Development and validation of the Gestational Diabetes Mellitus Holistic Healthcare Needs Scale

Development and validation of the Gestational Diabetes Mellitus Holistic Healthcare Needs Scale | 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 the Gestational Diabetes Mellitus Holistic Healthcare Needs Scale Cathy Knight-Agarwal, Abu Saleh, Mary-Ellen Hooper, Indira Samarawickrema, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7209307/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 Aims: This study aimed to develop and test a scale to measure the holistic healthcare needs of women with Gestational Diabetes Mellitus. Method : The scale was developed through a three-stage process. In stage one, initial items were generated based on a review of current literature, followed by content validation with service users and healthcare professionals. Stage two involved assessing face validity through cognitive interviews with women diagnosed with gestational diabetes mellitus (GDM). In the final stage, the scale was evaluated using a sample of 342 women with GDM, recruited through the National Diabetes Services Scheme in Australia. Exploratory and confirmatory factor analyses were conducted to assess the scale’s structure, and its reliability and validity were examined including tests for convergent and discriminant validity. Results: The final GDM Holistic Healthcare Needs Scale has 29 items within 6 domains; psychological, health education and information, managing GDM, healthcare services, social and personal, and culture. Variances of each factor explained were 12.87%, 12.21%, 12%, 10.80%, 8.41%, 7.39% and all six factors explained 69.13% of the variance in the 29 items. Results of confirmatory factor analysis suggest that adequate fit indices were achieved within the recommended thresholds. Conclusions: The GDM Holistic Healthcare Needs Scale shows adequate convergent and discriminant validity and reliability to measure the holistic healthcare needs of women with GDM. Obstetrics & Gynecology Sexual & Reproductive Medicine Gestational diabetes holistic unmet need scale development validation Introduction Gestational Diabetes Mellitus (GDM) is one of the most common complications of pregnancy [ 1 ], characterised by glucose intolerance occurring with onset or first recognition during pregnancy [ 2 – 4 ]. It is one of the fastest growing types of diabetes both in Australia and internationally [ 5 , 6 ]. The prevalence of GDM is estimated at around 14% of pregnancies worldwide, with ranges from 1–36% largely due to a lack of uniformly implemented diagnostic measures [ 1 ].However, in Australia and in many high-income nations, its prevalence is around 15% of pregnancies [ 7 ]. The number of women diagnosed with GDM continues to rise, tripling in the last 10 years, largely secondary to adoption of new diagnostic criteria in some nations [ 6 , 8 ], as well as increased numbers of higher-risk women due to rising average maternal age, higher rates of overweight and obesity and in some countries migration that is altering population demographics [ 4 , 8 ]. Risk factors for the development of GDM include having a family history of type 2 diabetes mellitus (T2DM), pre-existing insulin resistance, higher body mass index (BMI) [ 7 ], polycystic ovarian syndrome, advanced maternal age, having a previous large for gestational weight baby, and being from a disadvantaged group [ 8 – 10 ]. GDM is more likely to occur and have adverse health outcomes for women from culturally and linguistically diverse (CALD) backgrounds in particular, women from East, South and Southeast Asia; Indian subcontinent; Australian First Nations; Pacific Islander; Māori; middle eastern; non-white African; and South/Latina American women [ 4 , 5 , 11 ]. A pregnancy affected by GDM is associated with higher rates of adverse pregnancy outcomes and poorer longer-term health for both mother and babies. Adverse pregnancy outcomes for the babies include pre-term birth, macrosomia, birth trauma including from shoulder dystocia, neonatal hypoglycaemia and neonatal respiratory distress [ 12 ]. Women are also more likely to experience gestational hypertensive disorders including pre-eclampsia, in addition to receiving birth interventions such as induction of labour or caesarean section. Post partum such women have a higher chance of experiencing difficulties breastfeeding [ 13 ] [ 10 , 14 ]. In the longer term, women have an increased risk of a GDM diagnosis in subsequent pregnancies and a 60% life-time risk of developing T2DM [ 15 ], as well as an increased risk in developing cardiovascular diseases [ 16 , 17 ]. Babies born to women with GDM are also more likely to have difficulty in maintaining a recommended body mass index (BMI) and have an increased risk of developing cardiometabolic disease, including T2DM and heart disease, later in life [ 10 , 18 ]. Research suggests that the risks and comorbidities associated with GDM can be significantly reduced with lifestyle changes, such as diet and physical activity, together with monitoring of blood glucose levels (BGLs) [ 14 , 19 , 20 ]. Despite these initiatives, approximately 15–30% of women will require pharmacological glucose lowering medication such as insulin [ 21 ]. However, women report challenges associated with managing GDM and describe psychological distress, particularly as they navigate the demands of significant lifestyle changes alongside the demands of pregnancy. Women have reported feeling denial, fear, shock and guilt associated with their GDM diagnosis [ 22 ]. This is further impacted by a loss of normality and personal control [ 22 ], with some women feeling as though their needs are diminished by health professionals (HP’s) who have a primary focus on the fetus [ 23 ]. The unmet needs of women have been described in several publications, particularly in relation to the psychosocial impacts of GDM, as well as access to information, guidance, and support in managing the condition [ 24 , 25 ]. Research indicates that women of ethnic minority groups experience high levels of unmet need leading to disengagement, lack of understanding and poor compliance with recommendations [ 26 ]. Women desire person-centred care, with a need for management to be more holistic and not focused solely on clinical measures and outcomes [ 24 ]. The ability to measure the degree to which our services address the needs of the population it serves, is important to service providers and policy makers to ensure the design and delivery of services are meeting their needs. A review of the literature revealed several instruments that are useful for measuring different aspects of the diabetes experience including the Diabetes Management Self-Efficacy Scale (DMSES) [ 27 ], the Diabetes Distress Scale [ 28 ], Quality of Life questionnaire GDM – GDMQ-36 [ 29 ] and Problem Areas In Diabetes Scale (PAID)[ 30 ]. These instruments, however, are not specific to women with GDM who have a broader range of healthcare needs. Little is known about the quality of services provided to women with GDM and the extent to which they meet the unique needs of women with GDM. Thus, we have developed the GDM Holistic Healthcare Needs (GDM:HHN) Scale following best practice methods [ 31 ]. We anticipate that this will make a useful contribution to the evaluation and development of services for women with GDM. Subjects, Materials, Methods The GDM:HHN scale was developed in 3 stages of item development (stage 1), scale development (stage 2), and scale evaluation (stage 3), following Boateng et al [ 31 ]. In stage one , items were developed following the conduct of two systematic reviews: one a meta synthesis of qualitative studies focusing on the holistic healthcare needs of women with GDM [ 25 ]; and the other an integrative review of the needs of women with GDM from CALD communities in high income settings [ 26 ]. This resulted in the development of items under 5 domains: psychological; education and information; health services; diet and lifestyle; and social and personal. In this stage, content validity was assessed with a panel of experts comprising healthcare professionals (diabetes educator, midwife, endocrinologist, obstetrician, dietitian) ( n = 5) and women with experience of GDM ( n = 13). The expert panel members were asked to rate each item for relevance and clarity using a four-point Lickert Scale (strongly agree to strongly disagree) in an online survey using the REDCap electronic data capture tool hosted at the University of Canberra [ 32 ]. A content validity index for each item (i-CVI) was calculated by dividing the total number of experts rating each item as either 3 or 4 (strongly agree or agree item is relevant) and dividing this by the total number of experts. A i-CVI above 70% was considered acceptable [ 38 ]. In stage two , face validity was undertaken using cognitive interviews. Cognitive interviews involve the administration of the draft survey questions to a sample of the target population, asking them to verbalize their thought process while responding [ 31 ]. This ensures that: the questions produce intended data; confusing or problematic questions can be modified; response options are appropriate; questions are culturally sensitive; and the items comprehensively address the intended topic. The response options were borrowed from the Supportive Care Need Scale [ 33 ] which are used widely in cancer services to identify unmet need. These options were: not applicable or no need; low need; moderate need; high need. Interviews were conducted with women with a recent history of GDM. Responses were noted in a table by the interviewer and responses to all interviews were considered by the research team with amendments made as required. The resulting questionnaire was then translated into Simple Chinese, Hindi, Urdu, and Punjabi (forwards and backwards by qualified translators), these being the language groups of CALD women most affected by GDM in Australia and where English language capacity is lowest [ 34 ]. Five surveys were created in REDCap, one in each of the five languages included. In stage three , scale evaluation was undertaken. All women diagnosed with GDM in Australia are enrolled with the National Diabetes Services Scheme (NDSS). An email invitation was sent to a random sample of 19, 604 enrolled women with GDM, in five languages with links to the survey in REDCap. The inclusion criteria for participation were: 1) pregnant with GDM; 2) at least 34 weeks gestation; and 3) receiving healthcare in Australia. The survey was sent on 4th of May 2023 with a reminder sent 10 days later. The NDSS was unable to target women who were at least 34 weeks gestation, so the email was sent to all enrolled women with GDM. Screening questions established eligibility to participate. Validation of the GDM: HHN Scale Initially, descriptive statistics, frequency analysis, and missing value identification was undertaken. Normality for individual items was examined using a kurtosis value of > 3.00 (non-normality) [ 35 ] and multivariate normality was assessed using a kurtosis value of > 5.00 (non-normality) [ 36 ]. Based on the recommendations of Tabachnick [ 37 ], data from participants with ≥ 80% missing responses were excluded and responses with 1 to 4 missing values were replaced with the respective scale mean value. Univariate outlier assessment was undertaken using standardized z -scores of ± 2.29. Multivariate outliers were identified using Mahalanobis distance scores greater than χ 2 (6) = 22.46 (p < .001). Exploratory Factor Analysis (EFA) on the complete dataset with Varimax rotation was conducted. The Bartlett Test of Sphericity (agreeable if p < 0.05) and the Kaiser–Meyer–Olkin measure of sampling adequacy (≤ 0.50 poor-≥0.90 excellent) were examined to verify the uni-dimensionality of the constructs [ 38 ]. The number of factors to be retained was determined from scree plots of the Eigenvalues. The items that substantially contributed to a given factor were selected based on their loading of > 0.7 [ 39 ]. Single factor analysis using structural equation modelling (SEM) provided insight regarding individual scale items and their coherency thus signalling the degree of support for the overall model [ 39 ]. Our study evaluated model fit statistics including: Chi-square value/Degree of Freedom (CMIN/DF) (χ2/df: .90; Tucker-Lewis index (TLI): >0.90; Comparative Fit Index (CFI): >0.90; Root Mean Squared Error Approximation (RMSEA) (≤ 0.08) [ 40 – 43 ]. These were followed if goodness-of-fit indices either met or exceeded the ‘acceptable’ cut-off norms. Standardized loadings for the scale items, variance of the items, critical ratios (T-value), error covariance and modification indices were also assessed when evaluating model fit. To achieve model fit indices, error covariance and inclusion of items that provided solutions, if theoretically reasonable, were also included. Before undertaking further investigation, a series of Cronbach's Alpha tests, [ 44 ] based on standardized items, were conducted to assess internal consistency of the measures. The verified items under single factor analyses showed excellent scores exceeding the recommended threshold of 0.70 for all constructs. The next and final step of the scale validation process was Confirmatory Factor Analysis (CFA). High error covariance and redundancy of used items in the same or different constructs were identified via assessment of modification indices, covariance structure and standardized factor loading scores [ 45 ]. Convergent validity was measured by calculating Average Variance Extracted (AVE) and assessment of Composite Reliability (CR) for each of the constructs [ 46 ]. The recommended AVE ≥ 0.50 exhibited adequate convergent validity, meaning that the latent factor explains more than half of its indicators’ variance. A composite reliability > 0.70 signified acceptability as well as the degree to which measurement indicators reveal the latent factor [ 46 , 47 ]. Statistical analysis and ethics All analyses were performed using IBM SPSS version 22.0 and AMOS version 24.0. All hypothesis tests were two-tailed with a type I error rate fixed at 0.05. Ethics approval for all stages of the study was obtained from the University of Canberra Human Research Ethics Committee in March 2022 (approval number 2022:11518). Results Scale development In stage one , 135 items were established following a review of the literature. By addressing duplication, the research team reduced this to 71 items under 5 domains: psychological; education and information; healthcare services; diet and lifestyle; and social and personal. After expert assessment by HPs (diabetes educator, midwife, endocrinologist, obstetrician, dietitian) ( n = 5) and women with experience of GDM ( n = 13), four items were deemed irrelevant (CVI < 69%) and removed, leaving 67 items. Assessment of Chronbach’s Alpha reduced the items by a further 35. The research team considered the large number of items deleted at this stage and sought to balance parsimony with comprehensiveness. Given that the instrument was going to be further tested with a large sample of women, the decision was made to re-introduce select items based on the team’s experience as healthcare professionals and literature reviews. This resulted in the re-introduction of 9 items giving a total of 41. In stage two , cognitive interviews were conducted with 11 women with a recent history of GDM. After consideration by the research team, 5 domains remained (“diet and lifestyle” was renamed “managing GDM”) with some items deleted, others added, and many re-worded, resulting in a total of 43 items. In stage three the scale was administered to women with GDM. Characteristics of the 342 women who participated are presented in Table 1 . All states and territories of Australia are represented. Almost half the women were multiparous, and the vast majority were partnered (married or de facto). A high proportion of participants were well educated with degree qualifications. Table 1 Participant characteristics Characteristic 342 total responses MEAN (SD) / n (%) Mean age 34.47 (4.59) Mean gestation 36.7 (2.80) Mean gestation at diagnosis 24.3 (5.67) Parity Multiparous 169 (49.4) Primiparous 172 (50.3) Missing 1 (0.3) First GDM diagnosis Yes 147 (43) No 22 (6.4) Missing 173 (50.6) State/territory of residence NSW 114 (32.5) VIC 92 (26.2) SA 28 (8.0) WA 28 (8.0) NT 3 (0.9) QLD 59 (16.8) ACT 23 (6.6) TAS 3 (0.9) Aboriginal and or Torres Strait Islander 7 (2.0) Language spoken at home Arabic 2 (0.6) Cantonese 2 (0.6) English 282 (82.5) Hindi 8 (2.3) Italian 2 (0.6) Mandarin 15 (4.4) Punjabi 7 (2.0) Spanish 1 (0.3) Vietnamese 2 (0.6) Other 20 (5.8) Missing 1 (0.3) Education High school or lower 33 (9.6) Trade/diploma 58 (16.9) Degree/higher degree 244 (71.3) Other 5 (1.4) Missing 2 (0.6) Relationship status Married/de facto 326 (95.3) Single/divorced/separated/widowed 12 (3.5) Missing 4 (1.2) Healthcare support* No healthcare card 302 (88.3) Veteran White Card or Healthcare Card 39 (11.4) Missing 1 (0.3) *In Australia a Health Care Card or Veteran White Card provides the recipient with concessions, subsidies or free access to some health care and other essential services. Scale validation Exploratory Factor Analysis (EFA) on the complete dataset with Varimax rotation showed most items aligned under 7 factors (see Table 2 ). Two items failed to meet the threshold of 0.4 (HEI 11 and MGDM 7) indicating that their contribution to the factor was not substantial [ 48 ]. Items aligning to factor five were clearly focused on culture while those aligning with factor 7 did not have a coherent focus. Thus, items HEI9, HEI10, HS1, MGDM5, MGDM8 were used to form a new domain (factor), culture. Furthermore, variances of each factor were established as 12.87% (PSY), 12.21% (HEI), 12% (HS), 10.80% (MGDM), 8.41% (SP), 7.39% (C) and all six factors explained 69.13% of the variance in the 29 included items suggesting the extent to which the overall model captures the variability within the data. Table 2 Exploratory Factor Analysis (Matrix) Scale Items ® 1 2 3 4 5 6 7 Psychological PSY1 Help in coping with the initial shock of your GDM diagnosis .751 PSY2 Help in dealing with fears for the health of you or your baby because of GDM .751 PSY3 Help in dealing with guilt associated with being diagnosed with GDM .753 PSY4 Getting emotional support from your care providers .639 PSY5 Help to feel positive about your pregnancy despite GDM .664 PSY6 Help to use the diagnosis as an opportunity to lead a healthier life .507 Health Education and Information HEI1 Information to enable you to fully understand the impact of GDM on your pregnancy .436 .472 HEI2 Information to enable you to fully understand the tests and procedures recommended during pregnancy .492 HEI3 Information to enable you to fully understand the diabetic diet recommended for pregnancy .581 HEI4 Information to enable you to fully understand the recommended physical activity levels during pregnancy .466 .516 HEI5 Information to enable you to fully understand medications or injections needed to manage your GDM .623 HEI6 Information to enable you to fully understand recommendations for how you labour and give birth .625 HEI7 Information to enable you to fully understand tests and procedures recommended for your baby after birth .779 HEI8 Information to enable you to make informed decisions about infant feeding (breast or formula) after your baby is born .701 HEI9 Information about managing GDM that takes account of your culture .704 HEI10 Information provided in a language or words that you can understand .583 .509 HEI11 Information to enable you to fully understand tests and procedures recommended for you after discharge from hospital related to GDM HEI12 Information about maintaining a healthy diet and exercise patterns after your baby is born .666 HEI13 Information to enable you to fully understand tests and procedures recommended for you after discharge from hospital related to GDM .739 HEI14 Information about maintaining a healthy diet and exercise patterns after your baby is born .622 Health Services HS1 Having your spiritual and/or religious needs acknowledged by your healthcare providers .724 HS2 Getting the care you need; at the time you need it .546 HS3 Consistent information and advice from different healthcare providers .643 HS4 Having trust and confidence in your healthcare providers .726 HS5 Healthcare providers that respect your values, beliefs and/or culture .548 .505 HS6 Having a say in how your GDM is managed .738 HS7 Having choices about the way you labour and give birth .783 HS8 Feeling in control of the decisions about your pregnancy and birth .808 HS9 Not always feeling 'high risk' .610 Managing GDM MGDM 1 Guidance to enable you to meet the dietary recommendations for GDM .755 MGDM 2 Guidance to enable you to eat at restaurants and enjoy social outings .707 MGDM 3 Guidance to help you manage your GDM diet alongside the family meal schedule .752 MGDM 4 Guidance to help you manage your GDM with a busy schedule .651 MGDM 5 Guidance about diet that includes foods important to your culture or personal preferences .481 .625 MGDM 6 Guidance in self-administration of insulin injections or taking medicine .676 MGDM 7 Resources such as a diary to record your blood glucose levels, food intake and medications MGDM 8 Guidance for managing GDM that takes your culture and lifestyle into consideration .687 MGDM 9 Guidance on meeting the recommended levels of physical activity in pregnancy .503 Social and Personal SP1 Support from your family to manage your GDM .503 SP2 Knowledge of programs in the community that might be helpful to you .405 SP3 Having friends/colleagues accommodate your needs in relation to managing your GDM .687 SP4 Communicating with other women who also have GDM (online or other) .649 SP5 Positive reinforcement from family/friends about the things you are doing well to manage your GDM .675 There were some scores above 0.4 sitting in the different factors indicating either cross loading or miss alignment with the domain (factor) to which they were allocated prior to factor analysis. These were subject to further verification under single or confirmatory factor analyses. As a recommended sequence, the next step was to check each of the single factor analysis using the AMOS statistical package. Single Factor analysis Tables 3 presents the factor loading scores for each of the constructs showing reasonable fit indices. Psychological (PSY) measure shows good fit with 4 items (excluding item 4 and 6) and excellent factor loading. Health Education and Information (HEI) measure has 14 items. Eight items show coherent and reasonable factor loading with very good model fit. Heath Service (HS) measure has nine items. Five items excluding items 1, 5, 7, and 8 show very good fit with excellent factor loading. Managing GDM (MGDM) measure has nine items. Five items excluding items 6, 7, 8, 9 revealed excellent model fit and factor loading. Social and personal (SP) items show very good fit and factor loading excluding item number 4. Some of these excluded factors loaded well but they show co-sharing of co-variance with some of the measurement items in each of the single measures. Investigation of the covariance structure in the Modification Indices (Mis) section of these construct measures specifically suggested that at least one or more modification was necessary due to associated misspecification. The expected change statistics of error covariances also revealed that there were misspecifications associated with those of the items. Finally, excluding such problematic items and comparison of initial analysis/findings of each construct measure clearly suggest that some of those items were responsible for the poor fit to the model and they were finally excluded from the analyses to achieve the recommended and acceptable overall model fit to the data. Nonetheless, some of the measures, for example, the measure for culture (C) fitted very well without any recommended modifications. Table 3 Single models- Standardized Factor Loading Scale items Estimate (β value) Level of significance Psychological PSY1 .856 .001 PSY2 .895 .001 PSY3 .821 .001 PSY5 .783 .001 Model fit statistics : CMIN/DF = 1.68; IFI = .99; TLI = .99 CFI = .99; RMSEA = 0.045 Health Education and Information HEI2 .815 .001 HEI4 .748 .001 HEI5 .645 .001 HEI6 .765 .001 HEI8 .696 .001 HEI11 .689 .001 HEI12 .795 .001 Model fit statistics : CMIN/DF = 2.46; IFI = .98; TLI = .97 CFI = .98; RMSEA = 0.065 Health Services HS2 .734 .001 HS3 .851 .001 HS4 .899 .001 HS6 .757 .001 HS9 .658 .001 Model fit statistics : CMIN/DF = 3.10; IFI = .99; TLI = .97 CFI = .99; RMSEA = 0.078 Managing GDM MGDM1 .762 .001 MGDM2 .842 .001 MGDM3 .938 .001 MGDM4 .886 .001 Model fit statistics : CMIN/DF = 8.27; IFI = .99; TLI = .96 CFI = .99; RMSEA = 0.11 Social and Personal SP1 .740 .001 SP2 .516 .001 SP3 .705 .001 SP5 .821 .001 Model fit statistics : CMIN/DF = 5.48; IFI = .97; TLI = .93 CFI = .97; RMSEA = 0.11 Culture C1 .692 .001 C2 .501 .001 C3 .552 .001 C4 .813 .001 C5 .878 .001 Model fit statistics : CMIN/DF = 3.76; IFI = .98; TLI = .96 CFI = .98; RMSEA = 0.09 Convergent and discriminant validity EFA and CFA produced robust evidence that scale items were discriminant explaining the entire theoretical phenomenon including reasonable factor loading scores and model fit statistics. Additional analyses using χ 2 /df in one degree of freedom provided further evidence of convergent and discriminant validities. See Table 4 . The analyses demonstrate that all constrained models/constructs are significantly different from the unconstrained models/constructs which suggests that individual constructs are converged and discriminant from each of them. Table 4 Results of the χ 2 difference test for all theoretically related constructs Models χ 2 (d.f.) χ 2 (d.f.) χ 2 Differences (d.f.) Culture ⇓◊ HEI Constrained 178.60(53) Unconstrained 147.15(52) 31.45(1) Culture ⇓◊ HS Constrained 134.07(34) Unconstrained 86.19(33) 47.88(1) Culture ⇓◊ SP Constrained 114.69(26) Unconstrained 56.60(25) 58.09(1) Culture ⇓◊ PSY Constrained 84.32(26) Unconstrained 49.85(25) 34.47(1) Culture ⇓◊ MGDM Constrained 93.35(26) Unconstrained 60.79(25) 32.56(1) HEI ⇓◊ HS Constrained 165.11(54) Unconstrained 140.97 (53) 24.14(1) HEI ⇓◊ SP Constrained 164.82(44) Unconstrained 122.54(43) 42.28(1) HEI ⇓◊ PSY Constrained 88.44(44) Unconstrained 78.87(43) 9.57(1) HEI⇓◊ MGDM Constrained 195.75(44) Unconstrained 171.04(43) 24.71(1) HS ⇓◊ SP Constrained 180.52(27) Unconstrained 123.73(26) 56.79(1) HS ⇓◊ PSY Constrained 101.06(27) Unconstrained 83.86(26) 17.20(1) HS ⇓◊ MGDM Constrained 131.77(27) Unconstrained 97.20(26) 34.57(1) SP ⇓◊ PSY Constrained 102.85(20) Unconstrained 65.55(19) 37.30(1) SP ⇓◊ MGDM Constrained 118.83(20) Unconstrained 68.86(19) 49.97(1) PSY ⇓◊ MGDM Constrained 68.52(20) Unconstrained 44.66(19) 23.86(1) Confirmatory factor analysis (CFA) On confirming convergent and discriminant validities of the measures, the next sequential step was to conduct confirmatory factor analysis which is a robust approach to validate the construct measures. This analysis of validation produces factor loading and CFA model fit statistics using thresholds for the acceptable range of factor loadings scores (> .4) and CFA model fit statistics (CMIN/DF; CFI; TLI; IFI and RMSEA). Confirmatory Factor analysis was conducted using all retained items (based on single factor analyses). The analysis revealed parsimonious fit to the data/measurement model with satisfactory factor loadings. CFA results can be seen in Table 5 . Table 5 CFA factor loading scores. Factors/Measures Scale Items Estimate Level of significance Psychological AR = .91 AVE = .71 CR = .90 PSY1 .854 .001 PSY2 .891 .001 PSY3 .813 .001 PSY5 .802 .001 Health Education and Information AR = .89 AVE = .54 CR = .91 HEI2 .810 .001 HEI4 .745 .001 HEI5 .647 .001 HEI6 .769 .001 HEI8 .674 .001 HEI11 .717 .001 HEI12 .789 .001 Heath Service AR = .89 AVE = .62 CR = .89 HS2 .748 .001 HS3 .854 .001 HS4 .873 .001 HS6 .757 .001 HS9 .687 .001 Managing GDM AR = .92 AVE = .74 CR = .92 MGDM1 .774 .001 MGDM2 .845 .001 MGDM3 .930 .001 MGDM4 .886 .001 Social and personal AR = .79 AVE = .49 CR = .80 SP1 .723 .001 SP2 .628 .001 SP3 .712 .001 SP5 .744 .001 Culture AR = .83 AVE = .49 CR = .82 HEI9 .699 .001 HEI10 .496 .001 HS1 .546 .001 MGDM5 .826 .001 MGDM8 .865 .001 CFA Model fit statistics : CMIN/DF = 2.46; IFI = .92; TLI = .91 CFI = .92; RMSEA = 0.065 Notes: Cronbach's Alpha Reliability = AR; Average variance extracted = AVE; Composite reliability = CR Discussion GDM is the fastest growing type of diabetes globally and in Australia, health services are struggling to meet demand [ 49 ]. While a variety of scales exist to measure the healthcare experiences and needs of people with diabetes, none focus on the unique needs of women with GDM. Therefore, we developed the Holistic Healthcare Needs Scale for women with GDM following a robust process. The final GDM: HHN Scale has six domains: psychological, health education and information, managing GDM, healthcare services, social and personal, and culture. These domains are well supported with evidence from our systematic reviews indicating unmet need in this population, over these domains [ 13 , 25 , 26 ]. The scale development followed best practice [ 31 ] and importantly involved both healthcare professionals and those with lived experience of GDM. Those with lived experience are best placed to identify their needs and the inclusion of healthcare professionals ensures the scale is useful and relevant also to healthcare providers. Our study used exploratory and confirmatory factor analysis, with results providing evidence that scale items were discriminant explaining the theoretical phenomena with reasonable factor loading scores and model fit statistics. Additional analysis provides evidence of convergent and discriminant validity. The GDM: HHN Scale has several strengths. The development and validation process were comprehensive and included input from multiple sources including contemporary literature, service users and providers. The questionnaire was translated into languages where women are most affected by GDM in Australia and where English language capacity is lowest [ 50 ]. This helped to protect against instrument bias thus supporting its applicability across a wide range of settings. Next, a rigorous step by step statistical analysis was undertaken including descriptive statistics, EFA and CFA. Several limitations of this study should be noted. Responders to the questionnaire are not representative of the population in Australia. Most were highly educated and despite efforts to recruit an ethnically diverse sample, most mainly spoke English at home. Selection bias may limit the generalizability of the findings presented here. As no other scales measure holistic healthcare needs in this population, criterion validity cannot be assessed. Lastly, this newly developed scale may better assess women’s unmet needs which, in turn, may enable healthcare providers to tailor their service with greater precision. Although the GDM: HHN Scale is a promising new instrument with evidence that it is valid and reliable, its psychometric properties and test characteristics need to be further investigated in larger and more diverse samples. It also would be valuable to assess its responsiveness to GDM associated interventions before it can be recommended for widespread use. Conclusion GDM: HHN Scale is the first instrument designed to measure holistic health care needs of women with GDM. It demonstrates sufficient reliability and validity and as such, is a useful tool for healthcare providers to assess the quality of their services. Declarations All those participating in this study provided informed consent as detailed and approved by the relevant Human Research Ethics committee. Funding information This study was funded by a grant from the University of Canberra, Australia. The sponsors had no role in the design and conduct of the study or in the analysis data, interpretation of findings or approval of this manuscript. Declaration of competing interests The authors declare that they have no known competing financial interests or personal relationships that could have influenced the work presented in this manuscript. References Sweeting, A., et al., Epidemiology and management of gestational diabetes. The Lancet, 2024. 404 (10448): p. 175-192. World Health Organization. Diagnostic criteria and classification of hyperglycaemia first detected in pregnancy. World Health Organization. 2013 [cited 2022 28 January]; Available from: https://apps.who.int/iris/handle/10665/85975. McIntyre, H.D., et al., Gestational diabetes mellitus. Nature Reviews Disease Primers, 2019. 5 (1): p. 47. AIHW: Australian Institute of Health and Welfare. Incidence of gestational diabetes in Australia . 2019 [cited 2022 5 February ]; Available from: https://www.aihw.gov.au/reports/diabetes/incidence-of-gestational-diabetes-in-australia/contents/changing-trends#Trends%20discussion. Diabetes Australia. Position Statement. Gestational Diabetes in Australia . 2020 [cited 2022 29 January]; Available from: https://www.diabetesaustralia.com.au/wp-content/uploads/Gestational-Diabetes-in-Australia-Position-Statement-2020.pdf. Laurie, J.G. and H.D. McIntyre, A Review of the Current Status of Gestational Diabetes Mellitus in Australia—The Clinical Impact of Changing Population Demographics and Diagnostic Criteria on Prevalence. 2020. 17 (24): p. 9387. McIntyre, H.D., et al., Gestational diabetes mellitus. Nature reviews. Disease primers, 2019. 5 (1): p. 47. Nankervis, A., et al. Australasian Diabetes in Pregnancy Society consensus guidelines for the testing and diagnosis of gestational diabetes mellitus in Australia 2014; Available from: http://www.adips.org/downloads/ADIPSConsensusGuidelinesGDM-03.05.13VersionACCEPTEDFINAL.pdf. Jamieson, E.L., et al., Prediabetes and pregnancy: Early pregnancy HbA1c identifies Australian Aboriginal women with high-risk of gestational diabetes mellitus and adverse perinatal outcomes. Diabetes Research & Clinical Practice, 2021. 176 . Tieu, J., et al., Screening for gestational diabetes mellitus based on different risk profiles and settings for improving maternal and infant health. 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Parsons, J., et al., Perceptions among women with gestational diabetes. Qual Health Res, 2014. 24 (4): p. 575-85. Parsons, J., et al., Experiences of gestational diabetes and gestational diabetes care: a focus group and interview study. BMC Pregnancy Childbirth, 2018. 18 (1): p. 25. Litterbach, E., et al., 'I wish my health professionals understood that it's not just all about your HbA1c !'. Qualitative responses from the second Diabetes MILES - Australia (MILES-2) study. Diabet Med, 2020. 37 (6): p. 971-981. Davis, D., et al., The holistic maternity care needs of women with Gestational Diabetes Mellitus: A systematic review with thematic synthesis. Women Birth, 2024. 37 (1): p. 166-176. Tzotzis, L., et al., The needs and experiences of women with gestational diabetes mellitus from minority ethnic backgrounds in high-income nations: A systematic integrative review. Women Birth, 2023. 36 (2): p. 205-216. Bijl, J.V., A.V. Poelgeest-Eeltink, and L. Shortridge-Baggett, The psychometric properties of the diabetes management self-efficacy scale for patients with type 2 diabetes mellitus. J Adv Nurs, 1999. 30 (2): p. 352-9. Polonsky, W.H., et al., Assessing psychosocial distress in diabetes: development of the diabetes distress scale. Diabetes Care, 2005. 28 (3): p. 626-31. Mokhlesi, S., et al., Quality of life questionnaire for women with gestational diabetes mellitus (GDMQ-36): development and psychometric properties. BMC Pregnancy and Childbirth, 2019. 19 (1): p. 454. Polonsky, W.H., et al., Assessment of diabetes-related distress. Diabetes Care, 1995. 18 (6): p. 754-60. Boateng, G.O., et al., Best Practices for Developing and Validating Scales for Health, Social, and Behavioral Research: A Primer. Frontiers in public health, 2018. 6 : p. 149-149. Harris, P.A., et al., Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics support. Journal of Biomedical Informatics, 2009. 42 (2): p. 377-381. Bonevski, B., et al., Evaluation of an instrument to assess the needs of patients with cancer. Supportive Care Review Group. Cancer, 2000. 88 (1): p. 217-25. Australian Bureau of Statistics. Cultural diversity of Australia. Information on country of birth, year of arrival, ancestry, language and religion . 2022 [cited 2024 24th January]; Available from: https://www.abs.gov.au/articles/cultural-diversity-australia. Westfall, P., & Henning, K.S.S., Understanding Advanced Statistical Methods (1st ed.). . 1 ed. 2013: Chapman and Hall/CRC. Yuan, K.-H. and P.M. Bentler, Asymptotic robustness of standard errors in multilevel structural equation models. Journal of Multivariate Analysis, 2006. 97 (5): p. 1121-1141. Tabachnick, B.G., & Fidell, L. S., Using Multivariate Statistics 6th ed. 2013, USA: Pearson Education. Bartlett, M.S., A Note on the Multiplying Factors for Various χ2 Approximations. Journal of the Royal Statistical Society. Series B (Methodological), 1954. 16 (2): p. 296-298. Hulland, J., Y.H. Chow, and S. Lam, Use of causal models in marketing research: A review. International Journal of Research in Marketing, 1996. 13 (2): p. 181-197. Bentler, P.M., EQS 6 structural equations program manual . 1989, Encino, CA: Multivariate Software, Inc. Bentler, P.M. and D.G. Bonett, Significance tests and goodness of fit in the analysis of covariance structures. Psychological bulletin, 1980. 88 (3): p. 588. Steiger, J.H., Structural model evaluation and modification: An interval estimation approach. Multivariate behavioral research, 1990. 25 (2): p. 173-180. Browne, M.W. and R. Cudeck, Alternative ways of assessing model fit. Sociological Methods & Research, 1992. 21 (2): p. 230-258. Cronbach, L.J., Coefficient alpha and the internal structure of tests. Psychometrika, 1951. 16 (3): p. 297-334. Kline, R., Exploratory and confirmatory factor analysis , in Applied quantitative analysis in education and the social sciences . 2013, Routledge. p. 171-207. Fornell, C. and D.F. Larcker, Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 1981. 18 (1): p. 39-50. Hair, J.F., C.M. Ringle, and M. Sarstedt, PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 2011. 19 (2): p. 139-152. Hair Jr, J., et al., Multivariate data analysis 4th ed. 1998, London: Prentice-Hall. Australian Insitute of Health and Welfare. Diabetes: Australian facts . 2024 [cited 2024 25th June]; Available from: https://www.aihw.gov.au/reports/diabetes/diabetes/contents/how-common-is-diabetes/gestational-diabetes. Australian Bureau of Statistics. Regional population growth Australia . Cat. no. 3218.0 2019 [cited 2024 19th December]; Available from: https://www.abs.gov.au/statistics/people/population/migration-australia/latest-release#data-download. . Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7209307","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":490571113,"identity":"9ff52c44-52f7-4ac8-8bbd-ae328942c3d3","order_by":0,"name":"Cathy Knight-Agarwal","email":"","orcid":"https://orcid.org/0000-0003-0121-4900","institution":"Faculty of Health, University of Canberra","correspondingAuthor":false,"prefix":"","firstName":"Cathy","middleName":"","lastName":"Knight-Agarwal","suffix":""},{"id":490575489,"identity":"0aa57217-c225-44d6-8b05-a1514dc13772","order_by":1,"name":"Abu Saleh","email":"","orcid":"https://orcid.org/0000-0002-9889-1512","institution":"Canberra Business School, University of Canberra","correspondingAuthor":false,"prefix":"","firstName":"Abu","middleName":"","lastName":"Saleh","suffix":""},{"id":490575490,"identity":"31b887bb-35cf-473e-bb42-0e4640cf5fdd","order_by":2,"name":"Mary-Ellen Hooper","email":"","orcid":"https://orcid.org/0000-0003-1864-4739","institution":"Faculty of Health, University of Canberra","correspondingAuthor":false,"prefix":"","firstName":"Mary-Ellen","middleName":"","lastName":"Hooper","suffix":""},{"id":490575491,"identity":"018c4c64-9dd1-41fc-b34d-72bf3410ff72","order_by":3,"name":"Indira Samarawickrema","email":"","orcid":"https://orcid.org/0000-0003-4659-170X","institution":"Faculty of Health, University of Canberra","correspondingAuthor":false,"prefix":"","firstName":"Indira","middleName":"","lastName":"Samarawickrema","suffix":""},{"id":490575492,"identity":"57e6d6fb-92f4-4cde-a4bb-537d0c1e227f","order_by":4,"name":"Vivienne Lewis","email":"","orcid":"https://orcid.org/0000-0002-9261-1276","institution":"Faculty of Health, University of Canberra","correspondingAuthor":false,"prefix":"","firstName":"Vivienne","middleName":"","lastName":"Lewis","suffix":""},{"id":490575493,"identity":"cc0d94ed-1b65-4c48-a5dd-a017c7a66042","order_by":5,"name":"Rati Jan","email":"","orcid":"https://orcid.org/0000-0003-0915-4420","institution":"School of Health Sciences and Social Work, Griffith University","correspondingAuthor":false,"prefix":"","firstName":"Rati","middleName":"","lastName":"Jan","suffix":""},{"id":490575494,"identity":"d9b6e5b0-089b-43ab-8fb2-5ad801ec9baf","order_by":6,"name":"Christopher J. Nolan","email":"","orcid":"https://orcid.org/0000-0002-6964-3819","institution":"School of Medicine and Psychology, Australian National University and Department of Endocrinology, The Canberra Hospital, Canberra, ACT","correspondingAuthor":false,"prefix":"","firstName":"Christopher","middleName":"J.","lastName":"Nolan","suffix":""},{"id":490575495,"identity":"cb97df81-ad76-49f8-a01f-ae7aee6b575d","order_by":7,"name":"Deborah Davis","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0002-2041-1064","institution":"ACT government Health Directorate and Faculty of Health, University of Canberra","correspondingAuthor":true,"prefix":"","firstName":"Deborah","middleName":"","lastName":"Davis","suffix":""}],"badges":[],"createdAt":"2025-07-25 01:30:19","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7209307/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7209307/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88011035,"identity":"7f906e56-35b4-489d-a7ef-22e992a76a3e","added_by":"auto","created_at":"2025-07-31 11:59:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1644807,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7209307/v1/81034cee-59ae-403a-9802-2c711ed26e23.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eDevelopment and validation of the Gestational Diabetes Mellitus Holistic Healthcare Needs Scale\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGestational Diabetes Mellitus (GDM) is one of the most common complications of pregnancy [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], characterised by glucose intolerance occurring with onset or first recognition during pregnancy [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e–\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. It is one of the fastest growing types of diabetes both in Australia and internationally [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The prevalence of GDM is estimated at around 14% of pregnancies worldwide, with ranges from 1–36% largely due to a lack of uniformly implemented diagnostic measures [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].However, in Australia and in many high-income nations, its prevalence is around 15% of pregnancies [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The number of women diagnosed with GDM continues to rise, tripling in the last 10 years, largely secondary to adoption of new diagnostic criteria in some nations [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], as well as increased numbers of higher-risk women due to rising average maternal age, higher rates of overweight and obesity and in some countries migration that is altering population demographics [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRisk factors for the development of GDM include having a family history of type 2 diabetes mellitus (T2DM), pre-existing insulin resistance, higher body mass index (BMI) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], polycystic ovarian syndrome, advanced maternal age, having a previous large for gestational weight baby, and being from a disadvantaged group [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e–\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. GDM is more likely to occur and have adverse health outcomes for women from culturally and linguistically diverse (CALD) backgrounds in particular, women from East, South and Southeast Asia; Indian subcontinent; Australian First Nations; Pacific Islander; Māori; middle eastern; non-white African; and South/Latina American women [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA pregnancy affected by GDM is associated with higher rates of adverse pregnancy outcomes and poorer longer-term health for both mother and babies. Adverse pregnancy outcomes for the babies include pre-term birth, macrosomia, birth trauma including from shoulder dystocia, neonatal hypoglycaemia and neonatal respiratory distress [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Women are also more likely to experience gestational hypertensive disorders including pre-eclampsia, in addition to receiving birth interventions such as induction of labour or caesarean section. Post partum such women have a higher chance of experiencing difficulties breastfeeding [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In the longer term, women have an increased risk of a GDM diagnosis in subsequent pregnancies and a 60% life-time risk of developing T2DM [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], as well as an increased risk in developing cardiovascular diseases [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Babies born to women with GDM are also more likely to have difficulty in maintaining a recommended body mass index (BMI) and have an increased risk of developing cardiometabolic disease, including T2DM and heart disease, later in life [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eResearch suggests that the risks and comorbidities associated with GDM can be significantly reduced with lifestyle changes, such as diet and physical activity, together with monitoring of blood glucose levels (BGLs) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Despite these initiatives, approximately 15–30% of women will require pharmacological glucose lowering medication such as insulin [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, women report challenges associated with managing GDM and describe psychological distress, particularly as they navigate the demands of significant lifestyle changes alongside the demands of pregnancy. Women have reported feeling denial, fear, shock and guilt associated with their GDM diagnosis [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This is further impacted by a loss of normality and personal control [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], with some women feeling as though their needs are diminished by health professionals (HP’s) who have a primary focus on the fetus [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe unmet needs of women have been described in several publications, particularly in relation to the psychosocial impacts of GDM, as well as access to information, guidance, and support in managing the condition [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Research indicates that women of ethnic minority groups experience high levels of unmet need leading to disengagement, lack of understanding and poor compliance with recommendations [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Women desire person-centred care, with a need for management to be more holistic and not focused solely on clinical measures and outcomes [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe ability to measure the degree to which our services address the needs of the population it serves, is important to service providers and policy makers to ensure the design and delivery of services are meeting their needs. A review of the literature revealed several instruments that are useful for measuring different aspects of the diabetes experience including the Diabetes Management Self-Efficacy Scale (DMSES) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], the Diabetes Distress Scale [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], Quality of Life questionnaire GDM – GDMQ-36 [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] and Problem Areas In Diabetes Scale (PAID)[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. These instruments, however, are not specific to women with GDM who have a broader range of healthcare needs. Little is known about the quality of services provided to women with GDM and the extent to which they meet the unique needs of women with GDM. Thus, we have developed the GDM Holistic Healthcare Needs (GDM:HHN) Scale following best practice methods [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. We anticipate that this will make a useful contribution to the evaluation and development of services for women with GDM.\u003c/p\u003e"},{"header":"Subjects, Materials, Methods","content":"\u003cp\u003eThe GDM:HHN scale was developed in 3 stages of item development (stage 1), scale development (stage 2), and scale evaluation (stage 3), following Boateng et al [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn \u003cb\u003estage one\u003c/b\u003e, items were developed following the conduct of two systematic reviews: one a meta synthesis of qualitative studies focusing on the holistic healthcare needs of women with GDM [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]; and the other an integrative review of the needs of women with GDM from CALD communities in high income settings [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This resulted in the development of items under 5 domains: psychological; education and information; health services; diet and lifestyle; and social and personal. In this stage, content validity was assessed with a panel of experts comprising healthcare professionals (diabetes educator, midwife, endocrinologist, obstetrician, dietitian) (\u003cem\u003en\u003c/em\u003e = 5) and women with experience of GDM (\u003cem\u003en\u003c/em\u003e = 13). The expert panel members were asked to rate each item for relevance and clarity using a four-point Lickert Scale (strongly agree to strongly disagree) in an online survey using the REDCap electronic data capture tool hosted at the University of Canberra [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. A content validity index for each item (i-CVI) was calculated by dividing the total number of experts rating each item as either 3 or 4 (strongly agree or agree item is relevant) and dividing this by the total number of experts. A i-CVI above 70% was considered acceptable [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn \u003cb\u003estage two\u003c/b\u003e, face validity was undertaken using cognitive interviews. Cognitive interviews involve the administration of the draft survey questions to a sample of the target population, asking them to verbalize their thought process while responding [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. This ensures that: the questions produce intended data; confusing or problematic questions can be modified; response options are appropriate; questions are culturally sensitive; and the items comprehensively address the intended topic. The response options were borrowed from the Supportive Care Need Scale [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] which are used widely in cancer services to identify unmet need. These options were: not applicable or no need; low need; moderate need; high need.\u003c/p\u003e\u003cp\u003eInterviews were conducted with women with a recent history of GDM. Responses were noted in a table by the interviewer and responses to all interviews were considered by the research team with amendments made as required. The resulting questionnaire was then translated into Simple Chinese, Hindi, Urdu, and Punjabi (forwards and backwards by qualified translators), these being the language groups of CALD women most affected by GDM in Australia and where English language capacity is lowest [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Five surveys were created in REDCap, one in each of the five languages included.\u003c/p\u003e\u003cp\u003eIn \u003cb\u003estage three\u003c/b\u003e, scale evaluation was undertaken. All women diagnosed with GDM in Australia are enrolled with the National Diabetes Services Scheme (NDSS). An email invitation was sent to a random sample of 19, 604 enrolled women with GDM, in five languages with links to the survey in REDCap. The inclusion criteria for participation were: 1) pregnant with GDM; 2) at least 34 weeks gestation; and 3) receiving healthcare in Australia. The survey was sent on 4th of May 2023 with a reminder sent 10 days later. The NDSS was unable to target women who were at least 34 weeks gestation, so the email was sent to all enrolled women with GDM. Screening questions established eligibility to participate.\u003c/p\u003e\u003cp\u003e\u003cb\u003eValidation of the GDM: HHN Scale\u003c/b\u003e\u003c/p\u003e\u003cp\u003eInitially, descriptive statistics, frequency analysis, and missing value identification was undertaken. Normality for individual items was examined using a kurtosis value of \u0026gt; 3.00 (non-normality) [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] and multivariate normality was assessed using a kurtosis value of \u0026gt; 5.00 (non-normality) [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Based on the recommendations of Tabachnick [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], data from participants with ≥ 80% missing responses were excluded and responses with 1 to 4 missing values were replaced with the respective scale mean value. Univariate outlier assessment was undertaken using standardized \u003cem\u003ez\u003c/em\u003e-scores of ± 2.29. Multivariate outliers were identified using Mahalanobis distance scores greater than χ\u003csup\u003e2\u003c/sup\u003e(6) = 22.46 (p \u0026lt; .001).\u003c/p\u003e\u003cp\u003eExploratory Factor Analysis (EFA) on the complete dataset with Varimax rotation was conducted. The Bartlett Test of Sphericity (agreeable if p \u0026lt; 0.05) and the Kaiser–Meyer–Olkin measure of sampling adequacy (≤ 0.50 poor-≥0.90 excellent) were examined to verify the uni-dimensionality of the constructs [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. The number of factors to be retained was determined from scree plots of the Eigenvalues. The items that substantially contributed to a given factor were selected based on their loading of \u0026gt; 0.7 [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSingle factor analysis using structural equation modelling (SEM) provided insight regarding individual scale items and their coherency thus signalling the degree of support for the overall model [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Our study evaluated model fit statistics including: Chi-square value/Degree of Freedom (CMIN/DF) (χ2/df: \u0026lt; 2.00 desirable for around 200 sample); Incremental Fit Index (IFI): \u0026gt;.90; Tucker-Lewis index (TLI): \u0026gt;0.90; Comparative Fit Index (CFI): \u0026gt;0.90; Root Mean Squared Error Approximation (RMSEA) (≤ 0.08) [\u003cspan additionalcitationids=\"CR41 CR42\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e–\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. These were followed if goodness-of-fit indices either met or exceeded the ‘acceptable’ cut-off norms. Standardized loadings for the scale items, variance of the items, critical ratios (T-value), error covariance and modification indices were also assessed when evaluating model fit. To achieve model fit indices, error covariance and inclusion of items that provided solutions, if theoretically reasonable, were also included.\u003c/p\u003e\u003cp\u003eBefore undertaking further investigation, a series of Cronbach's Alpha tests, [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] based on standardized items, were conducted to assess internal consistency of the measures. The verified items under single factor analyses showed excellent scores exceeding the recommended threshold of 0.70 for all constructs. The next and final step of the scale validation process was Confirmatory Factor Analysis (CFA). High error covariance and redundancy of used items in the same or different constructs were identified via assessment of modification indices, covariance structure and standardized factor loading scores [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Convergent validity was measured by calculating Average Variance Extracted (AVE) and assessment of Composite Reliability (CR) for each of the constructs [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. The recommended AVE ≥ 0.50 exhibited adequate convergent validity, meaning that the latent factor explains more than half of its indicators’ variance. A composite reliability \u0026gt; 0.70 signified acceptability as well as the degree to which measurement indicators reveal the latent factor [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eStatistical analysis and ethics\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAll analyses were performed using IBM SPSS version 22.0 and AMOS version 24.0. All hypothesis tests were two-tailed with a type I error rate fixed at 0.05. Ethics approval for all stages of the study was obtained from the University of Canberra Human Research Ethics Committee in March 2022 (approval number 2022:11518).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eScale development\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn \u003cb\u003estage one\u003c/b\u003e, 135 items were established following a review of the literature. By addressing duplication, the research team reduced this to 71 items under 5 domains: psychological; education and information; healthcare services; diet and lifestyle; and social and personal. After expert assessment by HPs (diabetes educator, midwife, endocrinologist, obstetrician, dietitian) (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5) and women with experience of GDM (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;13), four items were deemed irrelevant (CVI\u0026thinsp;\u0026lt;\u0026thinsp;69%) and removed, leaving 67 items. Assessment of Chronbach\u0026rsquo;s Alpha reduced the items by a further 35. The research team considered the large number of items deleted at this stage and sought to balance parsimony with comprehensiveness. Given that the instrument was going to be further tested with a large sample of women, the decision was made to re-introduce select items based on the team\u0026rsquo;s experience as healthcare professionals and literature reviews. This resulted in the re-introduction of 9 items giving a total of 41.\u003c/p\u003e\u003cp\u003eIn \u003cb\u003estage two\u003c/b\u003e, cognitive interviews were conducted with 11 women with a recent history of GDM. After consideration by the research team, 5 domains remained (\u0026ldquo;diet and lifestyle\u0026rdquo; was renamed \u0026ldquo;managing GDM\u0026rdquo;) with some items deleted, others added, and many re-worded, resulting in a total of 43 items.\u003c/p\u003e\u003cp\u003eIn \u003cb\u003estage three\u003c/b\u003e the scale was administered to women with GDM. Characteristics of the 342 women who participated are presented in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. All states and territories of Australia are represented. Almost half the women were multiparous, and the vast majority were partnered (married or de facto). A high proportion of participants were well educated with degree qualifications.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eParticipant characteristics\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e342 total responses\u003c/p\u003e\u003cp\u003eMEAN (SD) / n (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean age\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34.47 (4.59)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean gestation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36.7 (2.80)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean gestation at diagnosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.3 (5.67)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMultiparous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e169 (49.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimiparous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e172 (50.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMissing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFirst GDM diagnosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147 (43)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22 (6.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMissing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e173 (50.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eState/territory of residence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNSW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e114 (32.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVIC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e92 (26.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28 (8.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28 (8.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (0.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQLD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e59 (16.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eACT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23 (6.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTAS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (0.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAboriginal and or Torres Strait Islander\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (2.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLanguage spoken at home\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eArabic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (0.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCantonese\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (0.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEnglish\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e282 (82.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHindi\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (2.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItalian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (0.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMandarin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15 (4.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePunjabi\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (2.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSpanish\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVietnamese\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (0.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20 (5.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMissing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh school or lower\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33 (9.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrade/diploma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e58 (16.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDegree/higher degree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e244 (71.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (1.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMissing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (0.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRelationship status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarried/de facto\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e326 (95.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSingle/divorced/separated/widowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12 (3.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMissing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (1.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealthcare support*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo healthcare card\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e302 (88.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVeteran White Card or Healthcare Card\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39 (11.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMissing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e*In Australia a Health Care Card or Veteran White Card provides the recipient with concessions, subsidies or free access to some health care and other essential services.\u003c/p\u003e\u003cp\u003e\u003cb\u003eScale validation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eExploratory Factor Analysis (EFA) on the complete dataset with Varimax rotation showed most items aligned under 7 factors (see Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Two items failed to meet the threshold of 0.4 (HEI 11 and MGDM 7) indicating that their contribution to the factor was not substantial [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Items aligning to factor five were clearly focused on culture while those aligning with factor 7 did not have a coherent focus. Thus, items HEI9, HEI10, HS1, MGDM5, MGDM8 were used to form a new domain (factor), culture. Furthermore, variances of each factor were established as 12.87% (PSY), 12.21% (HEI), 12% (HS), 10.80% (MGDM), 8.41% (SP), 7.39% (C) and all six factors explained 69.13% of the variance in the 29 included items suggesting the extent to which the overall model captures the variability within the data.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eExploratory Factor Analysis (Matrix)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eScale Items\u003c/p\u003e\u003cp\u003e\u0026reg;\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e\u003cp\u003ePsychological\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePSY1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHelp in coping with the initial shock of your GDM diagnosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e.751\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePSY2\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHelp in dealing with fears for the health of you or your baby because of GDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e.751\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePSY3\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHelp in dealing with guilt associated with being diagnosed with GDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e.753\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePSY4\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGetting emotional support from your care providers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e.639\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePSY5\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHelp to feel positive about your pregnancy despite GDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e.664\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePSY6\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHelp to use the diagnosis as an opportunity to lead a healthier life\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e.507\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHealth Education and Information\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHEI1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInformation to enable you to fully understand the impact of GDM on your pregnancy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e.436\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e.472\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHEI2\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInformation to enable you to fully understand the tests and procedures recommended during pregnancy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e.492\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHEI3\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInformation to enable you to fully understand the diabetic diet recommended for pregnancy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e.581\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHEI4\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInformation to enable you to fully understand the recommended physical activity levels during pregnancy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e.466\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e.516\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHEI5\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInformation to enable you to fully understand medications or injections needed to manage your GDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e\u003cb\u003e.623\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHEI6\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInformation to enable you to fully understand recommendations for how you labour and give birth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e.625\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHEI7\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInformation to enable you to fully understand tests and procedures recommended for your baby after birth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e.779\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHEI8\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInformation to enable you to make informed decisions about infant feeding (breast or formula) after your baby is born\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e.701\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHEI9\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInformation about managing GDM that takes account of your culture\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e.704\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHEI10\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInformation provided in a language or words that you can understand\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e.583\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e\u003cb\u003e.509\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHEI11\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInformation to enable you to fully understand tests and procedures recommended for you after discharge from hospital related to GDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHEI12\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInformation about maintaining a healthy diet and exercise patterns after your baby is born\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e.666\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHEI13\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInformation to enable you to fully understand tests and procedures recommended for you after discharge from hospital related to GDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e.739\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHEI14\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInformation about maintaining a healthy diet and exercise patterns after your baby is born\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e.622\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHealth Services\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHS1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHaving your spiritual and/or religious needs acknowledged by your healthcare providers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e.724\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHS2\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGetting the care you need; at the time you need it\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e.546\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHS3\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConsistent information and advice from different healthcare providers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e.643\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHS4\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHaving trust and confidence in your healthcare providers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e.726\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHS5\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHealthcare providers that respect your values, beliefs and/or culture\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e.548\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e.505\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHS6\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHaving a say in how your GDM is managed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e.738\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHS7\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHaving choices about the way you labour and give birth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e.783\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHS8\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFeeling in control of the decisions about your pregnancy and birth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e.808\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHS9\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNot always feeling 'high risk'\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e.610\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eManaging GDM\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMGDM\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGuidance to enable you to meet the dietary recommendations for GDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e.755\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMGDM\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGuidance to enable you to eat at restaurants and enjoy social outings\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e.707\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMGDM\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGuidance to help you manage your GDM diet alongside the family meal schedule\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e.752\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMGDM\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGuidance to help you manage your GDM with a busy schedule\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e.651\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMGDM\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGuidance about diet that includes foods important to your culture or personal preferences\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e.481\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e.625\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMGDM\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGuidance in self-administration of insulin injections or taking medicine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cb\u003e.676\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMGDM\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eResources such as a diary to record your blood glucose levels, food intake and medications\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMGDM\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e8\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGuidance for managing GDM that takes your culture and lifestyle into consideration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e.687\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMGDM\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGuidance on meeting the recommended levels of physical activity in pregnancy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e.503\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSocial and Personal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSP1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSupport from your family to manage your GDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e\u003cb\u003e.503\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSP2\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKnowledge of programs in the community that might be helpful to you\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e\u003cb\u003e.405\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSP3\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHaving friends/colleagues accommodate your needs in relation to managing your GDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e\u003cb\u003e.687\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSP4\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCommunicating with other women who also have GDM (online or other)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e\u003cb\u003e.649\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSP5\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePositive reinforcement from family/friends about the things you are doing well to manage your GDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e\u003cb\u003e.675\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThere were some scores above 0.4 sitting in the different factors indicating either cross loading or miss alignment with the domain (factor) to which they were allocated prior to factor analysis. These were subject to further verification under single or confirmatory factor analyses. As a recommended sequence, the next step was to check each of the single factor analysis using the AMOS statistical package.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSingle Factor analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the factor loading scores for each of the constructs showing reasonable fit indices. Psychological (PSY) measure shows good fit with 4 items (excluding item 4 and 6) and excellent factor loading. Health Education and Information (HEI) measure has 14 items. Eight items show coherent and reasonable factor loading with very good model fit. Heath Service (HS) measure has nine items. Five items excluding items 1, 5, 7, and 8 show very good fit with excellent factor loading. Managing GDM (MGDM) measure has nine items. Five items excluding items 6, 7, 8, 9 revealed excellent model fit and factor loading. Social and personal (SP) items show very good fit and factor loading excluding item number 4. Some of these excluded factors loaded well but they show co-sharing of co-variance with some of the measurement items in each of the single measures. Investigation of the covariance structure in the Modification Indices (Mis) section of these construct measures specifically suggested that at least one or more modification was necessary due to associated misspecification. The expected change statistics of error covariances also revealed that there were misspecifications associated with those of the items. Finally, excluding such problematic items and comparison of initial analysis/findings of each construct measure clearly suggest that some of those items were responsible for the poor fit to the model and they were finally excluded from the analyses to achieve the recommended and acceptable overall model fit to the data. Nonetheless, some of the measures, for example, the measure for culture (C) fitted very well without any recommended modifications.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSingle models- Standardized Factor Loading\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScale items\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEstimate (β value)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLevel of significance\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003ePsychological\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSY1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.856\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSY2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.895\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSY3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.821\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSY5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.783\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eModel fit statistics\u003c/b\u003e: CMIN/DF\u0026thinsp;=\u0026thinsp;1.68; IFI\u0026thinsp;=\u0026thinsp;.99; TLI\u0026thinsp;=\u0026thinsp;.99 CFI\u0026thinsp;=\u0026thinsp;.99; RMSEA\u0026thinsp;=\u0026thinsp;0.045\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHealth Education and Information\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHEI2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.815\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHEI4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.748\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHEI5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.645\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHEI6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.765\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHEI8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.696\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHEI11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.689\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHEI12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.795\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eModel fit statistics\u003c/b\u003e: CMIN/DF\u0026thinsp;=\u0026thinsp;2.46; IFI\u0026thinsp;=\u0026thinsp;.98; TLI\u0026thinsp;=\u0026thinsp;.97 CFI\u0026thinsp;=\u0026thinsp;.98; RMSEA\u0026thinsp;=\u0026thinsp;0.065\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHealth Services\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHS2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.734\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHS3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.851\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHS4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.899\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHS6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.757\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHS9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.658\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eModel fit statistics\u003c/b\u003e: CMIN/DF\u0026thinsp;=\u0026thinsp;3.10; IFI\u0026thinsp;=\u0026thinsp;.99; TLI\u0026thinsp;=\u0026thinsp;.97 CFI\u0026thinsp;=\u0026thinsp;.99; RMSEA\u0026thinsp;=\u0026thinsp;0.078\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eManaging GDM\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMGDM1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.762\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMGDM2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.842\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMGDM3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.938\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMGDM4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.886\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eModel fit statistics\u003c/b\u003e: CMIN/DF\u0026thinsp;=\u0026thinsp;8.27; IFI\u0026thinsp;=\u0026thinsp;.99; TLI\u0026thinsp;=\u0026thinsp;.96 CFI\u0026thinsp;=\u0026thinsp;.99; RMSEA\u0026thinsp;=\u0026thinsp;0.11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSocial and Personal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.740\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.516\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.705\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.821\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eModel fit statistics\u003c/b\u003e: CMIN/DF\u0026thinsp;=\u0026thinsp;5.48; IFI\u0026thinsp;=\u0026thinsp;.97; TLI\u0026thinsp;=\u0026thinsp;.93 CFI\u0026thinsp;=\u0026thinsp;.97; RMSEA\u0026thinsp;=\u0026thinsp;0.11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCulture\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.692\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.501\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.552\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.813\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.878\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eModel fit statistics\u003c/b\u003e: CMIN/DF\u0026thinsp;=\u0026thinsp;3.76; IFI\u0026thinsp;=\u0026thinsp;.98; TLI\u0026thinsp;=\u0026thinsp;.96 CFI\u0026thinsp;=\u0026thinsp;.98; RMSEA\u0026thinsp;=\u0026thinsp;0.09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eConvergent and discriminant validity\u003c/b\u003e\u003c/p\u003e\u003cp\u003eEFA and CFA produced robust evidence that scale items were discriminant explaining the entire theoretical phenomenon including reasonable factor loading scores and model fit statistics.\u003c/p\u003e\u003cp\u003eAdditional analyses using χ\u003csup\u003e2\u003c/sup\u003e/df in one degree of freedom provided further evidence of convergent and discriminant validities. See Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The analyses demonstrate that all constrained models/constructs are significantly different from the unconstrained models/constructs which suggests that individual constructs are converged and discriminant from each of them.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eResults of the χ\u003csup\u003e2\u003c/sup\u003e difference test for all theoretically related constructs\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eModels\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e (d.f.)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e (d.f.)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e Differences (d.f.)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCulture \u0026dArr;\u0026loz; HEI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e178.60(53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnconstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e147.15(52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e31.45(1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCulture \u0026dArr;\u0026loz; HS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134.07(34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnconstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e86.19(33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e47.88(1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCulture \u0026dArr;\u0026loz; SP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e114.69(26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnconstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e56.60(25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e58.09(1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCulture \u0026dArr;\u0026loz; PSY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e84.32(26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnconstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e49.85(25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e34.47(1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCulture \u0026dArr;\u0026loz; MGDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e93.35(26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnconstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e60.79(25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e32.56(1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHEI \u0026dArr;\u0026loz; HS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e165.11(54)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnconstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e140.97 (53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e24.14(1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHEI \u0026dArr;\u0026loz; SP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e164.82(44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnconstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e122.54(43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e42.28(1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHEI \u0026dArr;\u0026loz; PSY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e88.44(44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnconstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e78.87(43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9.57(1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHEI\u0026dArr;\u0026loz; MGDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e195.75(44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnconstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e171.04(43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e24.71(1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHS \u0026dArr;\u0026loz; SP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e180.52(27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnconstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e123.73(26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e56.79(1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHS \u0026dArr;\u0026loz; PSY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e101.06(27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnconstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e83.86(26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e17.20(1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHS \u0026dArr;\u0026loz; MGDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e131.77(27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnconstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e97.20(26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e34.57(1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP \u0026dArr;\u0026loz; PSY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e102.85(20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnconstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e65.55(19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e37.30(1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP \u0026dArr;\u0026loz; MGDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e118.83(20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnconstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e68.86(19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e49.97(1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSY \u0026dArr;\u0026loz; MGDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68.52(20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnconstrained\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e44.66(19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e23.86(1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eConfirmatory factor analysis (CFA)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOn confirming convergent and discriminant validities of the measures, the next sequential step was to conduct confirmatory factor analysis which is a robust approach to validate the construct measures. This analysis of validation produces factor loading and CFA model fit statistics using thresholds for the acceptable range of factor loadings scores (\u0026gt;\u0026thinsp;.4) and CFA model fit statistics (CMIN/DF; CFI; TLI; IFI and RMSEA).\u003c/p\u003e\u003cp\u003eConfirmatory Factor analysis was conducted using all retained items (based on single factor analyses). The analysis revealed parsimonious fit to the data/measurement model with satisfactory factor loadings. CFA results can be seen in Table \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCFA factor loading scores.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFactors/Measures\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eScale Items\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEstimate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLevel of significance\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003ePsychological\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eAR\u0026thinsp;=\u0026thinsp;.91\u003c/p\u003e\u003cp\u003eAVE\u0026thinsp;=\u0026thinsp;.71\u003c/p\u003e\u003cp\u003eCR\u0026thinsp;=\u0026thinsp;.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePSY1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.854\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePSY2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.891\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePSY3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.813\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePSY5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.802\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHealth Education and Information\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e\u003cp\u003eAR\u0026thinsp;=\u0026thinsp;.89\u003c/p\u003e\u003cp\u003eAVE\u0026thinsp;=\u0026thinsp;.54\u003c/p\u003e\u003cp\u003eCR\u0026thinsp;=\u0026thinsp;.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHEI2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.810\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHEI4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.745\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHEI5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.647\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHEI6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.769\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHEI8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.674\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHEI11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.717\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHEI12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.789\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHeath Service\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eAR\u0026thinsp;=\u0026thinsp;.89\u003c/p\u003e\u003cp\u003eAVE\u0026thinsp;=\u0026thinsp;.62\u003c/p\u003e\u003cp\u003eCR\u0026thinsp;=\u0026thinsp;.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHS2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.748\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHS3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.854\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHS4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.873\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHS6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.757\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHS9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.687\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eManaging GDM\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eAR\u0026thinsp;=\u0026thinsp;.92\u003c/p\u003e\u003cp\u003eAVE\u0026thinsp;=\u0026thinsp;.74\u003c/p\u003e\u003cp\u003eCR\u0026thinsp;=\u0026thinsp;.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMGDM1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.774\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMGDM2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.845\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMGDM3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.930\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMGDM4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.886\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSocial and personal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eAR\u0026thinsp;=\u0026thinsp;.79\u003c/p\u003e\u003cp\u003eAVE\u0026thinsp;=\u0026thinsp;.49\u003c/p\u003e\u003cp\u003eCR\u0026thinsp;=\u0026thinsp;.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSP1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.723\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSP2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.628\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSP3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.712\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSP5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.744\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCulture\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eAR\u0026thinsp;=\u0026thinsp;.83\u003c/p\u003e\u003cp\u003eAVE\u0026thinsp;=\u0026thinsp;.49\u003c/p\u003e\u003cp\u003eCR\u0026thinsp;=\u0026thinsp;.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHEI9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.699\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHEI10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.496\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHS1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.546\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMGDM5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.826\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMGDM8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.865\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCFA Model fit statistics\u003c/b\u003e: CMIN/DF\u0026thinsp;=\u0026thinsp;2.46; IFI\u0026thinsp;=\u0026thinsp;.92; TLI\u0026thinsp;=\u0026thinsp;.91 CFI\u0026thinsp;=\u0026thinsp;.92; RMSEA\u0026thinsp;=\u0026thinsp;0.065\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eNotes: Cronbach's Alpha Reliability\u0026thinsp;=\u0026thinsp;AR; Average variance extracted\u0026thinsp;=\u0026thinsp;AVE; Composite reliability\u0026thinsp;=\u0026thinsp;CR\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eGDM is the fastest growing type of diabetes globally and in Australia, health services are struggling to meet demand [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. While a variety of scales exist to measure the healthcare experiences and needs of people with diabetes, none focus on the unique needs of women with GDM. Therefore, we developed the Holistic Healthcare Needs Scale for women with GDM following a robust process.\u003c/p\u003e\u003cp\u003eThe final GDM: HHN Scale has six domains: psychological, health education and information, managing GDM, healthcare services, social and personal, and culture. These domains are well supported with evidence from our systematic reviews indicating unmet need in this population, over these domains [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe scale development followed best practice [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] and importantly involved both healthcare professionals and those with lived experience of GDM. Those with lived experience are best placed to identify their needs and the inclusion of healthcare professionals ensures the scale is useful and relevant also to healthcare providers. Our study used exploratory and confirmatory factor analysis, with results providing evidence that scale items were discriminant explaining the theoretical phenomena with reasonable factor loading scores and model fit statistics. Additional analysis provides evidence of convergent and discriminant validity.\u003c/p\u003e\u003cp\u003eThe GDM: HHN Scale has several strengths. The development and validation process were comprehensive and included input from multiple sources including contemporary literature, service users and providers. The questionnaire was translated into languages where women are most affected by GDM in Australia and where English language capacity is lowest [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. This helped to protect against instrument bias thus supporting its applicability across a wide range of settings. Next, a rigorous step by step statistical analysis was undertaken including descriptive statistics, EFA and CFA.\u003c/p\u003e\u003cp\u003eSeveral limitations of this study should be noted. Responders to the questionnaire are not representative of the population in Australia. Most were highly educated and despite efforts to recruit an ethnically diverse sample, most mainly spoke English at home. Selection bias may limit the generalizability of the findings presented here. As no other scales measure holistic healthcare needs in this population, criterion validity cannot be assessed.\u003c/p\u003e\u003cp\u003eLastly, this newly developed scale may better assess women\u0026rsquo;s unmet needs which, in turn, may enable healthcare providers to tailor their service with greater precision. Although the GDM: HHN Scale is a promising new instrument with evidence that it is valid and reliable, its psychometric properties and test characteristics need to be further investigated in larger and more diverse samples. It also would be valuable to assess its responsiveness to GDM associated interventions before it can be recommended for widespread use.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eGDM: HHN Scale is the first instrument designed to measure holistic health care needs of women with GDM. It demonstrates sufficient reliability and validity and as such, is a useful tool for healthcare providers to assess the quality of their services.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAll those participating in this study provided informed consent as detailed and approved by the relevant Human Research Ethics committee.\u003c/p\u003e\u003ch2\u003eFunding information\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThis study was funded by a grant from the University of Canberra, Australia. \u0026nbsp;The sponsors had no role in the design and conduct of the study or in the analysis data, interpretation of findings or approval of this manuscript.\u003c/p\u003e\n\u003ch2\u003eDeclaration of competing interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have influenced the work presented in this manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSweeting, A., et al., \u003cem\u003eEpidemiology and management of gestational diabetes.\u003c/em\u003e The Lancet, 2024. \u003cstrong\u003e404\u003c/strong\u003e(10448): p. 175-192.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. \u003cem\u003eDiagnostic criteria and classification of hyperglycaemia first detected in pregnancy. 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Cat. no. 3218.0 2019 [cited 2024 19th December]; Available from: https://www.abs.gov.au/statistics/people/population/migration-australia/latest-release#data-download. .\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Canberra","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"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},"keywords":"Gestational diabetes, holistic, unmet need, scale development, validation","lastPublishedDoi":"10.21203/rs.3.rs-7209307/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7209307/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eAims: \u003c/strong\u003eThis study aimed to develop and test a scale to measure the holistic healthcare needs of women with Gestational Diabetes Mellitus.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod\u003c/strong\u003e: The scale was developed through a three-stage process. In stage one, initial items were generated based on a review of current literature, followed by content validation with service users and healthcare professionals. Stage two involved assessing face validity through cognitive interviews with women diagnosed with gestational diabetes mellitus (GDM). In the final stage, the scale was evaluated using a sample of 342 women with GDM, recruited through the National Diabetes Services Scheme in Australia. Exploratory and confirmatory factor analyses were conducted to assess the scale’s structure, and its reliability and validity were examined including tests for convergent and discriminant validity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe final GDM Holistic Healthcare Needs Scale has 29 items within 6 domains; psychological, health education and information, managing GDM, healthcare services, social and personal, and culture. Variances of each factor explained were 12.87%, 12.21%, 12%, 10.80%, 8.41%, 7.39% and all six factors explained 69.13% of the variance in the 29 items. \u0026nbsp;Results of confirmatory factor analysis suggest that adequate fit indices were achieved within the recommended thresholds.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u0026nbsp;\u003c/strong\u003eThe GDM Holistic Healthcare Needs Scale shows adequate convergent and discriminant validity and reliability to measure the holistic healthcare needs of women with GDM.\u003c/p\u003e","manuscriptTitle":"Development and validation of the Gestational Diabetes Mellitus Holistic Healthcare Needs Scale","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-31 11:43:11","doi":"10.21203/rs.3.rs-7209307/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":"094d84a7-fd00-4557-b661-497090875dba","owner":[],"postedDate":"July 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":52431906,"name":"Obstetrics \u0026 Gynecology"},{"id":52431907,"name":"Sexual \u0026 Reproductive Medicine"}],"tags":[],"updatedAt":"2025-07-31T11:43:11+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-31 11:43:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7209307","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7209307","identity":"rs-7209307","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}