This article is open access. Learn more: What is Open Access?

ABSTRACT

Objective: Pregnancy-specific anxiety (PSA) is a distinct construct from general anxiety and depression. The purpose of this study was to develop, evaluate, and validate the Pregnancy-Specific Anxiety Tool (PSAT), to measure PSA and its severity.

Methods: The study was carried out in 2 stages. Stage 1 involved item development and content and face validation. Stage 2 included psychometric evaluation to examine item distributions and correlational structure, dimensionality, internal consistency reliability, stability, and construct, convergent, and criterion validity, using 2 independent samples (initial sample N = 494, May–October 2018; validation sample N = 325, July 2019–May 2020).

Results: Eighty-two items were evaluated for face validity and 41 items were considered in stage 2 based on feedback from participants and experts. Model fit from exploratory factor analysis and patterns of item-factor loadings suggested a 6-factor model with 33 items. The 6 factors included items pertaining to health and well-being of the baby, labor and the pregnant person’s well-being, postpartum, support, career and finance, and indicators of severity. Confirmatory factor analysis carried out using the initial sample showed good fit with the validation sample. The area under the curve (AUC) for the diagnosis of adjustment disorders (AD) was 0.73 (95% CI, 0.67–0.79), and for AD/any anxiety disorders, the AUC was 0.80 (95% CI, 0.75–0.85).

Conclusions: The PSAT can be useful for screening and monitoring of PSA, and pregnant people with scores higher than 10 should be considered for further assessment.

J Clin Psychiatry 2023;84(3):22m14696

To cite: Bayrampour H, Hohn RE, Tamana SK, et al. Pregnancy-Specific Anxiety Tool (PSAT): instrument development and psychometric evaluation. J Clin Psychiatry. 2023;84(3):22m14696.

To share: https://doi.org/10.4088/JCP.22m14696

© 2023 The Authors. Published by Physicians Postgraduate Press, Inc. This is an open access article under the CC BY-NC-ND license.

aDepartment of Family Practice, University of British Columbia (UBC), Vancouver, Canada
bDepartment of Psychology, Simon Fraser University, Vancouver, Canada
cDepartment of Pediatrics, University of British Columbia (UBC), Vancouver, Canada
dSchool of Nursing, Trinity Western University, Langley, Canada
eCentre for Health Evaluation and Outcome Science, Providence Health Care, Vancouver, Canada
fSchool of Population and Public Health, University of British Columbia (UBC), Vancouver, Canada
gDepartment of Obstetrics and Gynecology, University of British Columbia (UBC), Vancouver, Canada
hChildren’s and Women’s Hospital of British Columbia, Vancouver, Canada
*Corresponding author: Hamideh Bayrampour, MSc, PhD, Department of Family Practice, 320 – 5950 University Blvd, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada ([email protected]).

 

Pregnancy-specific anxiety (PSA) is defined as “nervousness and fear about the baby’s health, the mother’s health and appearance, experience with the health care system, social and financial issues in the context of pregnancy, childbirth, and parenting that are accompanied by excessive worry and somatic symptoms.”1(p121) Accumulating evidence indicates that PSA is a construct distinct from general anxiety and depression.2–6 In 2004, Huizink et al2 examined anxiety related to the baby’s health and childbirth at multiple points during pregnancy and found that depression and general anxiety explained only a small portion of the variance related to such anxiety during early and midpregnancy, with no associations in late pregnancy. PSA has stronger associations with biological markers (eg, shorter telomere length,7 higher rates of DNA methylation)8 and clinical outcomes (eg, postnatal mood disturbance, birth and early developmental outcomes).6,9–11 Despite its significance, measurement and diagnosis of PSA have been hindered by a paucity of valid assessment tools and clear diagnostic criteria. Based on the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), anxiety disorders share excessive worry/fear but vary in the type of cognition.12 The lack of specific items about cognition related to pregnancy in general or diagnostic measures of anxiety results in a significant proportion of pregnant people with elevated anxiety not meeting the required criteria.5 Furthermore, some measures rely heavily on somatic signs that overlap with physiological adjustments of normal pregnancy, leading to inappropriately inflated scores.9,13 A 2015 systematic review concluded that extant PSA measures2,4,14–17 lacked “sufficient scope and depth.”18(p31) For example, Levin’s Pregnancy Anxiety Scale (PAS)15 recognizes the multidimensional nature of the PSA and measures 3 domains including those related to anxiety about being pregnant, childbirth, and hospitalization. However, as Levin acknowledges, there are “missing dimensions”15 in this scale, as it does not include several known domains of PSA. Furthermore, this tool was designed to measure PSA retrospectively and not during pregnancy. Other scales designed to measure PSA, such as the Pregnancy-Related Anxiety Scale (P-RAS),17 the Pregnancy Outcome Questionnaire (POQ),4 the Pregnancy-Related Anxiety Questionnaire-Short,2 and the Pregnancy Anxiety Scale,16 each cover a variable number of PSA domains. Although the P-RAS17 covers a broader range of domains, it too misses several important domains. Furthermore, most items included in this scale pertain to anxiety about the fetus, and only 1 indicator addresses each of the other 4 domains, leading to concerns about the psychometric properties of the scale.17 A newly developed measure, the Pregnancy-related Anxiety Scale (PrAS),19 includes several domains of PSA, but does not assess partner support and financial concerns. The lack of indicators for assessing the severity of PSA is another limitation common to all the available scales.1 Severity classification is important, as mild anxiety is often transient and may represent a healthy response to ensure the safety of mother and child through pregnancy and childbirth. On the other hand, the severe anxiety is enduring and persistent and can impact a person’s ability to focus, relax, or function in daily responsibilities.20–22 The purpose of this study was to develop, evaluate, and validate a measurement tool to assess PSA and its severity.

METHODS

Study Design

This study was designed based on the principles required for developing Patient Reported Outcomes (PROs)23,24 and Patient Reported Outcome Measures (PROMs).25–28 The key steps in PROM development include identification of the conceptual framework, generation of items, content refinement, item reduction, scaling, and psychometric evaluation.25 This study involved 2 main stages: stage 1—item development (ie, item generation and content and face validation) and stage 2—scale development and evaluation (ie, examining the underlying dimensionality of the item set; identifying and eliminating redundant items or those not congruent with the construct being measured; and psychometric testing to establish test-retest and internal consistency reliability and construct, convergent, and criterion validity).

Stage 1: Item Development

The study was based on a conceptual framework developed through a comprehensive literature review that showed PSA to be a multidimensional construct with 9 domains (ie, anxiety about fetal health, fetal loss, childbirth, parenting and newborn care, mother’s well-being, body image, health care–related issues, financial issues, and family and social support); 2 attributes (ie, affective responses and cognitions); and 3 categories of consequences (ie, excessive reassurance-seeking, avoiding behaviors, and impact on daily function).1 This conceptual framework was shared at a multidisciplinary meeting, and feedback was elicited on the definition and domains of PSA, indicators of severity, timing of the assessment, appropriateness of inclusion of items related to sleep problems, and corresponding clinical diagnosis.

Item generation. Candidate items were generated based on an extensive literature review and items of previous scales deemed relevant in concept analysis1 as well as from the findings of a qualitative study.29 The qualitative study included 27 interviews with 15 pregnant persons and provided a person-identified base for item generation, particularly for severity and impact of anxiety on the pregnant person’s daily life (as such evidence is sparse in the literature).1 Using these approaches, 143 items were developed and grouped into 3 categories: severity of anxiety (40 items); confidence in managing the unknown/uncertainty related to pregnancy (10 items); and specific domains/cognition (93 items), including 11 subgroups: fetal health, loss of fetus, childbirth, pregnant person’s well-being, body image, parenting and care for the child, maternity care–related, financial, family and social support, general indicators, and impacts of person’s anxiety on the baby.

Content validation. Generated items were presented to a panel of 6 experts (per recommendation)30 to evaluate individual items for clarity and readability and rate each item for both clinical relevance and importance on a 4-point ordinal scale and to provide suggestions for new items.31 We computed a content validity index (CVI) to determine agreement among experts.32,33 Items were retained if the CVI on both relevance and importance exceeded 0.78.33 If an item met only 1 of the CVI requirements, the comments provided by the experts informed the deliberation on whether or not to retain the item. Based on CVI, a total of 75 items were retained. Although not meeting the CVI recommendation, 7 additional items were also retained based on further discussions with the experts. A total of 82 items were included for face validity evaluation: 30 items for severity of anxiety, 7 items for confidence in managing uncertainty related to pregnancy, and 45 items for specific domains and cognition. The expert panel recommended a Likert scale with 4 options for item presentation.

Pilot testing. We conducted a pilot test of the item pool to assess face validity and examine whether items were clearly expressed and were being interpreted correctly.34 Cognitive interviews were undertaken with 10 pregnant persons to determine respondent comprehension and identify potential problems in responding to items.25,35 Interviews were recorded and notes were taken on participants’ feedback on each item.

Stage 2: Instrument Development and Evaluation

For this stage, 2 samples were recruited: the first sample (development sample) was used to examine the initial structure of the Pregnancy-Specific Anxiety Tool (PSAT), and the second sample (validation sample) was used for psychometric testing and for conducting clinical diagnostic interviews.

Participants. As the PSAT is intended for use in the general population of pregnant people, we recruited nulliparous and multiparous pregnant people (age ≥ 19 years; able to read/write/speak English) at any gestational age. We chose a broad gestational range for two reasons: first, findings from a previous trajectory analysis suggest that despite slight fluctuations, symptoms of anxiety are consistent over the course of pregnancy36; second, research on time-specific effects of PSA shows that high levels of PSA at any time point in gestation can contribute to adverse pregnancy and child outcomes.37

Study procedures.

Sample 1. Participants for sample 1 were recruited from May 2, 2018, to October 11, 2018 (N = 494). Participants were recruited during pregnancy through study posters distributed in prenatal care clinics and classes, blood and other specimen collection laboratories across the province, and social media platforms. After signing an online informed consent form, participants completed the PSAT and a demographic and obstetrics characteristics questionnaire.

Sample 2. Participants were recruited from July 3, 2019, to May 18, 2020 (N = 325) using similar recruitment approaches. After signing an informed consent form, participants completed an online survey that included the Edinburgh Postnatal Depression Scale (EPDS),38 Generalized Anxiety Disorder Scale (GAD-7),39 State-Trait Anxiety Inventory (STAI-State),40 Perception of Pregnancy Risk Questionnaire (PPRQ),41 Perceived Stress Scale (PSS),42 Pregnancy-Related Anxiety Scale (P-RAS),17 PrAS,19 PSAT, and a demographic and obstetric characteristics questionnaire. To determine test-retest reliability, the participants completed the PSAT again 1 week later.34 PSS and PPRQ were used for hypothesis testing and further assessment of construct validity. We hypothesized that people who had higher PSAT scores would also have a higher perception of pregnancy risk (antecedent of PSA)1 and higher perceived stress. To examine convergent validity, we assessed associations of the PSAT with different measures of the PSA (ie, P-RAS, PrAS), which were expected to correlate highly with PSAT scores.43 Additionally, we measured relevant constructs of general anxiety and depression using the STAI-S, GAD-7, and EPDS.

After completion of the online survey, clinical diagnostic interviews were scheduled and occurred within 7 days of completing the PSAT self-report. A trained PhD-level psychologist (S.T.) conducted interviews in-person or through a phone/video call using the Structured Clinical Interview for DSM-5 (SCID-5),44 a validated semistructured diagnostic interview designed for assessment of a wide range of psychiatric problems, including all mood and anxiety disorders. According to DSM-5, for symptoms to meet the diagnostic criteria for a certain mental disorder, the disturbance must cause “clinically significant distress or impairment in social, occupational, or other important areas of functioning.”12(p21) Although the cognitive attributes of PSA are similar to those described in the DSM-5 for anxiety disorders, PSA may or may not be associated with behavioral responses or impaired functioning.1 Additionally, the criterion of a 6-month duration for generalized anxiety might not be practical for pregnancy. These considerations, and consultations with experts, led us to the understanding that the diagnostic category that corresponds most closely to PSA is adjustment disorder (AD). A current diagnosis of AD was made only if symptoms were present at the time of the interview. AD was also diagnosed as a comorbidity with another mental health disorder, as long as both criteria were met. Interrater agreement for AD diagnosis was assessed by randomly selecting a subset of the SCID-5 interviews (3 interviews) and having these reviewed by an experienced clinical psychologist blind to the assessment. Interviews were recorded to allow for a review in cases of diagnostic uncertainty. Participants who met diagnostic criteria for any mental health condition were offered appropriate referrals.

Data analysis. The primary focus of psychometric evaluations involved examining (a) the PSAT item distributions and correlational structure; (b) the implied dimensionality of the PSAT; (c) the internal consistency and stability (ie, test-retest reliability); and (d) the relationships between the PSAT and criterion validation measures.

Sample 1. To examine item distributions, we determined the relative frequencies of the response options for each item. Given the ordinal nature of the data, we observed the interitem relationships based on polychoric correlations. First, a scree plot was generated using the adjusted eigenvalues obtained from a parallel analysis (PA) using a common factor approach.45 Second, a series of 10 exploratory factor analyses (EFAs) was conducted that extracted 1 to 10 correlated factors, respectively. For each EFA, we observed the overall model fit to the data, the pattern of Geomin-rotated item-factor loadings and the presence of cross-loading items, as well as the correlations among factors. Third, confirmatory factor analysis (CFA) was fit to the data with model specification generated from both the EFA results and conceptual considerations. For all factor analyses, weighted least squares estimation with mean- and variance-adjustment (WLSMV) was used to accommodate the ordinal and non-normal characteristics of the items. Model fit was evaluated using comparative and Tucker Lewis fit indices (CFI and TLI, respectively), standardized root mean square residuals (SRMR), and the root mean square error of approximation (RMSEA). We were guided by conventional criteria for model fit assessment,46 although such criteria served only as rough guides given the ordinal nature of the data and use of WLSMV estimation.

Sample 2. An identical CFA was conducted to replicate the findings from the initial sample. Internal consistency was evaluated using ordinal coefficient α,47 based on the polychoric correlation matrix of the items, rather than from the scores directly. Test-retest reliability was evaluated at both the test and item levels by calculating the correlations between the PSAT scores across time points (> 0.70 considered acceptable).32 At the item level, weighted κ estimates were computed. Evidence of convergent validity was obtained by calculating the correlations between the PSAT scores and scores from the GAD-7, STAI-S, EPDS, PSS, PrAS, PPRQ, and P-RAS. To assess the criterion-related validity (diagnostic accuracy) of the PSAT, we plotted ROC curves and calculated indices for predictive performance (sensitivity, sensitivity, positive predictive value [PPV], negative predictive value [NPV], positive likelihood ratio [LR+], negative likelihood ratio [LR–] and the corresponding area under the curve [AUC], and 95% confidence intervals [CIs]). We determined a cutoff score that optimally detected the presence/absence of a current AD diagnosis based on the Youden index. In addition, we calculated values for the diagnostic performance of the PSAT for AD/any current anxiety disorders (ie, panic disorder, agoraphobia, social anxiety disorder, specific phobia, generalized anxiety disorder, separation anxiety disorder, other specified anxiety disorder, anxiety disorder due to another medical condition, and substance/medication induced anxiety disorder).

Pairwise deletion was employed for all analyses as missing data was very low. Sample characteristics were described using IBM SPSS. Other analyses were primarily conducted using version 4.1 of the R statistical programming language.48 The lavaan package49 was used to conduct the PAs and CFAs. The EFAs and polychoric correlations were obtained using Mplus version 8.4.50 This study was reviewed and approved by the University of British Columbia Conjoint Health Research Ethics Board (H16-02471).

RESULTS

Item Development

In stage 1, 10 pregnant persons were recruited for pilot testing and face validity assessment (Table 1). Participants’ feedback was reviewed by the research team and items were retained, revised, or removed. A total of 44 items were retained and were administered in stage 2, which included the recruitment of 2 independent samples. In this item pool, the specific cognitions category included 3 general anxiety items. These items were reviewed by the research team and were removed as these items did not capture cognition specific to pregnancy.1 Forty-one items were considered in stage 2 for the scale development and evaluation analyses (Supplementary Table 1). The majority of these items emerged from qualitative interviews and the literature review. Five items from 2 previous scales16,17 were retained and included with permission. A modified version of the postpartum preparation concerns item (in the avoidance domain, originated from a previous scale4 and revised in the process) was also retained in the final item pool.

Scale Development and Validation

Sample 1. Participants’ characteristics are presented in Table 1. To determine the initial structure of the PSAT, we conducted a series of psychometric evaluations, including a PA, 10 EFAs, and a CFA, using the initial 41 retained items. To reduce the number of items, we eliminated conceptually repetitive or overlapping items (8 items) and replicated all analyses using 33 items. These items included 3 items in the fetal health domain and 1 item in each of the sleep interruption, constant worries, avoidance, pregnant person’s well-being, and harm to the baby domains. The PA for the 33-item scale suggested the extraction of 8 factors. The examination of the model fit indices of the EFAs and their patterns of item-factor loadings showed that a 6-factor model (χ2345 = 562.8, P < .001, CFI = 0.979, TLI = 0.968, SRMR = 0.038, RMSEA = 0.037) best represented the PSA domains. Moreover, the 6-factor model did not represent a severe degradation of model fit compared to the 8-factor model (χ2292 = 404.089, P < .001, CFI = 0.989, TLI = 0.981, SRMR = 0.030, RMSEA = 0.029). The matrix of item-factor loadings for the 6-factor model also contained fewer cross-loading items (n = 4) than were observed in the 8-factor model (n = 9), where cross-loading items were defined as items that had loadings greater than or equal to 0.300 for multiple factors. The 4 cross-loading items (1 item each in childbirth, career/study, harm to the baby, and daily life/relationship interruptions subdomains; Supplementary Appendix 1) were evaluated by a PSA content expert (H.B.), who determined which factors the items should conceptually load on. For all cross-loading items, this corresponded to the items being assigned to the factors on which they loaded most strongly. The 6-factor model included the following factors: Severity, Health and Well-being of the Baby, Labor and Pregnant Person’s Well-being, Postpartum, Career and Finance, and Support. A CFA was then fit that used the model specification obtained from the 6-factor EFA. The CFA model fit the data well (χ2480 = 1,184.440, P < .001, CFI = 0.937, TLI = 0.931, SRMR = 0.071, RMSEA = 0.055) and resulted in loadings ranging from 0.526 to 0.907 (mean = 0.739, median = 0.757, SD = 0.105).

Sample 2. The CFA model obtained from sample 1 showed good fit for sample 2 data (χ2480 = 883.8, P < .001, CFI = 0.942, TLI = 0.937, SRMR = 0.080, RMSEA = 0.051) and a pattern and distribution of item-factor loadings that was similar to the first sample (mean = 0.728, median = 0.730, SD = 0.092, minimum = 0.520, maximum = 0.914). The item-factor loadings and item distributions are summarized in Table 2, and the model is shown in Figure 1.

To obtain the overall scale scores for the PSAT, we used a factor-averaged method,51 in which items are first averaged within each latent factor for every participant. The empirical distribution of the overall PSAT scores ranged from 6.39 to 18.54, encompassing much of the scale’s possible range from 6 to 24, with a mean score of 11.00 (median = 10.58, SD = 2.49). The PSAT scores were approximately normally distributed, with a slight positive skew. As a whole, the PSAT demonstrated a high degree of internal consistency (α = .93, 95% CI, 0.92–0.94)* and test-retest reliability (r12 = 0.83, P < .001, 95% CI, 0.80–0.86). Weighted-κ estimates obtained for each item (Table 2) ranged from 0.424 to 0.783 (mean = 0.597, median = 0.615, SD = 0.110), indicating that all individual items demonstrated “moderate” to “good” stability over time.52 Internal consistency estimates for the PSAT domains ranged from adequate to strong for Support (α = .73), Career and Finance (α = .75), Health and Well-being of the Baby (α = .84), Labor and Pregnant Person’s Well-being (α = .86), and Severity (α = .93), while the Postpartum (α = .69) domain estimate fell just short of the conventional threshold for adequate reliability. The PSAT correlations with criterion validation measures were significant and ranged from 0.397 to 0.827 (Table 3).

The AUC using PSAT for the diagnosis of AD was 0.73 (95% CI, 0.67–0.79), and for AD/any anxiety disorders the AUC was 0.80 (95% CI, 0.75–0.85; Figure 2). The optimal cutoff points calculated using the Youden index were 10.4 (sensitivity = 74%, specificity = 56%, PPV = 52.3%, NPV = 76.7%, LR+ = 1.68, LR– = 0.47) and 10.1 (sensitivity = 81%, specificity = 67%, PPV = 74.2%, NPV = 75.6%, LR+ =2.45, LR– = 0.28) for AD and AD/any anxiety disorders, respectively. Internal validation using bootstrap methods showed that the optimal cutoff points identified were reasonably consistent. Univariate odds ratios between each PSAT item and diagnoses (as an outcome) were typically quite large (eg, > 2), indicating most items were significantly associated with the diagnoses.

The finalized version of the PSAT is provided in Supplementary Appendix 1.

DISCUSSION

Anxiety is common during pregnancy, with prevalence rates of 23% and 15% for anxiety symptoms and disorders, respectively.53 The PSAT was developed to measure PSA and its severity and consists of 6 factors:

  • Health and Well-being of the Baby factor (5 items) measures concerns related to health, development, and potential loss of the baby. All previous PSA scales assessed this domain. The PSAT is unique insofar as it includes an item pertaining to developmental concerns.
  • Labor and Pregnant Person’s Well-being factor (4 items) assesses cognition related to labor and delivery. All previous measures except one16 cover this factor.
  • Postpartum factor (3 items) measures concerns related to body image, parenting, and bonding with the baby. Body image2,19 and parenting concerns4,17,19 were covered by previous measures. However, to our knowledge, no previous PSA scale assesses concerns related to bonding.
  • Career and Finance factor (3 items) measures concerns related to financial challenges and impact of pregnancy and parenting on career/education trajectory, another factor unique to the PSAT. Pregnant people are more likely to experience occupational stress than non-pregnant counterparts.54 They may experience anxieties related to employer’s/colleagues’ reactions to pregnancy disclosure, impact on work contract extensions, and promotion and earning capacity,54 as well as concerns about stigmatization and discrimination.55 Perceived pregnancy discrimination can increase the risk of a shorter gestation, smaller baby, and postpartum depression due to increased maternal stress.56
  • Support factor (4 items) measures concerns related to overall provision of social support and health care provider and partner’s support. While 2 previous scales included items related to care providers’ attitudes,15,19 to our knowledge no scales have included items related to partner and overall support. As a societal matter, issues provoking anxiety during pregnancy extend beyond health concerns and may include the extent of support network and interpersonal relationships.57
  • Severity factor (14 items) measures the consequences of elevated anxiety, including difficulty in concentration and making decisions, experiencing multiple and constant worries, and the extent to which anxiety interferes with the ability for self-care and daily function. The severity of PSA was an undermeasured domain in most previous scales with the exception of the POQ,4 which included 6 items pertaining to the consequences of PSA. The recently developed scale by Brunton et al19 also included a few items that could be considered severity indicators. However, these items are focused on preferences for and safety of cesarean birth that would depend on the health-related characteristics of pregnancy.

Psychometric testing of the PSAT showed a high degree of internal consistency, test-retest reliability, and construct, convergent, and divergent validity. The PSAT showed high correlation with PSA measures (P-RAS, PrAS, with estimates ranging from 0.70–0.83) and moderate correlation with general anxiety and depression measures (GAD-7, STAI-S, EPDS, with estimates ranging from 0.58–0.64) and theoretically related constructs (PSS, PPRQ, with estimates ranging from 0.40–0.58). To our knowledge, the PSAT is the first measure of PSA created with concurrent validation embedded in the scale development process. The PSAT showed a moderate accuracy for identifying AD and anxiety disorders.

Strengths of the PSAT include the utilization of a conceptual framework based on the literature dating back to the 1950s,1 incorporation of input from stakeholders and pregnant people, utilization of PRO principles, development of a severity metric, inclusion of contemporary dimensions of PSA, and validation against a clinically relevant diagnosis.

While we enrolled participants from across a wide geographic region including remote and rural areas, our participants were mostly educated and partnered and had a relatively high household income. Studies are needed with more diverse populations to examine the contextual and cultural validity of the PSAT among different ethnic groups as well as low- and middle-income settings. Part of the data collection for sample 2 occurred during the COVID-19 pandemic. We collected qualitative data from participants recruited during the pandemic, and their overall pandemic experience has been published previously.58 Data analyses for samples 1 and 2 were conducted after the completion of participant recruitment for these samples, and thus participants in both samples completed the initial version of the PSAT. All items were scored from 1 to 4, except partner-related items (items 27, 31, 33) that were scored from 1 to 5, with 5 being “not applicable.” The number of people with no partner in our sample was relatively small (1.8%–2.4%). The implications of this scoring in samples with a larger proportion of people without a partner need to be explored. Further studies for the continued development of the PSAT are needed particularly for the Postpartum factor (due to a lower internal consistency and lack of associations between 2 of its items and the AD diagnosis; results not shown). Finally, we used AD as an equivalent clinical diagnosis for PSA. The PSA is a relatively new construct—it has been recognized as a distinct entity for less than a few decades. As such, the clinical course and diagnostic criteria for PSA require further study to facilitate improved diagnosis.

CONCLUSION

The PSAT advances the measurement of PSA by tapping additional dimensions of the concept (eg, career/finance, bonding, and developmental concerns) and through an assessment of severity. As a PROM tool, the PSAT can be useful for screening and monitoring PSA among the general population of pregnant people throughout pregnancy, with scores higher than 10 indicating a need for further assessment. Future research is needed for refining the PSAT and for developing a shorter version of the instrument.

Submitted: October 25, 2022; accepted December 13, 2022.
Published online: April 19, 2023.
Relevant financial relationships: The authors declare no competing interests.
Author contributions: Dr Bayrampour contributed to conception of the project, design of the study, acquisition, analysis and interpretation of data, and drafting the manuscript. Mr Hohn contributed to analysis and interpretation of data and drafting the manuscript. Dr Tamana contributed to acquisition and interpretation of data and revising the manuscript. Dr Sawatzky contributed to design of the study, analysis and interpretation of data, and revising the manuscript. Dr Janssen contributed to conception of the project, design of the study, and interpretation of data and revising the manuscript. Mr Bone contributed to analysis and interpretation of data and revising the manuscript. Dr Fairbrother contributed to design of the study, interpretation of data, and revising the manuscript. Dr Joseph contributed to conception of the project, design of the study, and interpretation of data and revising the manuscript. All authors have approved the final version of the manuscript.
Funding/support: The PSAT study was supported by the Canadian Institutes of Health Research (CIHR)/Project Grant (grant number PJT – 152938; 2017–2020).
Role of the sponsor: The funding agency was not involved in the conceptualization, data collection, data analysis, and interpretation and preparation of the manuscript.
Previous presentations: Presented at the Biennial Conference of the International Marcé Society, September 2022, United Kingdom; and the 20th Congress of the International Society of Psychosomatic Obstetrics & Gynaecology (ISPOG), July 2022.
Acknowledgments: The authors acknowledge the contribution of Deirdre Ryan, MD (University of British Columbia); Suzanna Tough, PhD (University of Calgary); Karen Benzies, RN, PhD (University of Calgary); Elena Ali, RN, PhD (University of Calgary); and the late Glenda MacQueen, MD (University of Calgary) for rating items of the PSAT in the content validation phase. They acknowledge the contribution of Bruce Dick, PhD (University of Alberta) for rating a subset of clinical diagnostic interviews. They also acknowledge the contribution of the Perinatal Wellbeing Research team in conducting the study. The acknowledged individuals declare no conflict of interest related to this work.
Supplementary material: Available at Psychiatrist.com.

CLINICAL POINTS

  • Clinically valid tools are needed to measure pregnancy-specific anxiety and its severity.
  • The Pregnancy-Specific Anxiety Tool can be useful for screening pregnancy-specific anxiety throughout pregnancy.
  • People with a score > 10 may need further assessments.

*The estimate of internal consistency calculated from the item scores yielded α = .895.

Editor’s Note: We encourage authors to submit papers for con­sideration as a part of our Focus on Women’s Mental Health section. Please contact Marlene P. Freeman, MD, at [email protected].
  1. Department of Family Practice, University of British Columbia (UBC), Vancouver, Canada
  2. Corresponding author: Hamideh Bayrampour, MSc, PhD, Department of Family Practice, 320 - 5950 University Blvd, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada ([email protected]).
  3. bDepartment of Psychology, Simon Fraser University, Vancouver, Canada
  4. Department of Pediatrics, University of British Columbia (UBC), Vancouver, Canada
  5. School of Nursing, Trinity Western University, Langley, Canada
  6. Centre for Health Evaluation and Outcome Science, Providence Health Care, Vancouver, Canada
  7. School of Population and Public Health, University of British Columbia (UBC), Vancouver, Canada
  8. Department of Obstetrics and Gynecology, University of British Columbia (UBC), Vancouver, Canada
  9. Department of Family Practice, University of British Columbia (UBC), Vancouver, Canada
  10. School of Population and Public Health, University of British Columbia (UBC), Vancouver, Canada
  11. Department of Obstetrics and Gynecology, University of British Columbia (UBC), Vancouver, Canada
  12. Children’s and Women’s Hospital of British Columbia, Vancouver, Canada
  1. Bayrampour H, Ali E, McNeil DA, et al. Pregnancy-related anxiety: a concept analysis. Int J Nurs Stud. 2016. PubMed CrossRef
  2. Huizink AC, Mulder EJH, Robles de Medina PG, et al. Is pregnancy anxiety a distinctive syndrome? Early Hum Dev. 2004;79(2):81–91. PubMed CrossRef
  3. Orr ST, Reiter JP, Blazer DG, et al. Maternal prenatal pregnancy-related anxiety and spontaneous preterm birth in Baltimore, Maryland. Psychosom Med. 2007;69(6):566–570. PubMed CrossRef
  4. Theut SK, Pedersen FA, Zaslow MJ, et al. Pregnancy subsequent to perinatal loss: parental anxiety and depression. J Am Acad Child Adolesc Psychiatry. 1988;27(3):289–292. PubMed CrossRef
  5. Ross LE, Gilbert Evans SE, Sellers EM, et al. Measurement issues in postpartum depression part 1: anxiety as a feature of postpartum depression. Arch Women Ment Health. 2003;6(1):51–57. PubMed CrossRef
  6. Blackmore ER, Gustafsson H, Gilchrist M, et al. Pregnancy-related anxiety: evidence of distinct clinical significance from a prospective longitudinal study. J Affect Disord. 2016;197:251–258. PubMed CrossRef
  7. Stout-Oswald SA, Glynn LM, Bisoffi M, et al. Prenatal exposure to maternal psychological distress and telomere length in childhood. Dev Psychobiol. 2022;64(1):e22238. PubMed CrossRef
  8. Dereix AE, Ledyard R, Redhunt AM, et al. Maternal anxiety and depression in pregnancy and DNA methylation of the NR3C1 glucocorticoid receptor gene. Epigenomics. 2021;13(21):1701–1709. PubMed CrossRef
  9. Blair MM, Glynn LM, Sandman CA, et al. Prenatal maternal anxiety and early childhood temperament. Stress. 2011;14(6):644–651. PubMed CrossRef
  10. Kramer MS, Lydon J, Séguin L, et al. Stress pathways to spontaneous preterm birth: the role of stressors, psychological distress, and stress hormones. Am J Epidemiol. 2009;169(11):1319–1326. PubMed CrossRef
  11. Lobel M, Cannella DL, Graham JE, et al. Pregnancy-specific stress, prenatal health behaviors, and birth outcomes. Health Psychol. 2008;27(5):604–615. PubMed CrossRef
  12. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. Fifth Edition. American Psychiatric Association; 2013.
  13. Matthey S, Ross-Hamid C. The validity of DSM symptoms for depression and anxiety disorders during pregnancy. J Affect Disord. 2011;133(3):546–552. PubMed CrossRef
  14. Roesch SC, Dunkel SC, Woo G, et al. Modeling the types and timing of stress in pregnancy. Anxiety Stress Coping. 2004;17(1):87–102. CrossRef
  15. Levin JS. The factor structure of the Pregnancy Anxiety Scale. J Health Soc Behav. 1991;32(4):368–381. PubMed CrossRef
  16. Cote-Arsenault D. The influence of perinatal loss on anxiety in multigravidas. J Obstet, Gynecol, Neonat Nurs. 2003;32(5):623–629.
  17. Rini CK, Dunkel-Schetter C, Wadhwa PD, et al. Psychological adaptation and birth outcomes: the role of personal resources, stress, and sociocultural context in pregnancy. Health Psychol. 1999;18(4):333–345. PubMed CrossRef
  18. Brunton RJ, Dryer R, Saliba A, et al. Pregnancy anxiety: a systematic review of current scales. J Affect Disord. 2015;176:24–34. PubMed CrossRef
  19. Brunton RJ, Dryer R, Saliba A, et al. The initial development of the Pregnancy-related Anxiety Scale. Women Birth. 2019;32(1):e118–e130. PubMed CrossRef
  20. Harpel TS. Fear of the unknown: ultrasound and anxiety about fetal health. Health (London). 2008;12(3):295–312. PubMed CrossRef
  21. Cox BE. Pregnancy, Anxiety, and Time Perception. University of Illinois; 1987.
  22. Rubin R. Maternal tasks in pregnancy. Matern Child Nurs J. 1975;4(3):143–153. PubMed
  23. Patrick DL, Guyatt GH, Acquardo C. Patient-reported outcomes. In: Higgins JPT, Green S, eds. Cochrane Handbook for Systematic Reviews of Interventions. The Cochrane Collaboration; 2011.
  24. Reeve BB, Wyrwich KW, Wu AW, et al. ISOQOL recommends minimum standards for patient-reported outcome measures used in patient-centered outcomes and comparative effectiveness research. Qual Life Res. 2013;22(8):1889–1905. PubMed CrossRef
  25. McKenna SP. Measuring patient-reported outcomes: moving beyond misplaced common sense to hard science. (Review) BMC Med. 2011;9(1):86. PubMed CrossRef
  26. Boateng GO, Neilands TB, Frongillo EA, et al. Best practices for developing and validating scales for health, social, and behavioral research: a primer. Front Public Health. 2018;6:149. PubMed CrossRef
  27. Fayers PM, Machin D. Quality of Life: The Assessment, Analysis, and Reporting of Patient-Reported Outcomes. 3rd ed. Wiley Blackwell; 2016.
  28. Greenhalgh J, Gooding K, Gibbons E, et al. How do patient reported outcome measures (PROMs) support clinician-patient communication and patient care? A realist synthesis. J Patient Rep Outcomes. 2018;2(1):42. PubMed CrossRef
  29. Bayrampour H, McNeil DA, Benzies K, et al. A qualitative inquiry on pregnant women’s preferences for mental health screening. BMC Pregnancy Childbirth. 2017;17(1):339. PubMed CrossRef
  30. Lynn MR. Determination and quantification of content validity. Nurs Res. 1986;35(6):382–386. PubMed CrossRef
  31. DeVellis RF. Scale Development: Theory and Applications. Sage Publications; 2012.
  32. Polit DFB. CT Nursing Research: Principles and Methods. 7th ed. Lippincott Williams & Wilkins; 2004.
  33. Polit DF, Beck CT, Owen SV. Is the CVI an acceptable indicator of content validity? appraisal and recommendations. Res Nurs Health. 2007;30(4):459–467. PubMed CrossRef
  34. Streiner DL, Norman GR, Cairney J. Health Measurement Scales: A Practical Guide to Their Development and Use. 5th ed. Oxford University Press; 2015.
  35. Ryan K, Gannon-Slater N, Culbertson MJ. Improving survey methods with cognitive interviews in small- and medium-scale evaluations. Am J Eval. 2012;33(3):414–430. CrossRef
  36. Bayrampour H, Tomfohr L, Tough S. Trajectories of perinatal depressive and anxiety symptoms in a community cohort. J Clin Psychiatry. 2016;77(11):e1467–e1473. PubMed CrossRef
  37. Buss C, Davis EP, Hobel CJ, et al. Maternal pregnancy-specific anxiety is associated with child executive function at 6–9 years age. Stress. 2011;14(6):665–676. PubMed CrossRef
  38. Cox JL, Holden JM, Sagovsky R. Detection of postnatal depression: development of the 10-item Edinburgh Postnatal Depression Scale. Br J Psychiatry. 1987;150(6):782–786. PubMed CrossRef
  39. Spitzer RL, Kroenke K, Williams JB, et al. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006;166(10):1092–1097. PubMed CrossRef
  40. Spielberger CD, Gorsuch RL. Manual for the State-Trait Anxiety Inventory (Form Y). Consulting Psychologists Press; 1983.
  41. Heaman MI, Gupton AL. Psychometric testing of the Perception of Pregnancy Risk Questionnaire. Res Nurs Health. 2009;32(5):493–503. PubMed CrossRef
  42. Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24(4):385–396. PubMed CrossRef
  43. Waltz CF, Strickland OL, Lenz ER. Measurement in Nursing and Health Research. 4th ed. Springer; 2010.
  44. American Psychiatric Association. Structured Clinical Interview for DSM-5 (SCID-5). 2015. https://wwwappiorg/products/structured-clinical-interview-for-dsm-5-scid-5
  45. Cook KF, Kallen MA, Amtmann D. Having a fit: impact of number of items and distribution of data on traditional criteria for assessing IRT’s unidimensionality assumption. Qual Life Res. 2009;18(4):447–460. PubMed CrossRef
  46. Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Modeling. 1999;6(1):1–55. CrossRef
  47. Zumbo BD, Gadermann A, Zeisser C. Ordinal versions of coefficients alpha and theta for Likert rating scales. J Mod Appl Stat Methods. 2007;6(1):8. CrossRef
  48. RCR Team. A language and environment for statistical computing. R Foundation for Statistical Computing. R Project website. https://www.R-project.org/.
  49. Rosseel Y. lavaan: an R package for structural equation modeling. J Stat Softw. 2012;48(2):36. CrossRef
  50. Muthén LK, Muthén BO. Mplus (Version 8.4) [computer software]. https://www.statmodel.com/.
  51. McNeish D, Wolf MG. Thinking twice about sum scores. Behav Res Methods. 2020;52(6):2287–2305. PubMed CrossRef
  52. Altman DG. Practical Statistics for Medical Research. CRC Press; 1990.
  53. Dennis CL, Falah-Hassani K, Shiri R. Prevalence of antenatal and postnatal anxiety: systematic review and meta-analysis. Br J Psychiatry. 2017;210(5):315–323. PubMed CrossRef
  54. Lojewski J, Flothow A, Harth V, et al. Employed and expecting in Germany: a qualitative investigation into pregnancy-related occupational stress and coping behavior. Work. 2018;59(2):183–199. PubMed CrossRef
  55. Jones KP. To tell or not to tell? examining the role of discrimination in the pregnancy disclosure process at work. J Occup Health Psychol. 2017;22(2):239–250. PubMed CrossRef
  56. Hackney KJ, Daniels SR, Paustian-Underdahl SC, et al. Examining the effects of perceived pregnancy discrimination on mother and baby health. J Appl Psychol. 2021;106(5):774–783. PubMed CrossRef
  57. Bayrampour H, Heaman M, Duncan KA, et al. Advanced maternal age and risk perception: a qualitative study. BMC Pregnancy Childbirth. 2012;12(1):100. PubMed CrossRef
  58. Bayrampour H, Tamana SK, Boutin A. Pregnant people’s responses to the COVID-19 pandemic: a mixed-methods, descriptive study. CMAJ Open. 2022;10(1):E146–E154. PubMed CrossRef