the effects of dyadic congruency in fertility motivation on fertility desire/intention using the DRSA ²⁶. We examined polynomial regression route models with our dyadic data (Fig. 2). Two equations independently predict husband and wife fertility intention. The two equations share variables that include his/her own and the spouse’s fertility motivation, their interaction, and the quadratic terms of the motivation in case the response was curvilinear.

Yw = b10 + b11XW + b12Xh + b13XwXh + b14Xw2 + b15Xh2 + e (1)

Yh = b20 + b21Xh + b22Xw + b23XwXh + b24Xh2 + b25Xw2 + e (2)

Equations (1) and (2) are dyadic polynomial regression equations for husband-and-wife reproductive desire/intention (Yw and Yh) predicted by couple personalities (Xw and Xh), the interaction term, XwXh, and quadratic terms Xh2 and Xw2. Each equation assesses two linear (fertility motivation) coefficients, one linear-linear interaction, and two quadratic coefficients.

Based on Eqs. (1) and (2), line of congruence (LOC) and line of incongruence (LOIC) with the interaction/quadratic terms for the wife’s side are defined as linear congruence a1w=(b1w + b2w), linear incongruence a3w=(b1w-b2w), curvature congruence a2w=(b3w + b4w + b5w), and curvature incongruence a4w=(b3w-b4w + b5w). The male surface parameters are defined identically, with the addition of coefficients with the notation ‘h’. Our major concern in the present research was the relationship between the degree of disagreement between a wife’s own level of fertility motivation and her husband’s level of fertility motivation (a4) and the direction of disagreement (a3) and each partner’s fertility desire and purpose. The analysis also examined how the degree of agreement between a wife’s own level of fertility motivation and her husband’s level of motivation (a1) was associated with fertility desire and intention—that is, when partners have high agreement, is it better to agree on higher versus lower fertility desire and intention? —and whether a1 is best described by a nonlinear relationship (a2)—that is, whether the association between agreement and deliberation is linear or nonlinear.

Statistical Software and Model Fit

All APIM and DRSA models were tested in two steps. First, we set up an unconstrained model in which all parameters were estimated freely. Second, we forced all of the actor and partner effects to be equal for wives and husbands in the constrained model. Subsequently, we evaluated the saturated model between the constrained and unconstrained model via the χ2 difference test. All models were analyzed using the lavaan package for R ²⁷. The APIM used the maximum likelihood robust estimator. The overall model fit was evaluated using multiple fit indices as suggested in the literature. Specifically, five goodness-of-fit indices were used that included the chi-square/degree of freedom (χ2/df), Tucker-Lewis Index (TLI), comparative fit index (CFI), root mean square error of approximation (RMSEA), and standardized root means square residual (SRMR). Values of χ2/df < 3, TLI and CFI > 0.90, and RMSEA and SRMR < 0.08 are indicative of a good fit with the data. We generated confidence intervals using bootstrapped percentile samples in the DRSA. Percentile bootstrapping was done using 10,000 bootstrapped samples.

Characteristics of Couples Living with HIV

A total of 314 couples were identified, and verbal commitments were obtained to participate in the research with their spouses and be included in the data analysis. The mean (SD) ages of wives and husbands were 33.8 (5.2) and 36.9 (5.8) years, respectively. In the husband group, the most frequent educational level was senior high school or less. In the wife group, the most common educational level was junior high school or less. The percentage of husbands with a graduate degree or higher was 26.4%, which was more than the proportion of spouses with a graduate degree or higher (17.8%). When questioned about their job status, the majority of wives in the study said they were unemployed. Many respondents were of Han ethnicity and dwelled in rural areas. The majority of couples (63.2%) indicated New Rural Cooperative Medical Insurance as their supplier of medical insurance. Table 1 displays the sociodemographic and HIV serostatus characteristics of the HIV-positive couples. As a variable at the couple level, more than over half of the couples had a low household monthly income of less than CNY 9,999). HIV positive on the wife's side was somewhat more prevalent than on the husband’s side among the HIV discordant couples. The socio-economic and HIV status characteristics are summarized in Table 1.

Table 1

Socio-demographic characteristics
Variables	Wife (314)	Husband (314)	Total (N = 628)
Age Categories
20–30	73 (23.2)	31 (9.9)	104 (16.6)
31–35	102 (32.5)	95 (30.3)	197 (31.4)
36–40	101 (32.2)	92 (29.3)	193 (30.7)
41+	38 (12.1)	96 (30.6)	134 (21.3)
Registered residence
Rural	205 (65.3)	192 (61.1)	397 (63.2)
Urban	109 (34.7)	122 (38.9)	231 (36.8)
Ethnic Group
Han	262 (83.4)	282 (89.8)	544 (86.6)
Others	52 (16.6)	32 (10.2)	84 (13.4)
Education level
Primary school	43 (13.7)	33 (10.5)	76 (12.1)
Junior school	123 (39.2)	94 (29.9)	217 (34.6)
Senior school	92 (29.3)	104 (33.1)	196 (31.2)
Graduate and above	56 (17.8)	83 (26.4)	139 (22.1)
Occupation Status
Government employee	17 (5.4)	44 (14)	61 (9.7)
Jobless	104 (33.1)	48 (15.3)	152 (24.2)
Manual laborer	26 (8.3)	45 (14.3)	71 (11.3)
Private employee	84 (26.8)	73 (23.2)	157 (25)
Self-employed	83 (26.4)	104 (33.1)	187 (29.8)
Medical insurance status
NRCMS	192 (61.1)	180 (57.3)	372 (59.2)
UEBMI	21 (6.7)	36 (11.5)	57 (9.1)
URBMI	101 (32.2)	98 (31.2)	199 (31.7)
Household monthly income, CNY
0–5,999	54 (32.1)	36 (24.7)	90 (28.7)
6,000–9,999	49 (29.2)	29 (19.9)	78 (24.8)
10,000–19,999	38 (22.6)	40 (27.4)	78 (24.8)
20,000+	27 (16.1)	41 (28.1)	68 (21.7)

NRCMS New Rural Cooperative Medical Insurance Scheme, UEBMI Urban Employees Basic Med-ical Insurance, URBMI Urban Residents Basic Medical Insurance, CNY Chinese Yuan.

Descriptive Statistics And Bivariate Correlation In Husband-wife Dyads

Table 2 shows Pearson’s correlation coefficients between fertility motivation and fertility desire/intention in both the husbands and their wives. Despite the high mean values of the variables, the correlations between husband and wife in the observed and latent variables of fertility motivation and desire/intention were strong (0.3–0.74). In this study, all scales had good Cronbach’s alpha reliability (CR = 0.73–0.96) and good average variance extracted discriminant validity coefficients (0.51–0.93).

Table 2

Means, standard deviations, correlations, and average variance extracted among the study variables
	Mean (SD)	1	2	3	4	5	6	7	8	9	10	11	12	13
1.Happiness (Husband)	4.2 (0.48)	-
2.Well-being (Husband)	4.5 (0.57)	0.53	-
3.Identity (Husband)	3.9 (0.58)	0.47	0.64	-
4.Continuity (Husband)	3.9(0.69)	0.29	0.4	0.35	-
5.Happiness (Wife)	4.2 (0.52)	0.3	0.41	0.37	0.23	-
6.Well-being (Wife)	4.5 (0.62)	0.43	0.59	0.52	0.32	0.61	-
7.Identity (Wife)	3.9 (0.69)	0.34	0.46	0.41	0.25	0.48	0.68	-
8.Continuity (Wife)	3.5 (0.76)	0.16	0.22	0.19	0.12	0.22	0.32	0.25	-
9.Fertility motivation (Husband)	4.1 (0.42)	0.62	0.85	0.75	0.47	0.49	0.69	0.54	0.25	-
10.Fertility motivation (Wife)	4.0 (0.46)	0.46	0.63	0.56	0.35	0.65	0.93	0.73	0.34	0.74	-
11.Fertility desire (Husband)	0.60 (0.49)	0.19	0.27	0.24	0.15	0.2	0.28	0.22	0.1	0.31	0.3	-
12.Fertility desire (Wife)	0.54 (0.50)	0.2	0.28	0.24	0.15	0.29	0.42	0.33	0.15	0.32	0.45	0.46	-
13.Fertility intention (Husband)	3.43 (1.13)	0.19	0.27	0.24	0.15	0.22	0.31	0.24	0.11	0.31	0.33	0.57	0.53	-
14.Fertility intention (Wife)	3.14 (1.22)	0.2	0.27	0.24	0.15	0.27	0.38	0.3	0.14	0.32	0.41	0.51	0.64	0.73
CR	-	0.87	0.93	0.81	0.77	0.90	0.96	0.77	0.73	0.85	0.86	-	-	-
AVE	-	0.70	0.88	0.59	0.55	0.75	0.93	0.67	0.51	-	-	-	-	-
Boldface coefficients: p < 0.01
CR Cronbach's alpha, AVE average variance extracted

Dyadic Analysis

Actor-Partner Interdependence Modeling (APIM)

Figure 3 summarizes the results of the APIM analysis. The latent variable fertility motivation had a high load level on the observed variable. The wife’s fertility motivation had an indirect influence on fertility intention mediated by fertility desire. Consistent with both the husband-and-wife correlation matrix for all variables summarized in Table 2, APIM showed significant influence of the husband on the wife’s fertility desire and intention and vice versa. R2 was 0.48 for the husband and 0.42 for the wife. This model fit the data well: χ2/df = 2.5; CFI = 0.920; TLI = 0.906; RMSEA = 0.069; and SRMR = 0.074.

Downstream, the individual fertility desire was associated significantly and positively with the spouse's fertility intention. Upstream, the wife’s fertility motivation significantly influenced fertility desire. However, we did not find a significance relationship on the husband’s side, and no cross influence of fertility motivation was observed in the spouses’ fertility desire.

Dyadic Response Surface Analysis

Table 3 displays the results of the dyadic polynomial regression coefficients and the surface tests. The surface parameters are the most important tests for our hypotheses. Figures 4 and 5 represent the response surface plots, illustrating the relationships between combinations of actor’s (x-axis) and partner’s (y-axis) fertility motivation and the wives’ and husbands’ fertility desire and intention (z-axis). We compared an unconstrained model to one in which actor and partner effects were bound to be equivalent. This constrained model did not perform worse than the unconstrained model (Δχ2 = 5.28, Δdf = 5; p > 0.05), which demonstrated no significant differences between the wives and husbands regarding the effect of fertility motivation on desire/intention. Moreover, the constrained model matched the data well, as evidenced by the following fit indices: χ2/df = 1.35; CFI = 0.997; TLI = 0.994; RMSEA = 0.014; and SRMR = 0.024.

Frequencies Of Fertility Motivation Discrepancies And Congruence

More than half (165, 52.5%) of the 314 couples had congruence in fertility motivation. Ninety-nine (31.5%) and 50 (15.9%) had husband and wife dominance, respectively (see SUPPLEMENTAL APPENDIX Table 2). The frequencies of discrepancy between wives' and husbands' motivation were larger than 10%, which indicated that DRSA was warranted for analyzing the level of congruence in the data.

Congruency And Incongruency In Fertility Motivation And Fertility Desire/intention

Table 3 summarizes the DRSA model analysis results. Figures 4 and 5 display the response surface plot. The regression coefficients are the same as those in Fig. 2 except that the suffix ‘w’ and ‘h’ were omitted. There is a similarity in the level of significance of the models between fertility desire and intention, and between those of wife and husband. The personal effect (b1 for wife and b2 for husband) were highly significant. But the effects from the spouse (b1 for wife and b2 for husband) were not.

Surface analysis showed that congruence (a1 = b1 + b2) of the fertility motivation significantly enhanced fertility desire and intention of CLWH. More specifically, the curvilinear term (a2 = b3 + b4 + b5) indicated that the husband’s fertility intention increased more sharply when both couple’s motivation corresponded to increasingly high levels.

Incongruence of fertility motivation, on the other hand, affects only the wife’s fertility desire and intention. The wife’s motivation (a3 = b1 − b2 > 0) increased her fertility desire. Otherwise, her husband’s motivation (b1 − b2 < 0) would negatively affect her fertility desire. However, incongruence of fertility motivation influenced fertility intention of couples living with HIV. As shown by the significant positive a4 value for the husband's fertility intention and negative a4 for his fertility desire, the husbands reported higher fertility intention and lower desire when the degree of motivation discrepancy was larger. However, the degree of motivation discrepancy was not associated with fertility intention for either couple; that is, overall, couples who were matched on fertility motivation did not report significantly greater relationship fertility intention than couples who were mismatched.

Table 3

Dyadic Polynomial Regression Coefficients and Response Surface Parameters of Both Partners’ Fertility Motivation and Desire on Fertility Intention (N = 314 couples)
		Fertility intention		Fertility desire
		Wife	Husband	Wife	Husband
Dyadic poly regression coefficients	Constant (b0)	3.376**	3.361**	0.614**	0.584**
	Wife's motivation (b1)	0.083**	0.038*	0.041**	0.017*
	Husband's motivation (b2)	0.029	0.059**	0.006	0.019**
	b1² (b3)	0	-0.001	0.001	-0.001
	b2² (b4)	0.001	0	-0.001	0.003*
	Mutual motivation b1*b2 (b5)	0	0.006**	0.001	0
Response surface parameters	R2	15.8	17.1	18.6	11.6
	a1=(b1 + b2)	0.112**	0.097**	0.047**	0.036**
	a2=(b3 + b4 + b5)	0.001	0.005**	0.001	0.002**
	a3=(b1 − b2)	0.054	-0.021	0.035**	-0.001
	a4=(b3 − b4 + b5)	0.001	0.005	0.002	−0.005*
** p < 0.01, *p < 0.05

The coefficients a1 and a2 represent the slope of each surface along the line of congruence, while 𝑎4 represents the slope of each surface along the line of incongruence, where b1, b2, b3, b4, and b5 are the unstandardized β-weights coefficients.

Among the couples living with HIV, we found that fertility desire and intention were highly correlated and had mutual influence between the wife and husband. Fertility motivation influenced fertility desire on the wife’s side but not on the husband’s side. Individual fertility motivation had no significant effect on the spouse. Congruence of fertility motivation was found in more than half of the couples. For the incongruent couples, the husband’s motivation was often stronger than the wife’s motivation. Congruence in fertility motivation enhanced the individual fertility desire/intention on both sides, whereas the husband’s stronger motivation depleted fertility desire in the wife.

Casual Pathway Of Fertility Motivation-desire-intention

The linkage between fertility desire and intention among people living with HIV was reported in a previous study in Ontario, Canada ¹². We confirmed this relationship in CLWH and demonstrated a strong intercorrelation within CLWH. We also found influences of individual fertility desire on the spouse’s fertility intention.

We put fertility motivation as a factor influencing fertility desire. This was confirmed on the wife’s side but not on the husband’s side. This difference was unexpected because there was a strong correlation (r = 0.74) between the husbands’ and wives’ fertility motivation. Perhaps, such a difference was due to a difference in perceived fertility responsibility in Chinese women and men. In the Chinese culture, women bear more responsibility on fertility than the husband ^28,29. Chinese wives are expected to give birth to continue the blood line of the husband. Also, the mother plays more important roles in raising children. Family planning procedures are more commonly done on the wife’s side ³⁰. With low perceived fertility responsibility among men, their fertility motivation would not have significant effect on fertility desire and intention. Globally and in China, the husband plays a passive role in fertility regulation. For CLWH without male heirs, HIV-positive women risk desertion because the male may have little decision-making authority. Mothers-in-law who urge their daughters-in-law to have children do not inquire about lineage with their husbands in Vietnam or in China ^15,31.

Congruency And Congruency Of Fertility Motivation On Fertility Desire/intention In Wife-husband Dyads

Our results further highlight the importance of moving beyond one-way perspectives and considering both the perspectives of the wives and husbands when examining fertility motivation.

Our findings showed that more than one-half of congruence in fertility motivation among the wives and husbands were consistent with most previous studies using a DRSA among couples ^32–34. Among the incongruent couples, the husband was more likely to have stronger fertility motivation than the wife.

The positive effects of congruence on fertility motivation on both the wife’s and husband’s fertility desire and intention indicated a statistical effect. With synergism, congruent couples would be more successful in carrying out their family plan. On the other hand, a husband’s stronger motivation was not only ineffective in raising his fertility desire and intention but may also deplete the effect of an already lower motivation of the wife on fertility desire and intention. If may indicate that among women with low fertility motivation, demonstrating motivation by her husband would have a further negative effect on her own fertility desire and intention. If this causal relationship is true, the dominating husband should be counselled to be aware of this possible unwanted effect and if possibly adjust himself to fit with this incongruent setting.

Strengths And Limitations

This dyadic analysis enabled us to gain better insight into the interrelationship within CLWH using the similarity and discrepancy of fertility motivation based on the TDIB model. More important is our finding of the negative effect of incongruence of fertility motivation of the wives with low fertility motivation. However, although this statistical analysis gave clear results, the actual causal relationship needs to be confirmed with similar studies.

Despite the high level and correlation of fertility desire and motivation in the study of CLWH, incongruence in fertility motivation should not be ignored. Our findings may suggest the need to examine and compare fertility motivation within the couple before giving fertility advice. The husband’s domination in fertility motivation was common and may negatively affect the wife’s fertility desire and intention if her fertility motivation is already weak.

HIV, human immunodeficiency; AIDS, acquired immunodeficiency syndrome; ART, antiretroviral therapy; CLWH, couples living with HIV; APIM, actor-partner interdependence model; DRSA, dyadic response surface analysis; TDIB, Traits-Desire-Intention-Behavior (TDIB); LOC, line of congruence; LOIC, line of incongruence; SEM, structural equation model; χ2/df, chi-square/degree of freedom; CFI, comparative fit index; TLI, Tucker-Lewis Index; SRMR, standardized root means square residual; RMSEA, root mean square error of approximation.

Authors’ Contributions Conceptualization, Yingwu Guo and Virasakdi Chongsuvivatwong; Data curation, Yingwu Guo; Formal analysis, Yingwu Guo, Virasakdi Chongsuvivatwong, and Jun Liu; Funding acquisition, Yingwu Guo, Jun Liu, Yingrong Du; Investigation, Yingwu Guo, Jun Liu, Yingrong Du; Methodology, Yingwu Guo and Virasakdi Chongsuvivatwong; Project administration, Yingwu Guo and Virasakdi Chongsuvivatwong; Resources, Jun Liu, Yingrong Du; Supervision, Virasakdi Chongsuvivatwong; Validation, Yingwu Guo and Virasakdi Chongsuvivatwong; Writing – original draft, Yingwu Guo; Writing – review & editing, Virasakdi Chongsuvivatwong.

Acknowledgments This study is a part of the first author’s thesis in partial fulfillment of the requirements for a Ph.D. degree in Epidemiology at Prince of Songkla University, Songkhla, Thailand. We greatly appreciate the assistance from the staff members of the HIV treatment center who supported our study at the Third People’s Hospital in Kunming, China.

Funding: Funding was received from the Higher Education Research Promotion and Thailand’s Education Hub for the Southern Region of ASEAN Countries Project Office of the Higher Education Commission (TEH-AC:016/2018).

Data Availability Statement All pertinent information is contained in the text and its accompanying information files. Data and codes can be provided by the corresponding author (Virasakdi Chongsuvivatwong) upon reasonable request.

Institutional Review Board Statement This study was approved by the Ethics Committee of Prince of Songkla University (REC-63-208-18-1) and the Research Ethics Review Committee of the Third People’s Hospital (2020072001). In this study, pseudonyms were used to protect the identity of the participants.

Consent for Publication Not applicable

Conflicts of Interest The authors declare no conflict of interest.

Author Details 1. Department of Infectious Diseases, Third People’s Hospital of Kunming City, Kunming, Yunnan, People’s Republic of China. 2. Department of Epidemiology, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkla, Thailand

Disclaimer The opinions expressed in this viewpoint are solely those of its writers and do not necessarily reflect the opinions of the institutions with which they are connected.

Yan, X., Du, J. & Ji, G. Prevalence and factors associated with fertility desire among people living with HIV: A systematic review and meta-analysis. PLoS One 16, (2021).
Martins, A., Alves, S., Chaves, C., Canavarro, M. C. & Pereira, M. Prevalence and factors associated with fertility desires/intentions among individuals in HIV-serodiscordant relationships: a systematic review of empirical studies. J Int AIDS Soc 22, e25241 (2019).
Jose, H. et al. Fertility Desires and Intentions among People Living with HIV/AIDS (PLWHA) in Southern India. J Clin Diagn Res 10, OC19–OC22 (2016).
Kuete, M. et al. Sexual Practices, Fertility Intentions, and Awareness to Prevent Mother-to-Child Transmission of HIV Among Infected Pregnant Women at the Yaounde Central Hospital. Sexual Medicine 4, e97–e105 (2016).
Muldoon, K. A. et al. ‘He said, she said’: assessing dyadic agreement of reported sexual behaviour and decision-making among an HIV sero-discordant couples cohort in Uganda. J Fam Plann Reprod Health Care 43, 142–146 (2017).
Mindry, D. et al. Fertility Desires Among HIV-Infected Men and Women in Los Angeles County: Client Needs and Provider Perspectives. Matern Child Health J 17, 593–600 (2013).
Klein, J., Peña, J. E., Thornton, M. H. I. & Sauer, M. V. Understanding the Motivations, Concerns, and Desires of Human Immunodeficiency Virus 1–Serodiscordant Couples Wishing to Have Children Through Assisted Reproduction. Obstetrics & Gynecology 101, 987–994 (2003).
Rogers, A. J. et al. Couple interdependence impacts HIV-related health behaviours among pregnant couples in southwestern Kenya: a qualitative analysis. Journal of the International AIDS Society 19, 21224 (2016).
Miller, W. B. Childbearing motivations, desires, and intentions: a theoretical framework. Genet Soc Gen Psychol Monogr 120, 223–258 (1994).
Dyer, S., Mokoena, N., Maritz, J. & van der Spuy, Z. Motives for parenthood among couples attending a level 3 infertility clinic in the public health sector in South Africa. Human Reproduction 23, 352–357 (2008).
Miller, W. B. Differences between fertility desires and intentions: Implications for theory, research and policy. Vienna Yearbook of Population Research 75–98 (2011).
Wagner, A. C., Ivanova, E. L., Hart, T. A. & Loutfy, M. R. Examining the Traits-Desires-Intentions-Behavior (TDIB) Model for Fertility Planning in Women Living with HIV in Ontario, Canada. AIDS Patient Care STDS 28, 594–601 (2014).
Finocchario-Kessler, S. et al. Do HIV-infected women want to discuss reproductive plans with providers, and are those conversations occurring? AIDS Patient Care STDS 24, 317–323 (2010).
Shreffler, K. M., Tiemeyer, S., McQuillan, J., Greil, A. L. & Spierling, T. Partner congruence on fertility intentions and values: Implications for birth outcomes. Journal of Social and Personal Relationships 36, 2307–2322 (2019).
Tran, B. X., Duong, H. D., Nguyen, A. Q. & Pham, L. D. Child Desire Among Men and Women Living with HIV/AIDS in the Traditional Culture of Vietnam. AIDS Behav 22, 2888–2894 (2018).
Beyeza-Kashesya, J. et al. My partner wants a child: A cross-sectional study of the determinants of the desire for children among mutually disclosed sero-discordant couples receiving care in Uganda. BMC Public Health 10, 247 (2010).
Miller, W. B. & Pasta, D. J. Couple disagreement: effects on the formation and implementation of fertility decisions. Pers Relatsh 3, 307–336 (1996).
Mujugira, A. et al. Fertility Intentions and Interest in Early Antiretroviral Therapy Among East African HIV-1–Infected Individuals in Serodiscordant Partnerships. JAIDS Journal of Acquired Immune Deficiency Syndromes 63, e33 (2013).
Mandell, L. N., Rodriguez, V. J., Peltzer, K., Weiss, S. M. & Jones, D. L. Fertility intentions of women living with HIV and their male partners during the perinatal period in rural South Africa. Int J STD AIDS 32, 740–750 (2021).
BELL, J. S., BANCROFT, J. & PHILIP, A. Motivation For Parenthood: A Factor Analytic Study of Attitudes Towards Having Children. Journal of Comparative Family Studies 16, 111–119 (1985).
Miller, W. B. Differences between fertility desires and intentions: implications for theory, research and policy. Vienna Yearbook of Population Research 9, 75–98 (2011).
Miller, W. B. Fertility Intentions, Counterintentions, and Subintentions: 31.
Bonett, D. G., Woodward, J. A. & Randall, R. L. Estimating p-values for Mardia’s coefficients of multivariate skewness and kurtosis. Computational Statistics 17, 117–122 (2002).
Rosseel, Y. lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software 48, 1–36 (2012).
Cook, W. L. & Kenny, D. A. The Actor–Partner Interdependence Model: A model of bidirectional effects in developmental studies. International Journal of Behavioral Development 29, 101–109 (2005).
Testing Similarity Effects with Dyadic Response Surface Analysis - Felix D. Schönbrodt, Sarah Humberg, Steffen Nestler, 2018. https://journals.sagepub.com/doi/10.1002/per.2169.
Rosseel, Y. lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software 48, 1–36 (2012).
Zhang, J. & Tian, Y. Housework Division and Second-Child Fertility Anxiety among Couples in China: The Urban and Rural Differences. Int J Environ Res Public Health 16, 3910 (2019).
Kane, D. & Li, K. Fertility cultures and childbearing desire after the Two-Child Policy: evidence from southwest China. Journal of Family Studies 0, 1–19 (2021).
Kan, M.-Y. & Hertog, E. Domestic division of labour and fertility preference in China, Japan, South Korea, and Taiwan. Demographic Research S25, 557–588 (2017).
Yeo, T. E. D. & Chu, T. H. Social-cultural factors of HIV-related stigma among the Chinese general population in Hong Kong. AIDS Care 29, 1255–1259 (2017).
Nattabi, B., Li, J., Thompson, S. C., Orach, C. G. & Earnest, J. A Systematic Review of Factors Influencing Fertility Desires and Intentions Among People Living with HIV/AIDS: Implications for Policy and Service Delivery. AIDS Behav 13, 949–968 (2009).
Hashemzadeh, M., Shariati, M., Mohammad Nazari, A. & Keramat, A. Childbearing intention and its associated factors: A systematic review. Nurs Open 8, 2354–2368 (2021).
Diro, C. W. & Afework, M. F. Agreement and concordance between married couples regarding family planning utilization and fertility intention in Dukem, Ethiopia. BMC Public Health 13, 903 (2013).

No competing interests reported.

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Effects of (In)Congruency in Fertility Motivation on Fertility Desire and Intention Among Couples Living with HIV: A Dyadic Approach

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Abstract

Figures

Introduction

Traits-desires-intentions-behavior Framework

Congruence In Fertility Motivation Between Husband And Wife

Objective Of The Current Study

Materials And Methods

Study Design and Setting

Variables

Statistical Analysis

Results

Characteristics of Couples Living with HIV

Descriptive Statistics And Bivariate Correlation In Husband-wife Dyads

Dyadic Analysis

Frequencies Of Fertility Motivation Discrepancies And Congruence

Congruency And Incongruency In Fertility Motivation And Fertility Desire/intention

Discussion

Casual Pathway Of Fertility Motivation-desire-intention

Congruency And Congruency Of Fertility Motivation On Fertility Desire/intention In Wife-husband Dyads

Strengths And Limitations

Conclusions

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

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