Development and Validation of a Novel Culturally-Tailored Postpartum Depression Risk Scoring Scale (PDRS) in Malaysia: A Sequential Mixed-Methods Study

Development and Validation of a Novel Culturally-Tailored Postpartum Depression Risk Scoring Scale (PDRS) in Malaysia: A Sequential Mixed-Methods Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Development and Validation of a Novel Culturally-Tailored Postpartum Depression Risk Scoring Scale (PDRS) in Malaysia: A Sequential Mixed-Methods Study Amilia Afzan Mohd Jamil, Rania Alsabi, Rima Angrena Dasrilsyah, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7580820/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose Postpartum depression (PPD) still underdiagnosed in many multicultural societies due to the lack of culturally sensitive screening tools. Existing instruments often overlook sociocultural stressors specific to local contexts. This study aimed to develop and validate a Postpartum Depression Risk Scoring (PDRS) scale tailored to Malaysian women, addressing the multidimensional nature of PPD risk, to enable earlier detection. Adopting this scale within 24-hour postpartum screening procedures could facilitate prompt clinical interventions. Methods A sequential mixed-methods design was employed in three phases: (1) item generation from a systematic review and qualitative synthesis; (2) expert content validation; and (3) psychometric evaluation using Partial Least Squares Structural Equation Modeling (PLS-SEM) and Confirmatory Factor Analysis (CFA) on data from 300 postpartum women recruited from two public hospitals. Discriminant validity and criterion validity were also assessed. Results The initial 31-item pool was refined to a 15-item scale encompassing three domains: biological (CR = 0.700), psychological (CR = 0.851), and social (CR = 0.693). CFA confirmed acceptable model fit (χ² = 123.595; χ²/df = 1.67; SRMR = 0.077; NFI = 0.842). Discriminant validity was supported via the Fornell–Larcker criterion. ROC analysis yielded an optimal cutoff score of 15, with a sensitivity of 71.3%, specificity of 80.2%, and an AUC of 0.781 (95% CI: 0.742–0.820), demonstrating satisfactory predictive performance. Convergent validity analysis revealed a statistically significant positive association between the PDRS and the EPDS (Kendall’s τ_b = 0.226, P < .001), indicating higher EPDS scores correspond to elevated risk classification on the PDRS. Discussion The PDRS scale is a valid and reliable tool, which captures culturally relevant risk factors for PPD among Malaysian women. Its multidimensional structure reflects the biopsychosocial complexity of PPD and addresses gaps in traditional screening practices. The scale holds potential for early identification and prevention of PPD in diverse maternal health settings. Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Postpartum depression (PPD) is one of the most common complications following childbirth, with global prevalence estimates reaching 17.22% (Wang et al. 2021 ). It significantly affects maternal well-being, mother-infant bonding, and child development outcomes. In Malaysia, reported PPD rates vary widely, from 4.4% to 14.3%, depending on region, methodology, and measurement tools (Ahmad et al. 2018 ; Hairol et al. 2021 ). However, these figures may underrepresent the true burden due to underreporting, cultural stigma, and inconsistent screening practices. Despite the existence of validated instruments like the Edinburgh Postnatal Depression Scale (EPDS) (Cox et al. 1987 ) and the Postpartum Depression Screening Scale (PDSS) (Beck et al 2001), their effectiveness in multicultural settings remains contested. Studies in Malaysia report that while these tools have generally acceptable sensitivity and specificity, their performance may vary across ethnic groups and contexts (Asikin et al. 2019 ; Abdullah et al. 2019). Over-reliance on translated Western tools without adequate cultural adaptation risks misidentifying or overlooking women at risk. Furthermore, traditional postpartum practices, such as extended confinement, dietary taboos, and reliance on family support, vary across Malay, Chinese, and Indian communities (Fadzil et al. 2016 ), influencing how PPD symptoms are expressed and understood (Arifin et al. 2021 ). Cultural stigma around mental health continues to undermine help-seeking among postpartum women in Malaysia, notably those in rural or resource-limited areas (Ghani, 2018 ). PPD symptoms are confused with ordinary fatigue or explained through spiritual frameworks in many cases. As a result, care is often delayed or not pursued at all. Standard screening tools further complicate the issue. While widely used, they rarely capture relational or culturally specific stressors—such as familial conflict, pressure to breastfeed, or societal ideals around motherhood—that influence how women understand and report psychological symptoms (Jackson et al. 2021 ; Qi et al. 2021 ). These limitations highlight the need for a culturally grounded, risk-based screening tool that can identify vulnerable women before clinical symptoms emerge. Early identification enables timely support and may reduce the severity, duration, and long-term impact of PPD. The biopsychosocial model (Engel 1977 ) provides an ideal framework for understanding PPD as a multifactorial condition influenced by biological, psychological, and social determinants. This study aimed to develop and validate a Postpartum Depression Risk Scoring (PDRS) scale for Malaysian women using a sequential mixed-methods approach. The objectives were to evaluate the scale’s criterion validity against a standardized PPD measure and to assess its predictive accuracy in identifying PPD risk in a culturally diverse population. By addressing the limitations of existing tools and incorporating culturally specific risk factors, this study contributes to advancing equitable and early mental health care in maternal settings. MATERIALS AND METHODS Study Design This study employed a sequential mixed-methods design comprising three phases: (1) a systematic review and mixed-methods study to identify PPD risk factors, (2) the development of the Postpartum Depression Risk Scoring (PDRS) scale, and (3) the psychometric validation of the PDRS scale among Malaysian postpartum women. Phase 1: Identification of Risk Factors through Systematic Review A systematic review was conducted to synthesize evidence on PPD risk factors, informing the construction of the initial PDRS item pool. Studies were evaluated if they focused on the risk factors for PPD in Malaysian women aged 18 and above. Studies were also included if the word "postpartum depression" was used. Studies were excluded for prenatal or perinatal depression, if they were in press, conference proceedings, older than 2011, abstracts, or not written in English. The search terms specifically included: "postpartum" OR "postnatal" OR "childbirth" OR "after delivery" AND "depression" AND ("risk factors" OR "predictors" OR "determinants" OR "covariates" OR "exposure" OR "explanation") AND "Malaysia". There were no book, editorial, case study, or conference proceedings searches. The EPPI-Reviewer 4 gateway (Thomas et al. 2010 ) was used to sort possible related studies, look at the titles and abstracts of the papers that came up in the initial research, get rid of any duplicates, and make the first reports of the review. The search strategy followed PRISMA guidelines, utilizing databases such as PubMed, Scopus, Web of Science, and PsycINFO, covering studies published between January 2010 and December 2023. The detailed search approach for each database is outlined in Supplementary 1 file. Data were extracted regarding study design, sample characteristics, identified risk factors, and psychometric properties. The methodological quality of the included studies was assessed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklists for cross-sectional, cohort, and qualitative studies (Joanna Briggs Institute [JBI] 2017a, 2017b, 2017c). The search identified 8 studies via PRISMA-guided synthesis (Page et al. 2021 ). These studies guided the generation an initial pool of 31 items categorised into the three domains: biological, psychological, and social. Phase 2: Scale Development and Content Validation The initial PDRS draft underwent rigorous evaluation of face and content validity to ensure cultural and clinical relevance for the target population. Face validity was assessed by three experts in psychiatry and nursing. They assessed the ambiguity, importance, and difficulty of items evaluating PPD. Six experts in nursing, psychiatry, midwifery, family medicine, and Obstetrics/ Gynecology evaluated the content validity. The researcher evaluated the scale for fundamental modifications after collecting expert comments. Experts were asked to assess each item’s numeric content validity using a 4-point Likert scale ranging from 1 (not relevant) to 4 (very relevant). The authors incorporated the experts’ feedback to further refine the items, resulting in the second draft of the PDRS scale. According to the expert’s judgement, little modifications were necessary, as the majority concurred on the appropriateness of the questions. In this stage, none of the 31 items of the PDRS scale were deleted. Then, the evaluations were used to calculate the Content Validity Index (CVI), both at the item level (I-CVI) and the scale level (S-CVI). All analyses were conducted using Microsoft® Excel (Microsoft 2018). Phase 3: Psychometric Testing A pilot study was conducted using the prototype PDRS scale, and was administered to a sample of 30 postpartum women who had recently given birth in Hospital Serdang and Hospital Sultan Abdul Aziz Shah (HSAAS) so that the study could be tested. A second round of data collection was a cross-sectional sample of 300 postpartum women who were recruited from Hospital Serdang and HSAAS (response rate: 85%). Power analysis indicated 80% power to detect medium effect sizes (α = 0.05). Confirmatory Factor Analysis (CFA) refined the scale and validated construct validity. Partial Least Squares-Structural Equation Modeling (PLS-SEM), a robust alternative for small or non-normal datasets, was applied, as it requires no distributional assumptions or large samples (Ringle et al. 2022 ). Internal consistency reliability was evaluated using Composite Reliability (CR). The EPDS was used to test discriminant validity. The study used the Fornell-Larcker criterion (Fornell & Larcker 1981 ) and cross-loadings to make sure that the biological, psychological, and social risk factors on the new scale were conceptually different from the PPD symptoms on the EPDS. The CFA/PLS-SEM was analysed using SmartPLS V.4.0 ‎(Ringle et al. 2022 )‎. The PDRS scale’s sensitivity and specificity were evaluated using a Receiver Operating Characteristic (ROC) curve, which illustrated the model’s ability to balance true positive and false positive rates (Hanley & McNeil 1982 ; Zweig & Campbell 1993 ). The correlation between the PDRS and EPDS was evaluated using Kendall's Tau-b (τ_b) (Wilson 1969 ), which was chosen because it is robust to tied ranks and works well with ordinal data structures, such as the PDRS (binary scale) and EPDS (Likert scale). We used SPSS v30 (IBM 2023) computed two-tailed significance tests, 95% CIs, and correlation coefficients (Altman 1991 ). Values below 0.10 were interpreted as negligible association, 0.10–0.29 as weak, 0.30–0.49 as moderate, and ≥ 0.50 as strong. Ethical Considerations All procedures were performed in compliance with relevant laws and institutional guidelines and have been approved by the Ethics Committee of Universiti Putra Malaysia (Jawatankuasa Etika Universiti) under the reference number JKEUPM-2021-702. Eligible women were given an invitation letter to ask for the decision on whether to participate in this study. Once the agreement was gained, an interview session was arranged, and the consent forms were completed before conducting the interview. All information gathered from this study was strictly confidential and only to be used in this study RESULTS Results of Phase 1: Systematic Review and Risk Factor Identification A total of 1922 articles were retrieved from initial database searches. After removing duplicates and screening titles and abstracts, 79 full-text articles were assessed for eligibility. Ultimately, eight studies were included in the review (Fig. 1 ). The included studies encompassed both quantitative and qualitative designs and were conducted across diverse populations, including Malaysian postpartum women. Quality assessment using the Joanna Briggs Institute (JBI) tool indicated that most studies had moderate to high methodological quality (Supplementary 2). The systematic review revealed that risk factors for PPD among Malaysian women could be categorized into three major domains. These domains informed the construction of the initial 31-item pool for the Postpartum Depression Risk Scoring (PDRS) scale. The biological domain contained of 13 items, the psychological domain contained of 9 items, and the social domain contained of 9 items (Supplementary 3). To guarantee distinct elements for each domain, Churchill ( 1979 ) argued that encoded domains should be used in research. Results of Phase 2: Scale Development and Content Validation Face validity was supported by expert feedback, which affirmed the PDRS scale’s clarity, comprehensibility, and relevance to biological, psychological, and social experiences. The overall S-CVI of .90 indicated excellent scale-level content validity. Most items demonstrated acceptable CVR and I-CVI values, with particularly strong results in the behavioral factors category (Table 1 ). Minor modifications to wording were made based on expert feedback to enhance cultural and clinical appropriateness. Table 1 PDRS Item Pool with Domains, Codes, Item Statements, and Content Validity (I-CVI) Code Domain Item Statement No. of Agreements (n = 6) I-CVI BF1 Biological Previous history of depression or untreated mental illness 6 1.00 BF2 Biological Depression or mental illness during current pregnancy 6 1.00 BF3 Biological Family history of depression 6 1.00 BF4 Biological Obstetric complications (e.g., pre-eclampsia, GDM) 6 1.00 BF5 Biological Traumatic or prolonged birth experience 6 1.00 BF6 Biological Postpartum complications 4 0.67 BF7 Biological Baby health problems 4 0.67 BF8 Biological Pre-existing conditions (e.g., thyroid dysfunction, anemia) 5 0.83 BF9 Biological Postpartum sleep disturbance 6 1.00 BF10 Biological Breastfeeding difficulties 6 1.00 BF11 Biological Not intending to breastfeed 6 1.00 BF12 Biological Unplanned pregnancy 6 1.00 BF13 Biological Physical changes and fatigue 6 1.00 PSF1 Psychological Persistent worry about baby care 5 0.83 PSF2 Psychological Negative thoughts about motherhood or pregnancy 4 0.67 PSF3 Psychological Feelings of isolation and loneliness 6 1.00 PSF4 Psychological Negative body image 6 1.00 PSF5 Psychological Low or lack of self-esteem 5 0.83 PSF6 Psychological Loss of control since becoming a mother 4 0.67 PSF7 Psychological Stressful life events during pregnancy (e.g., job loss, bereavement) 5 0.83 PSF8 Psychological Recent partner physical abuse 5 0.83 PSF9 Psychological Recent partner emotional abuse 6 1.00 SOF1 Social Cultural pressure (e.g., breastfeeding, caregiving expectations) 5 0.83 SOF2 Social Expected to cope without showing distress 6 1.00 SOF3 Social Conflicts with husband about parenting or household responsibilities 5 0.83 SOF4 Social Lack of family support during confinement 4 0.67 SOF5 Social Conflict with in-laws or extended family 6 1.00 SOF6 Social Dissatisfaction with marital relationship 6 1.00 SOF7 Social Shame or reluctance to seek help for depressive symptoms 6 1.00 SOF8 Social Partner substance abuse or alcoholism 5 0.83 SOF9 Social Low income or financial burden 6 1.00 Scale-Level CVI (S-CVI) 0.903 Table 1 . PDRS Item Pool with Domains, Codes, Item Statements, and Content Validity (I-CVI) Results of Phase 3: Psychometric Validation Pilot Study The validated PDRS scale was piloted with 30 postpartum women from two Malaysian public hospitals. Participants found the scale clear and easy to complete. As no issues were reported, the same version was used for the main data collection. Demographic Characteristics Of the 300 postpartum women surveyed, the majority were aged 25–34 years (68.3%), married (99.0%), and of Malay ethnicity (84.0%). Most had attained at least secondary education, and 38.67% identified as housewives. More than half reported a monthly household income below MYR 3,000. Clinically, 92.67% were first-time mothers, and 85.0% delivered at term (37–40 weeks of gestation). Normal vaginal delivery was the most common mode (53.67%), and 29.33% of newborns required NICU admission. Stillbirth and early neonatal death were rare. (Table 2 ). Table 2 Sociodemographic and Clinical Characteristics of Participants (N = 300) Variable Category Frequency (n) Percentage (%) Age 17–24 years 32 10.7 25–34 years 205 68.3 35–43 years 60 20.0 ≥ 44 years 3 1.0 Marital Status Married 297 99.0 Single 2 0.67 Divorced 1 0.33 Race Malay 252 84.0 Indian 17 5.67 Chinese 16 5.33 Others 15 5.0 Education Primary 14 4.67 Secondary 119 39.67 Diploma 72 24.0 Degree 83 27.67 Masters/PhD 12 4.0 Partner Education Primary 10 3.33 Secondary 136 45.3 Diploma 64 21.3 Degree 81 27.0 Masters/PhD 9 3.0 Occupation Housewife 116 38.67 Private 112 37.33 Public 36 12.0 Self-employed 15 5.0 Others 18 6.0 Student 3 1.0 Household Income MYR 6000 73 24.33 Health Risks None 152 50.67 Diabetes Mellitus 106 35.33 Hypertension 14 4.67 Thyroid 4 1.33 Others 22 7.33 Anxiety 1 0.33 Depression 1 0.33 Gestational Age 40 weeks 19 6.33 Newborn Outcome Discharge to home 209 69.67 Admitted to NICU 88 29.33 Stillbirth 2 0.67 Early neonatal death 1 0.33 Parity 0 children 278 92.67 1–4 children 21 7.0 ≥ 5 children 1 0.33 Mode of Delivery Normal Vaginal Delivery 161 53.67 Cesarean Section 124 41.33 Instrumental Delivery 15 5.0 Table 2 . Sociodemographic and Clinical Characteristics of Participants (N = 300) Confirmatory Factor Analysis/PLS-SEM PLS-SEM analysis showed that several items in the initial model had factor loadings below the 0.4 threshold, reducing construct reliability across the biological, psychological, and social domains. Specifically, items such as BF3, PSF1, PSF7–PSF9, and SOF2, SOF6, SOF8–SOF9 underperformed, prompting the removal of 16 items. The revised PDRS scale was refined to 15 items, forming a three-factor structure aligned with the core domains (Table 3 , Fig. 2). Table 3 Cross Loadings and Composite Reliability of PDRS Items by Domain Domain Item Code Cross Loading CR P Biological 0.700 0.000 BF1 0.341 BF2 0.407 BF9 0.573 BF12 0.779 BF13 0.791 Psychological 0.851 0.000 PSF2 0.753 PSF3 0.667 PSF4 0.794 PSF5 0.841 PSF6 0.582 Social 0.693 0.000 SOF3 0.542 SOF4 0.508 SOF5 0.407 SOF7 0.602 Note: CR: Composite Reliability; P : P-value Table 3. Cross Loadings and Composite Reliability of PDRS Items by Domain The biological construct had a moderate level of internal consistency, as shown in Table 4 . Its composite reliability (CR) was 0.700 (P < 0.001), which was above the acceptable level. The psychological construct exhibited the highest significant reliability among the three domains, with a CR of 0.851 ( P < 0.001), exceeding the recommended benchmark. The social construct showed marginal reliability, with a CR of 0.693, slightly below the conventional threshold of 0.70. Nonetheless, the p -value remained statistically significant (< .001), indicating consistent measurement across items. Table 4 Discriminant Validity Assessment of the PDRS Scale Fornell-Larcker Criterion* Biological Psychological Social Biological 0.581 Psychological 0.529 0.733 Social 0.345 0.524 0.564 Notes: Diagonal elements (bold) represent the square root of the Average Variance Extracted (AVE) for each construct. Off-diagonal values indicate inter-construct correlations. Discriminant validity is supported when the square root of AVE exceeds correlations with other constructs. Model fit was supported by a low but statistically significant chi-square value (χ² = 123.595) and an acceptable normed chi-square (χ²/df = 1.67). The SRMR value of 0.077 indicated minimal residual variance. Additional fit indices, d_ULS = 1.284 and d_G = 0.276, confirmed low discrepancies between observed and model-implied matrices. The NFI of 0.842 reflected a moderate yet acceptable fit for exploratory validation. Discriminant validity was confirmed using the Fornell–Larcker criterion, as each construct’s square root of AVE—biological (0.581), psychological (0.733), and social (0.564)—exceeded its inter-construct correlations (Table 4 ). Cross-loading analysis further supported this, with all items loading higher on their respective constructs than on others. Table 4 . Discriminant Validity Assessment of the PDRS Scale ROC Curve Analysis ROC analysis identified an optimal cutoff score of 15 for the PDRS, with a sensitivity of 71.3% and specificity of 80.2%, resulting in a Youden’s index of 0.515. The area under the curve (AUC = 0.781; 95% CI: 0.742–0.820) indicated good discriminatory ability. These results reflect a well-balanced diagnostic performance, effectively minimizing false positives and negatives in clinical screening (Fig. 3 ). Kendall’s Tau-B Correlation Analysis A statistically significant positive association emerged between the EPDS and PDSS (Kendall’s τ_b = 0.226, P < .001, 95% CI: 0.153, 0.296), indicating that higher EPDS scores modestly predict classification as high-risk (≥ 8) on the PDRS. The weak correlation magnitude (τ_b ≈ 0.23) reflects limited shared variance, attributed to the PDRS’s broader construct (risk vulnerability) versus the EPDS’s (affective symptoms). This divergence confirms these instruments measure distinct but related aspects of PPD, excluding interchangeable use. DISCUSSION This study provided strong empirical support for the validity and reliability of the PDRS scale, confirming its three-factor structure encompassing biological, psychological, and social risk domains. Grounded in the biopsychosocial framework, the model reflects the complex and multidimensional nature of postpartum depression. These findings underlined that PPD risk arises from an interplay of physiological, emotional, and social factors, elements often underrepresented in traditional symptom-based screening tools, underscoring the need for more holistic and culturally sensitive approaches to early detection. Biological Risk Factors A history of mental illness remained one of the most consistent predictors of PPD, as highlighted by Liu et al. ( 2020 ), Shorey et al. ( 2021 ), and Usmani et al. ( 2021 ). Zhao and Zhang ( 2020 ) reinforced this with a meta-analysis reporting a pooled OR of 3.71 (95% CI: 2.46–5.60, p < .001), emphasising the need for routine antenatal mental health screening. Sleep disturbances were also significant, with studies by Mohd Shukri et al. ( 2022 ) and Zhao and Zhang ( 2020 ) underscoring the role of sleep deprivation in emotional dysregulation. Unplanned pregnancy was another notable risk factor, associated with increased stress and lower coping capacity (Arifin et al. 2014 ; Salsabilla et al. 2020 ; Muskens et al. 2022 ; Usmani et al. 2021 ). Additionally, postpartum fatigue and body dissatisfaction contributed to depressive symptoms, as documented by Javaid et al. (2022), Asadi et al. ( 2021 ), Dimcea et al. ( 2024 ), and Day ( 2023 ), supporting the need for postpartum care that addresses both physical and emotional recovery. Psychological Risk Factors Negative thoughts and self-doubt during pregnancy were consistently linked to an increased risk of PPD, particularly when tied to maternal identity and parenting concerns (Araji et al. 2020 ; Najid et al. 2023 ). Pregnancy-related anxiety also emerged as a strong predictor, as noted by Qi et al. ( 2021 ), although cultural variability in its impact was observed (Hutchens & Kearney 2020 ). Emotional isolation and lack of support were recurrent psychological stressors, with studies reporting their strong association with depressive symptoms (Qi et al. 2021 ; Smorti et al. 2019; Hairol et al. 2021 ), while Agrawal et al. (2022) described how anxiety and isolation may interact to worsen outcomes. Although social support can mitigate these risks (Hutchens & Kearney 2020 ), its effectiveness may vary across contexts (Alsabi et al. 2022 ). Body image dissatisfaction was another key contributor, with women reporting psychological distress linked to physical changes after childbirth (Najid et al. 2023 ; Ryan et al. 2022 ; Pehlivan et al. 2022 ). While Qi et al. ( 2021 ) confirmed a strong correlation, other studies noted more variable outcomes depending on demographic or cultural factors (Agrawal et al. 2022; Hairol et al. 2021 ). Low self-esteem and perceived loss of control also played a significant role in PPD vulnerability (Najid et al. 2023 ; Qi et al. 2021 ), particularly as new mothers navigated shifting identities and responsibilities (Wigert et al. 2020 ; Watson et al. 2021 ). These findings were supported by Liu et al. ( 2020 ) and Saharoy et al. ( 2023 ), though individual resilience and social support may moderate these effects (Hutchens & Kearney 2020 ; Tang et al. 2021 ; Yu et al. 2021 ). Social Risk Factors Cultural expectations, including traditional confinement practices and the pressure to breastfeed, were found to contribute to stress, isolation, and emotional strain (Fadzil et al. 2016 ; Haque & Malebranche 2020 ; Jackson et al. 2021 ). Although some practices, such as religious coping, were protective for certain groups (Chow et al. 2024; Sampson et al. 2021 ), others, particularly when rigid or unsupported, heightened psychological vulnerability (Makama et al. 2021 ; Saharoy et al. 2023 ). Marital conflict and lack of spousal support were consistently associated with increased PPD symptoms, especially when coupled with traditional gender roles or limited healthcare access (Smorti et al. 2019; Hutchens & Kearney 2020 ; Chu & Moore 2020 ). Similarly, insufficient family support during the confinement period was linked to emotional exhaustion and depressive symptoms (Najid et al. 2023 ; Hairol et al. 2021 ; Qi et al. 2021 ), with the quality of support being more impactful than its presence alone (Agrawal et al. 2022; Pehlivan et al. 2022 ). Conflicts with in-laws or extended family members further increased emotional distress, particularly in collectivist cultures where such relationships are central to postpartum care (Shorey et al. 2021 ; Chen et al. 2023 ). Finally, cultural ideals of ideal motherhood and fear of judgment frequently cause shame and stigma surrounding depressive symptoms to delay seeking help (Jackson et al. 2024 ; De Jesus et al. 2024 ; Zhao & Zhang 2020 ). These effects were moderated by education, social support, and access to care (Ryan et al. 2022 ; Hutchens & Kearney 2020 ). Scale Validation The study’s findings partially supported the proposed hypothesis, with all three domains, biological, psychological, and social, demonstrating statistically significant reliability and criterion validity. The psychological domain had the highest internal consistency (CR = 0.851), aligning with literature on the predictive role of emotional and cognitive stressors in PPD (Tatevosyan 2024 ; Huiju et al. 2025). The biological domain also met acceptable reliability standards (CR = 0.700), reflecting established links with hormonal and medical risk factors (Yang et al. 2022 ; Munk-Olsen et al. 2022 ). Although the social domain showed slightly lower reliability (CR = 0.693), it remained valid, likely reflecting the cultural variability of social support and stressors (English et al. 2018 ; Bjertrup et al. 2023 ). The final 15-item scale was reduced from an initial 31-item pool through expert review and CFA, confirming construct validity and reducing redundancy. Discriminant validity was established; unlike other tools limited to content validation (Johansson et al. 2020 ; Lee et al. 2020 ), the PDRS underwent a comprehensive, culturally sensitive validation process. Conclusion The validated PDRS scale reflected its findings by incorporating culturally relevant, evidence-based items that capture both individual and contextual risks. This multidomain approach offers a more holistic framework for early identification and intervention, supporting the need for preventive screening strategies that extend beyond symptom-based models like the EPDS. Implications of the Study Theoretically, the validated Postpartum Depression Risk Scoring (PDRS) scale addressed a critical gap in culturally relevant, risk-based screening tools for PPD. Grounded in the biopsychosocial model, the scale integrated psychological, biological, and social predictors, reflecting the complexity of maternal experiences in the Malaysian context. The psychological domain, in particular, demonstrated strong internal consistency, while the biological and social domains provided additional layers of risk insight. By incorporating factors such as family conflict, cultural pressures, and stigma-related help-seeking hesitancy, the scale responded to sociocultural dimensions often overlooked in global instruments. In clinical practice, the PDRS presents a feasible and targeted screening tool for early identification of at-risk mothers, particularly in maternal and child health settings. It facilitates proactive intervention before symptom escalation, aligning with public health goals for preventive mental health care. Moreover, the findings support the need for culturally sensitive public health initiatives, including anti-stigma campaigns, caregiver training, and family-centered support during the postpartum period. Limitations Several limitations must be considered. The study was based on a secondary systematic review and cross-sectional data from 300 respondents, which may limit generalizability. The slightly lower reliability of the social domain suggests the need for item refinement, especially to capture diverse cultural and relational contexts. The absence of longitudinal data restricts conclusions about the scale’s predictive validity over time. Future research should focus on extending validation to other Southeast Asian populations and exploring the scale’s performance in longitudinal and clinical applications. Comparative studies with established tools can assess their distinct utility, while qualitative research may deepen understanding of culturally embedded risk factors. Iterative refinement based on user feedback will enhance the scale’s sensitivity and applicability. Ultimately, the PDRS provides a foundation for improving culturally responsive maternal mental health screening and policy in Malaysia and similar multicultural settings. Declarations CRediT Author Statement RS: Conceptualization; Methodology; Software; Validation; Roles/Writing - original draft; Writing; Data curation; Investigation and Formal analysis. AA: Project administration; Resources and Funding acquisition , AA, RAD, ASBA & RRD : Reviewing, Visualization, Conflict of Interest Statements The authors declare that they have no competing interests. Role of Funding Source This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. References Ahmad N, Silim U, Rosman A, Mohamed M, Chan YY, Kasim N, et al. (2018) Postnatal depression and intimate partner violence: a nationwide clinic-based cross-sectional study in Malaysia. BMJ Open 8(5):e020649. doi:10.1136/bmjopen-2017-020649. 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13:50:07","extension":"xml","order_by":25,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":169815,"visible":true,"origin":"","legend":"","description":"","filename":"3bfb35b8ce324a47885aabc0a5ef679c1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7580820/v1/1ed0e0f19ab1cc39a6b422c3.xml"},{"id":93406604,"identity":"cd133c01-32e4-4ca5-9675-f42b6696c761","added_by":"auto","created_at":"2025-10-13 13:50:07","extension":"html","order_by":26,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":179412,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7580820/v1/a319f605ff997b031b2ab697.html"},{"id":93406573,"identity":"15329dc8-cb46-48fe-b664-875315bc553c","added_by":"auto","created_at":"2025-10-13 13:50:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":271941,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA 2020 Flow Diagram of the Literature Screening Process.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e(Source: Page et al., 2021).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7580820/v1/5c15dfdcecd99647f28d3ce9.png"},{"id":93407920,"identity":"46b728e5-acbd-4a09-8d3e-d3d4c4ef40d9","added_by":"auto","created_at":"2025-10-13 14:06:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":179514,"visible":true,"origin":"","legend":"\u003cp\u003eFinal PLS-SEM Model with Factor Loadings and Path Coefficients.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7580820/v1/72b164ec8c43de43b910d4d9.png"},{"id":93407536,"identity":"612e87db-ccf1-4694-a9ec-b43d55bce9ad","added_by":"auto","created_at":"2025-10-13 13:58:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":103836,"visible":true,"origin":"","legend":"\u003cp\u003eROC Curve of PPDRS Scores.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7580820/v1/73cb143e5921edeafb2599dd.png"},{"id":105832479,"identity":"cd992412-9ff1-4497-913b-72f038e49ef3","added_by":"auto","created_at":"2026-03-31 14:57:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1790312,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7580820/v1/c3f4c634-7a45-4d1b-87f3-f2ecf898cdd3.pdf"},{"id":93407537,"identity":"e40f9bd4-7c79-483b-8e9e-0290908df63e","added_by":"auto","created_at":"2025-10-13 13:58:06","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16325,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7580820/v1/2bfc7044cef237dde61558c9.docx"},{"id":93406575,"identity":"3a89a741-4913-4a2e-a3e9-33c9c8d59bd6","added_by":"auto","created_at":"2025-10-13 13:50:06","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":22862,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary2.docx","url":"https://assets-eu.researchsquare.com/files/rs-7580820/v1/6a10b610e0dfef8a0b672ec4.docx"},{"id":93406579,"identity":"b22d4633-789e-486d-9237-2e27f5aab469","added_by":"auto","created_at":"2025-10-13 13:50:06","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":24126,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary3.docx","url":"https://assets-eu.researchsquare.com/files/rs-7580820/v1/60612a536b4c8da833972bda.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Development and Validation of a Novel Culturally-Tailored Postpartum Depression Risk Scoring Scale (PDRS) in Malaysia: A Sequential Mixed-Methods Study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003ePostpartum depression (PPD) is one of the most common complications following childbirth, with global prevalence estimates reaching 17.22% (Wang et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). It significantly affects maternal well-being, mother-infant bonding, and child development outcomes. In Malaysia, reported PPD rates vary widely, from 4.4% to 14.3%, depending on region, methodology, and measurement tools (Ahmad et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Hairol et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, these figures may underrepresent the true burden due to underreporting, cultural stigma, and inconsistent screening practices.\u003c/p\u003e\u003cp\u003eDespite the existence of validated instruments like the Edinburgh Postnatal Depression Scale (EPDS) (Cox et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1987\u003c/span\u003e) and the Postpartum Depression Screening Scale (PDSS) (Beck et al 2001), their effectiveness in multicultural settings remains contested. Studies in Malaysia report that while these tools have generally acceptable sensitivity and specificity, their performance may vary across ethnic groups and contexts (Asikin et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Abdullah et al. 2019). Over-reliance on translated Western tools without adequate cultural adaptation risks misidentifying or overlooking women at risk. Furthermore, traditional postpartum practices, such as extended confinement, dietary taboos, and reliance on family support, vary across Malay, Chinese, and Indian communities (Fadzil et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), influencing how PPD symptoms are expressed and understood (Arifin et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCultural stigma around mental health continues to undermine help-seeking among postpartum women in Malaysia, notably those in rural or resource-limited areas (Ghani, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). PPD symptoms are confused with ordinary fatigue or explained through spiritual frameworks in many cases. As a result, care is often delayed or not pursued at all. Standard screening tools further complicate the issue. While widely used, they rarely capture relational or culturally specific stressors\u0026mdash;such as familial conflict, pressure to breastfeed, or societal ideals around motherhood\u0026mdash;that influence how women understand and report psychological symptoms (Jackson et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Qi et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThese limitations highlight the need for a culturally grounded, risk-based screening tool that can identify vulnerable women before clinical symptoms emerge. Early identification enables timely support and may reduce the severity, duration, and long-term impact of PPD. The biopsychosocial model (Engel \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1977\u003c/span\u003e) provides an ideal framework for understanding PPD as a multifactorial condition influenced by biological, psychological, and social determinants.\u003c/p\u003e\u003cp\u003eThis study aimed to develop and validate a Postpartum Depression Risk Scoring (PDRS) scale for Malaysian women using a sequential mixed-methods approach. The objectives were to evaluate the scale\u0026rsquo;s criterion validity against a standardized PPD measure and to assess its predictive accuracy in identifying PPD risk in a culturally diverse population. By addressing the limitations of existing tools and incorporating culturally specific risk factors, this study contributes to advancing equitable and early mental health care in maternal settings.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design\u003c/h2\u003e\u003cp\u003eThis study employed a sequential mixed-methods design comprising three phases: (1) a systematic review and mixed-methods study to identify PPD risk factors, (2) the development of the Postpartum Depression Risk Scoring (PDRS) scale, and (3) the psychometric validation of the PDRS scale among Malaysian postpartum women.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003ePhase 1: Identification of Risk Factors through Systematic Review\u003c/h3\u003e\n\u003cp\u003eA systematic review was conducted to synthesize evidence on PPD risk factors, informing the construction of the initial PDRS item pool. Studies were evaluated if they focused on the risk factors for PPD in Malaysian women aged 18 and above. Studies were also included if the word \"postpartum depression\" was used. Studies were excluded for prenatal or perinatal depression, if they were in press, conference proceedings, older than 2011, abstracts, or not written in English. The search terms specifically included: \"postpartum\" OR \"postnatal\" OR \"childbirth\" OR \"after delivery\" AND \"depression\" AND (\"risk factors\" OR \"predictors\" OR \"determinants\" OR \"covariates\" OR \"exposure\" OR \"explanation\") AND \"Malaysia\". There were no book, editorial, case study, or conference proceedings searches.\u003c/p\u003e\u003cp\u003eThe EPPI-Reviewer 4 gateway (Thomas et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) was used to sort possible related studies, look at the titles and abstracts of the papers that came up in the initial research, get rid of any duplicates, and make the first reports of the review. The search strategy followed PRISMA guidelines, utilizing databases such as PubMed, Scopus, Web of Science, and PsycINFO, covering studies published between January 2010 and December 2023. The detailed search approach for each database is outlined in Supplementary 1 file.\u003c/p\u003e\u003cp\u003eData were extracted regarding study design, sample characteristics, identified risk factors, and psychometric properties. The methodological quality of the included studies was assessed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklists for cross-sectional, cohort, and qualitative studies (Joanna Briggs Institute [JBI] 2017a, 2017b, 2017c). The search identified 8 studies via PRISMA-guided synthesis (Page et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These studies guided the generation an initial pool of 31 items categorised into the three domains: biological, psychological, and social.\u003c/p\u003e\n\u003ch3\u003ePhase 2: Scale Development and Content Validation\u003c/h3\u003e\n\u003cp\u003eThe initial PDRS draft underwent rigorous evaluation of face and content validity to ensure cultural and clinical relevance for the target population. Face validity was assessed by three experts in psychiatry and nursing. They assessed the ambiguity, importance, and difficulty of items evaluating PPD.\u003c/p\u003e\u003cp\u003eSix experts in nursing, psychiatry, midwifery, family medicine, and Obstetrics/ Gynecology evaluated the content validity. The researcher evaluated the scale for fundamental modifications after collecting expert comments. Experts were asked to assess each item\u0026rsquo;s numeric content validity using a 4-point Likert scale ranging from 1 (not relevant) to 4 (very relevant). The authors incorporated the experts\u0026rsquo; feedback to further refine the items, resulting in the second draft of the PDRS scale. According to the expert\u0026rsquo;s judgement, little modifications were necessary, as the majority concurred on the appropriateness of the questions. In this stage, none of the 31 items of the PDRS scale were deleted. Then, the evaluations were used to calculate the Content Validity Index (CVI), both at the item level (I-CVI) and the scale level (S-CVI). All analyses were conducted using Microsoft\u0026reg; Excel (Microsoft 2018).\u003c/p\u003e\n\u003ch3\u003ePhase 3: Psychometric Testing\u003c/h3\u003e\n\u003cp\u003eA pilot study was conducted using the prototype PDRS scale, and was administered to a sample of 30 postpartum women who had recently given birth in Hospital Serdang and Hospital Sultan Abdul Aziz Shah (HSAAS) so that the study could be tested.\u003c/p\u003e\u003cp\u003eA second round of data collection was a cross-sectional sample of 300 postpartum women who were recruited from Hospital Serdang and HSAAS (response rate: 85%). Power analysis indicated 80% power to detect medium effect sizes (α\u0026thinsp;=\u0026thinsp;0.05). Confirmatory Factor Analysis (CFA) refined the scale and validated construct validity. Partial Least Squares-Structural Equation Modeling (PLS-SEM), a robust alternative for small or non-normal datasets, was applied, as it requires no distributional assumptions or large samples (Ringle et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Internal consistency reliability was evaluated using Composite Reliability (CR).\u003c/p\u003e\u003cp\u003eThe EPDS was used to test discriminant validity. The study used the Fornell-Larcker criterion (Fornell \u0026amp; Larcker \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1981\u003c/span\u003e) and cross-loadings to make sure that the biological, psychological, and social risk factors on the new scale were conceptually different from the PPD symptoms on the EPDS. The CFA/PLS-SEM was analysed using SmartPLS V.4.0 \u0026lrm;(Ringle et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u0026lrm;.\u003c/p\u003e\u003cp\u003eThe PDRS scale\u0026rsquo;s sensitivity and specificity were evaluated using a Receiver Operating Characteristic (ROC) curve, which illustrated the model\u0026rsquo;s ability to balance true positive and false positive rates (Hanley \u0026amp; McNeil \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1982\u003c/span\u003e; Zweig \u0026amp; Campbell \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). The correlation between the PDRS and EPDS was evaluated using Kendall's Tau-b (τ_b) (Wilson \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e1969\u003c/span\u003e), which was chosen because it is robust to tied ranks and works well with ordinal data structures, such as the PDRS (binary scale) and EPDS (Likert scale). We used SPSS v30 (IBM 2023) computed two-tailed significance tests, 95% CIs, and correlation coefficients (Altman \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). Values below 0.10 were interpreted as negligible association, 0.10\u0026ndash;0.29 as weak, 0.30\u0026ndash;0.49 as moderate, and \u0026ge;\u0026thinsp;0.50 as strong.\u003c/p\u003e\n\u003ch3\u003eEthical Considerations\u003c/h3\u003e\n\u003cp\u003e All procedures were performed in compliance with relevant laws and institutional guidelines and have been approved by the Ethics Committee of Universiti Putra Malaysia (Jawatankuasa Etika Universiti) under the reference number JKEUPM-2021-702. Eligible women were given an invitation letter to ask for the decision on whether to participate in this study. Once the agreement was gained, an interview session was arranged, and the consent forms were completed before conducting the interview. All information gathered from this study was strictly confidential and only to be used in this study\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003eResults of Phase 1: Systematic Review and Risk Factor Identification\u003c/h2\u003e\n \u003cp\u003eA total of 1922 articles were retrieved from initial database searches. After removing duplicates and screening titles and abstracts, 79 full-text articles were assessed for eligibility. Ultimately, eight studies were included in the review (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). The included studies encompassed both quantitative and qualitative designs and were conducted across diverse populations, including Malaysian postpartum women. Quality assessment using the Joanna Briggs Institute (JBI) tool indicated that most studies had moderate to high methodological quality (Supplementary 2).\u003c/p\u003e\n \u003cp\u003eThe systematic review revealed that risk factors for PPD among Malaysian women could be categorized into three major domains. These domains informed the construction of the initial 31-item pool for the Postpartum Depression Risk Scoring (PDRS) scale. The biological domain contained of 13 items, the psychological domain contained of 9 items, and the social domain contained of 9 items (Supplementary 3). To guarantee distinct elements for each domain, Churchill (\u003cspan class=\"CitationRef\"\u003e1979\u003c/span\u003e) argued that encoded domains should be used in research.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eResults of Phase 2: Scale Development and Content Validation\u003c/h3\u003e\n\u003cp\u003eFace validity was supported by expert feedback, which affirmed the PDRS scale\u0026rsquo;s clarity, comprehensibility, and relevance to biological, psychological, and social experiences. The overall S-CVI of .90 indicated excellent scale-level content validity. Most items demonstrated acceptable CVR and I-CVI values, with particularly strong results in the behavioral factors category (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Minor modifications to wording were made based on expert feedback to enhance cultural and clinical appropriateness.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePDRS Item Pool with Domains, Codes, Item Statements, and Content Validity (I-CVI)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCode\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDomain\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eItem Statement\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo. of Agreements (n\u0026thinsp;=\u0026thinsp;6)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eI-CVI\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBF1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevious history of depression or untreated mental illness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBF2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDepression or mental illness during current pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBF3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFamily history of depression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBF4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eObstetric complications (e.g., pre-eclampsia, GDM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBF5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTraumatic or prolonged birth experience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBF6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePostpartum complications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBF7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBaby health problems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBF8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePre-existing conditions (e.g., thyroid dysfunction, anemia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBF9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePostpartum sleep disturbance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBF10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBreastfeeding difficulties\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBF11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot intending to breastfeed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBF12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnplanned pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBF13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysical changes and fatigue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePSF1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePersistent worry about baby care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePSF2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNegative thoughts about motherhood or pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePSF3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFeelings of isolation and loneliness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePSF4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNegative body image\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePSF5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow or lack of self-esteem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePSF6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLoss of control since becoming a mother\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePSF7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStressful life events during pregnancy (e.g., job loss, bereavement)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePSF8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRecent partner physical abuse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePSF9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRecent partner emotional abuse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSOF1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCultural pressure (e.g., breastfeeding, caregiving expectations)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSOF2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExpected to cope without showing distress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSOF3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConflicts with husband about parenting or household responsibilities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSOF4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLack of family support during confinement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSOF5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConflict with in-laws or extended family\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSOF6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDissatisfaction with marital relationship\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSOF7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eShame or reluctance to seek help for depressive symptoms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSOF8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePartner substance abuse or alcoholism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSOF9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow income or financial burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eScale-Level CVI (S-CVI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.903\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. PDRS Item Pool with Domains, Codes, Item Statements, and Content Validity (I-CVI)\u003c/p\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eResults of Phase 3: Psychometric Validation\u003c/h2\u003e\n \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\n \u003ch2\u003ePilot Study\u003c/h2\u003e\n \u003cp\u003eThe validated PDRS scale was piloted with 30 postpartum women from two Malaysian public hospitals. Participants found the scale clear and easy to complete. As no issues were reported, the same version was used for the main data collection.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eDemographic Characteristics\u003c/h2\u003e\n \u003cp\u003eOf the 300 postpartum women surveyed, the majority were aged 25\u0026ndash;34 years (68.3%), married (99.0%), and of Malay ethnicity (84.0%). Most had attained at least secondary education, and 38.67% identified as housewives. More than half reported a monthly household income below MYR 3,000. Clinically, 92.67% were first-time mothers, and 85.0% delivered at term (37\u0026ndash;40 weeks of gestation). Normal vaginal delivery was the most common mode (53.67%), and 29.33% of newborns required NICU admission. Stillbirth and early neonatal death were rare. (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSociodemographic and Clinical Characteristics of Participants (N\u0026thinsp;=\u0026thinsp;300)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFrequency (n)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePercentage (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u0026ndash;24 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026ndash;34 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e205\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e68.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u0026ndash;43 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;44 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e99.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMalay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e252\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e84.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIndian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChinese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiploma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDegree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMasters/PhD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePartner Education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiploma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDegree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMasters/PhD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHousewife\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrivate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePublic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSelf-employed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHousehold Income\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt; MYR 1500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMYR 1501\u0026ndash;3000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMYR 3001\u0026ndash;4500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMYR 4501\u0026ndash;6000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;MYR 6000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealth Risks\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiabetes Mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyroid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGestational Age\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;30 weeks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u0026ndash;36 weeks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u0026ndash;40 weeks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e85.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;40 weeks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNewborn Outcome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDischarge to home\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e69.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdmitted to NICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStillbirth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEarly neonatal death\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eParity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 children\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e92.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;4 children\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;5 children\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMode of Delivery\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal Vaginal Delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCesarean Section\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e41.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInstrumental Delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. Sociodemographic and Clinical Characteristics of Participants (N\u0026thinsp;=\u0026thinsp;300)\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eConfirmatory Factor Analysis/PLS-SEM\u003c/h2\u003e\n \u003cp\u003ePLS-SEM analysis showed that several items in the initial model had factor loadings below the 0.4 threshold, reducing construct reliability across the biological, psychological, and social domains. Specifically, items such as BF3, PSF1, PSF7\u0026ndash;PSF9, and SOF2, SOF6, SOF8\u0026ndash;SOF9 underperformed, prompting the removal of 16 items. The revised PDRS scale was refined to 15 items, forming a three-factor structure aligned with the core domains (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, Fig. 2).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCross Loadings and Composite Reliability of PDRS Items by Domain\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDomain\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eItem Code\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCross Loading\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBiological\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBF1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.341\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBF2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.407\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBF9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.573\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBF12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.779\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBF13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePsychological\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.851\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePSF2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.753\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePSF3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePSF4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.794\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePSF5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.841\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePSF6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.582\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocial\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.693\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSOF3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSOF4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.508\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSOF5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.407\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSOF7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.602\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eNote: CR: Composite Reliability; \u003cem\u003eP\u003c/em\u003e: P-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Cross Loadings and Composite Reliability of PDRS Items by Domain\u003c/p\u003e\n \u003cp\u003eThe biological construct had a moderate level of internal consistency, as shown in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. Its composite reliability (CR) was 0.700 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), which was above the acceptable level. The psychological construct exhibited the highest significant reliability among the three domains, with a CR of 0.851 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), exceeding the recommended benchmark. The social construct showed marginal reliability, with a CR of 0.693, slightly below the conventional threshold of 0.70. Nonetheless, the \u003cem\u003ep\u003c/em\u003e-value remained statistically significant (\u0026lt;\u0026thinsp;.001), indicating consistent measurement across items.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDiscriminant Validity Assessment of the PDRS Scale Fornell-Larcker Criterion*\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBiological\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePsychological\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSocial\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBiological\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e0.581\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePsychological\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.529\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.733\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocial\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.345\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.524\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.564\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eNotes: Diagonal elements (bold) represent the square root of the Average Variance Extracted (AVE) for each construct. Off-diagonal values indicate inter-construct correlations. Discriminant validity is supported when the square root of AVE exceeds correlations with other constructs.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eModel fit was supported by a low but statistically significant chi-square value (\u0026chi;\u0026sup2; = 123.595) and an acceptable normed chi-square (\u0026chi;\u0026sup2;/df\u0026thinsp;=\u0026thinsp;1.67). The SRMR value of 0.077 indicated minimal residual variance. Additional fit indices, d_ULS\u0026thinsp;=\u0026thinsp;1.284 and d_G\u0026thinsp;=\u0026thinsp;0.276, confirmed low discrepancies between observed and model-implied matrices. The NFI of 0.842 reflected a moderate yet acceptable fit for exploratory validation.\u003c/p\u003e\n \u003cp\u003eDiscriminant validity was confirmed using the Fornell\u0026ndash;Larcker criterion, as each construct\u0026rsquo;s square root of AVE\u0026mdash;biological (0.581), psychological (0.733), and social (0.564)\u0026mdash;exceeded its inter-construct correlations (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). Cross-loading analysis further supported this, with all items loading higher on their respective constructs than on others.\u003c/p\u003e\n \u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. Discriminant Validity Assessment of the PDRS Scale\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003eROC Curve Analysis\u003c/h2\u003e\n \u003cp\u003eROC analysis identified an optimal cutoff score of 15 for the PDRS, with a sensitivity of 71.3% and specificity of 80.2%, resulting in a Youden\u0026rsquo;s index of 0.515. The area under the curve (AUC\u0026thinsp;=\u0026thinsp;0.781; 95% CI: 0.742\u0026ndash;0.820) indicated good discriminatory ability. These results reflect a well-balanced diagnostic performance, effectively minimizing false positives and negatives in clinical screening (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003eKendall\u0026rsquo;s Tau-B Correlation Analysis\u003c/h2\u003e\n \u003cp\u003eA statistically significant positive association emerged between the EPDS and PDSS (Kendall\u0026rsquo;s \u0026tau;_b\u0026thinsp;=\u0026thinsp;0.226, P\u0026thinsp;\u0026lt;\u0026thinsp;.001, 95% CI: 0.153, 0.296), indicating that higher EPDS scores modestly predict classification as high-risk (\u0026ge;\u0026thinsp;8) on the PDRS. The weak correlation magnitude (\u0026tau;_b\u0026thinsp;\u0026asymp;\u0026thinsp;0.23) reflects limited shared variance, attributed to the PDRS\u0026rsquo;s broader construct (risk vulnerability) versus the EPDS\u0026rsquo;s (affective symptoms). This divergence confirms these instruments measure distinct but related aspects of PPD, excluding interchangeable use.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study provided strong empirical support for the validity and reliability of the PDRS scale, confirming its three-factor structure encompassing biological, psychological, and social risk domains. Grounded in the biopsychosocial framework, the model reflects the complex and multidimensional nature of postpartum depression. These findings underlined that PPD risk arises from an interplay of physiological, emotional, and social factors, elements often underrepresented in traditional symptom-based screening tools, underscoring the need for more holistic and culturally sensitive approaches to early detection.\u003c/p\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eBiological Risk Factors\u003c/h2\u003e\u003cp\u003eA history of mental illness remained one of the most consistent predictors of PPD, as highlighted by Liu et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), Shorey et al. (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and Usmani et al. (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Zhao and Zhang (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) reinforced this with a meta-analysis reporting a pooled OR of 3.71 (95% CI: 2.46\u0026ndash;5.60, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), emphasising the need for routine antenatal mental health screening. Sleep disturbances were also significant, with studies by Mohd Shukri et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and Zhao and Zhang (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) underscoring the role of sleep deprivation in emotional dysregulation. Unplanned pregnancy was another notable risk factor, associated with increased stress and lower coping capacity (Arifin et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Salsabilla et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Muskens et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Usmani et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Additionally, postpartum fatigue and body dissatisfaction contributed to depressive symptoms, as documented by Javaid et al. (2022), Asadi et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), Dimcea et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), and Day (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), supporting the need for postpartum care that addresses both physical and emotional recovery.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003ePsychological Risk Factors\u003c/h2\u003e\u003cp\u003eNegative thoughts and self-doubt during pregnancy were consistently linked to an increased risk of PPD, particularly when tied to maternal identity and parenting concerns (Araji et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Najid et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Pregnancy-related anxiety also emerged as a strong predictor, as noted by Qi et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), although cultural variability in its impact was observed (Hutchens \u0026amp; Kearney \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Emotional isolation and lack of support were recurrent psychological stressors, with studies reporting their strong association with depressive symptoms (Qi et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Smorti et al. 2019; Hairol et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), while Agrawal et al. (2022) described how anxiety and isolation may interact to worsen outcomes. Although social support can mitigate these risks (Hutchens \u0026amp; Kearney \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), its effectiveness may vary across contexts (Alsabi et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBody image dissatisfaction was another key contributor, with women reporting psychological distress linked to physical changes after childbirth (Najid et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Ryan et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Pehlivan et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). While Qi et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) confirmed a strong correlation, other studies noted more variable outcomes depending on demographic or cultural factors (Agrawal et al. 2022; Hairol et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Low self-esteem and perceived loss of control also played a significant role in PPD vulnerability (Najid et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Qi et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), particularly as new mothers navigated shifting identities and responsibilities (Wigert et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Watson et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These findings were supported by Liu et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and Saharoy et al. (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), though individual resilience and social support may moderate these effects (Hutchens \u0026amp; Kearney \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Tang et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Yu et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eSocial Risk Factors\u003c/h2\u003e\u003cp\u003eCultural expectations, including traditional confinement practices and the pressure to breastfeed, were found to contribute to stress, isolation, and emotional strain (Fadzil et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Haque \u0026amp; Malebranche \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Jackson et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Although some practices, such as religious coping, were protective for certain groups (Chow et al. 2024; Sampson et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), others, particularly when rigid or unsupported, heightened psychological vulnerability (Makama et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Saharoy et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Marital conflict and lack of spousal support were consistently associated with increased PPD symptoms, especially when coupled with traditional gender roles or limited healthcare access (Smorti et al. 2019; Hutchens \u0026amp; Kearney \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Chu \u0026amp; Moore \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSimilarly, insufficient family support during the confinement period was linked to emotional exhaustion and depressive symptoms (Najid et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Hairol et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Qi et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), with the quality of support being more impactful than its presence alone (Agrawal et al. 2022; Pehlivan et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Conflicts with in-laws or extended family members further increased emotional distress, particularly in collectivist cultures where such relationships are central to postpartum care (Shorey et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Chen et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Finally, cultural ideals of ideal motherhood and fear of judgment frequently cause shame and stigma surrounding depressive symptoms to delay seeking help (Jackson et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; De Jesus et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Zhao \u0026amp; Zhang \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These effects were moderated by education, social support, and access to care (Ryan et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Hutchens \u0026amp; Kearney \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eScale Validation\u003c/h2\u003e\u003cp\u003eThe study\u0026rsquo;s findings partially supported the proposed hypothesis, with all three domains, biological, psychological, and social, demonstrating statistically significant reliability and criterion validity. The psychological domain had the highest internal consistency (CR\u0026thinsp;=\u0026thinsp;0.851), aligning with literature on the predictive role of emotional and cognitive stressors in PPD (Tatevosyan \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Huiju et al. 2025). The biological domain also met acceptable reliability standards (CR\u0026thinsp;=\u0026thinsp;0.700), reflecting established links with hormonal and medical risk factors (Yang et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Munk-Olsen et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Although the social domain showed slightly lower reliability (CR\u0026thinsp;=\u0026thinsp;0.693), it remained valid, likely reflecting the cultural variability of social support and stressors (English et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Bjertrup et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The final 15-item scale was reduced from an initial 31-item pool through expert review and CFA, confirming construct validity and reducing redundancy. Discriminant validity was established; unlike other tools limited to content validation (Johansson et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Lee et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), the PDRS underwent a comprehensive, culturally sensitive validation process.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe validated PDRS scale reflected its findings by incorporating culturally relevant, evidence-based items that capture both individual and contextual risks. This multidomain approach offers a more holistic framework for early identification and intervention, supporting the need for preventive screening strategies that extend beyond symptom-based models like the EPDS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImplications of the Study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTheoretically, the validated Postpartum Depression Risk Scoring (PDRS) scale addressed a critical gap in culturally relevant, risk-based screening tools for PPD. Grounded in the biopsychosocial model, the scale integrated psychological, biological, and social predictors, reflecting the complexity of maternal experiences in the Malaysian context. The psychological domain, in particular, demonstrated strong internal consistency, while the biological and social domains provided additional layers of risk insight. By incorporating factors such as family conflict, cultural pressures, and stigma-related help-seeking hesitancy, the scale responded to sociocultural dimensions often overlooked in global instruments.\u003c/p\u003e\n\u003cp\u003eIn clinical practice, the PDRS presents a feasible and targeted screening tool for early identification of at-risk mothers, particularly in maternal and child health settings. It facilitates proactive intervention before symptom escalation, aligning with public health goals for preventive mental health care. Moreover, the findings support the need for culturally sensitive public health initiatives, including anti-stigma campaigns, caregiver training, and family-centered support during the postpartum period.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSeveral limitations must be considered. The study was based on a secondary systematic review and cross-sectional data from 300 respondents, which may limit generalizability. The slightly lower reliability of the social domain suggests the need for item refinement, especially to capture diverse cultural and relational contexts. The absence of longitudinal data restricts conclusions about the scale\u0026rsquo;s predictive validity over time.\u003c/p\u003e\n\u003cp\u003eFuture research should focus on extending validation to other Southeast Asian populations and exploring the scale\u0026rsquo;s performance in longitudinal and clinical applications. Comparative studies with established tools can assess their distinct utility, while qualitative research may deepen understanding of culturally embedded risk factors. Iterative refinement based on user feedback will enhance the scale\u0026rsquo;s sensitivity and applicability. Ultimately, the PDRS provides a foundation for improving culturally responsive maternal mental health screening and policy in Malaysia and similar multicultural settings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCRediT Author Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRS:\u003c/strong\u003e Conceptualization; Methodology; Software; Validation; Roles/Writing - original draft; Writing; Data curation; Investigation and Formal analysis. \u003cstrong\u003eAA:\u0026nbsp;\u003c/strong\u003eProject administration; Resources and Funding acquisition\u003cstrong\u003e, AA, RAD, ASBA \u0026amp; RRD\u003c/strong\u003e: Reviewing, Visualization,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest Statements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRole of Funding Source\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAhmad N, Silim U, Rosman A, Mohamed M, Chan YY, Kasim N, et al. 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Existing instruments often overlook sociocultural stressors specific to local contexts. This study aimed to develop and validate a Postpartum Depression Risk Scoring (PDRS) scale tailored to Malaysian women, addressing the multidimensional nature of PPD risk, to enable earlier detection. Adopting this scale within 24-hour postpartum screening procedures could facilitate prompt clinical interventions.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003e A sequential mixed-methods design was employed in three phases: (1) item generation from a systematic review and qualitative synthesis; (2) expert content validation; and (3) psychometric evaluation using Partial Least Squares Structural Equation Modeling (PLS-SEM) and Confirmatory Factor Analysis (CFA) on data from 300 postpartum women recruited from two public hospitals. Discriminant validity and criterion validity were also assessed.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe initial 31-item pool was refined to a 15-item scale encompassing three domains: biological (CR\u0026thinsp;=\u0026thinsp;0.700), psychological (CR\u0026thinsp;=\u0026thinsp;0.851), and social (CR\u0026thinsp;=\u0026thinsp;0.693). CFA confirmed acceptable model fit (χ\u0026sup2; = 123.595; χ\u0026sup2;/df\u0026thinsp;=\u0026thinsp;1.67; SRMR\u0026thinsp;=\u0026thinsp;0.077; NFI\u0026thinsp;=\u0026thinsp;0.842). Discriminant validity was supported via the Fornell\u0026ndash;Larcker criterion. ROC analysis yielded an optimal cutoff score of 15, with a sensitivity of 71.3%, specificity of 80.2%, and an AUC of 0.781 (95% CI: 0.742\u0026ndash;0.820), demonstrating satisfactory predictive performance. Convergent validity analysis revealed a statistically significant positive association between the PDRS and the EPDS (Kendall\u0026rsquo;s τ_b\u0026thinsp;=\u0026thinsp;0.226, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), indicating higher EPDS scores correspond to elevated risk classification on the PDRS.\u003c/p\u003e\u003ch2\u003eDiscussion\u003c/h2\u003e\u003cp\u003eThe PDRS scale is a valid and reliable tool, which captures culturally relevant risk factors for PPD among Malaysian women. Its multidimensional structure reflects the biopsychosocial complexity of PPD and addresses gaps in traditional screening practices. The scale holds potential for early identification and prevention of PPD in diverse maternal health settings.\u003c/p\u003e","manuscriptTitle":"Development and Validation of a Novel Culturally-Tailored Postpartum Depression Risk Scoring Scale (PDRS) in Malaysia: A Sequential Mixed-Methods Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-13 13:50:01","doi":"10.21203/rs.3.rs-7580820/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7cd81808-1857-4ad6-aeb0-356a7bce11f9","owner":[],"postedDate":"October 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-31T14:57:05+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-13 13:50:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7580820","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7580820","identity":"rs-7580820","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}