Psychometric Properties,Stability,and Predictive Validity of the Hindi Version of the Prolonged Grief Disorder Scale (PG-13-R-H) Among Hindi-speaking Adults in the United States

Abstract

Background:

Prolonged grief disorder (PGD) significantly impacts individuals following bereavement, particularly under conditions of sudden loss and disrupted mourning. Despite Hindi being one of the most widely spoken languages, no validated PGD assessment tool has existed for Hindi speakers. This study aimed to translate, adapt, and validate the Hindi version of the Prolonged Grief Disorder-13 Revised Scale (PG-13-R-H) among Hindi-speaking adults in the United States for screening and secondary monitoring.

Methods:

A cross-sectional online survey was conducted with 527 Hindi-speaking adults residing in the United States who had experienced bereavement. Participants completed the PG-13-R-H, the Patient Health Questionnaire-9 (PHQ-9), and the Warwick-Edinburgh Mental Well-Being Scale (WEMWBS). Reliability was assessed with Cronbach’s alpha, and validity was evaluated using Pearson correlations and a multi-trait-multimethod matrix (MTMM).

Results:

The PG-13-R-H demonstrated adequate internal consistency (Cronbach’s alpha = 0.75). Overall, 15.6% of participants met diagnostic thresholds for PGD. COVID-19–related deaths were reported by 41.7% of the sample, and 88.6% had experienced an unexpected loss—both strong risk factors for PGD. Convergent validity was supported by correlation with depressive symptoms (PHQ-9; r = .23, p < .001), while discriminant validity was supported by a non-significant correlation with well-being (WEMWBS; r = –.05, p = .34). Findings also highlighted the impact of diaspora mourning contexts, where disruptions in family-based rituals and limited support systems may intensify grief among Hindi-speaking Americans.

Conclusions:

The PG-13-R-H is a reliable, valid, and culturally sensitive tool for assessing PGD among Hindi-speaking Americans. This study emphasizes the importance of language-specific and contextually informed assessment tools to identify at risk individuals in diasporic communities, where pandemic-related disruptions and limited support systems may heighten vulnerability to prolonged grief.

Keywords

Bereavement Hindi speakers prolonged grief disorder (PGD)validation study

Key Messages:

This is the first validation of the PG-13-R-H in Hindi, addressing a critical gap for Hindi-speaking populations in the United States.

Prolonged grief and depression, while related, are distinct conditions, as shown by the PG-13-R-H’s correlation patterns with PHQ-9 and WEMWBS.

Nearly 15.6% of Hindi-speaking Americans in the study met diagnostic thresholds for PGD, with risk elevated by unexpected and COVID-19–related losses.

Diaspora mourning differences, including disrupted rituals, and reduced access to extended family support, may intensify grief experiences for Hindi-speaking Americans.

The PG-13-R-H provides clinicians and community organizations with a culturally and linguistically appropriate tool for identifying and supporting those at risk for PGD in this population.

The PG-13-Revised (PG-13-R) is a self-report clinical assessment tool designed to measure prolonged grief disorder (PGD) symptoms according to updated diagnostic criteria. Its scope includes clinical and research utility, and it has become a gold standard due to its brevity, alignment with Diagnostic and Statistical Manual of Mental Disorders (DSM)-5-TR and International Classification of Diseases (ICD)-11 frameworks, and validation across diverse cultural contexts.¹ The PG-13-R is primarily intended as a screening instrument to identify individuals at risk for PGD, with secondary use in monitoring symptom severity and evaluating treatment outcomes.¹

Despite Hindi being the third most spoken language globally, with more than 600 million speakers,² no PGD scale has been validated for Hindi-speaking populations. Existing validations of the PG-13-R span more than 15 languages, including Korean, Urdu, Swedish, and Turkish.^3–5 Yet Hindi has remained unexamined. At the same time, severe grief persisting beyond a year has been associated with morbidity and dysfunction.^6,7

Global public health challenges underscore the importance of validated PGD assessment tools. COVID-19, for instance, led to a surge of sudden, unexpected deaths, a recognized risk factor for PGD.^1,7 Other risk factors include violent or unnatural death, low education, low income, female gender, anxious attachment style, and loss of a child or partner.^8–10 Rates of PGD have been reported as high in conflict-affected or marginalized communities, including Ukraine, Bosnia, Cambodian refugees in Germany, and the Mandaean community in Sydney.^11–13 In the United Kingdom, over 35% of people bereaved during the pandemic met PGD criteria 13 months post-loss.^7,14 In India, between June 2020 and July 2021, an estimated 4.1 million deaths were attributed to COVID-19, disproportionately affecting women, Muslims, and scheduled tribes.^15,16

To address the lack of validated grief measures for Hindi-speaking adults, we translated, back-translated, and pilot-tested the Prolonged Grief Disorder-13 Revised Scale (PG-13-R-H) with bereaved Hindi-speaking adults residing in the United States. This adaptation fills a crucial linguistic gap and expands access to standardized tools for assessing prolonged grief in one of the world’s most widely spoken languages.

Aims

To evaluate the psychometric properties, reliability, and validity of the Hindi-translated PG-13-R-H among bereaved Hindi-speaking adults residing in the United States.

To explore whether the Hindi version of the PG-13-R-H will demonstrate strong psychometric properties such as reliability, internal consistency, and construct validity comparable to those observed in other language adaptations.

Objectives

To assess the internal consistency and reliability of the PG-13-R-H in a large, diverse United States Hindi-speaking sample, ensuring robust, generalizable findings.

To examine construct, convergent, and discriminant validity using related mental health indicators (Patient Health Questionnaire-9 [PHQ-9] for depression, Warwick-Edinburgh Mental Well-Being Scale [WEMWBS] for well-being).

To compare the psychometric performance of the PG-13-R-H to other validated language adaptations, confirming its use as a culturally and linguistically sensitive tool for screening prolonged grief.

Methods

Ethical Considerations

The study received Institutional Review Board (IRB) approval and was classified as minimal risk. All participants provided informed consent after reviewing the study’s purpose, procedures, and potential risks. To maintain confidentiality, responses were de-identified, and securely stored with encryption protocols. Given the sensitive nature of bereavement research, participants were provided with mental health resources in case of distress. Each participant received a US$10 Amazon gift card upon completing the survey.

Eligibility

Participants were eligible if they were (a) 18 years or older, (b) had experienced the death of a close family member or friend, (c) reported Hindi as their primary language (self-reported at the start of the survey), (d) had internet access, and (e) resided in the United States at the time of the study. All surveys were completed in Hindi to ensure linguistic validity.

Translation and Cultural Adaptation

The Hindi version of the PG-13-R-H was developed using a structured, multi-step process. In November 2022, a bilingual translator in India was hired to translate the instrument into Hindi. A second bilingual coinvestigator (AM) performed a back translation into English. Discrepancies were reconciled through joint review meetings, focusing on conceptual rather than literal equivalence. They reviewed the reconciled version together, making minor adjustments to optimize readability and cultural resonance while preserving diagnostic fidelity.

Finally, 11 Hindi-speaking adults residing in the United States participated in cognitive debriefing interviews using think-aloud and probing techniques to assess clarity, cultural resonance, and ease of comprehension. Feedback resulted in minor wording refinements. This process aligns with established guidance recommending 5–15 participants for cognitive interviewing, with ≥7 considered sufficient for ensuring comprehensibility.^17,18

Participants and Sampling

For the main validation, recruitment used convenience, and snowball sampling. Invitations were distributed via email across [University Redacted] campuses and in person at Indian community hubs, such as Jackson Heights, Queens—one of the most linguistically diverse areas in the United States. Cards with Quick Response (QR) codes linking to an eligibility screener and survey were distributed at supermarkets, jewelry and clothing stores, and other Jackson Heights establishments in January 2023, as well as at places of worship in Jamaica, Queens, New York. A total of 1,194 individuals responded between January and April 2023.

Measures

PG-13-R: A 13-item self-report measure designed to assess PGD according to DSM-5-TR and ICD-11 criteria.¹⁹

PHQ-9: Used as a measure of depressive symptoms. The Hindi version has previously demonstrated a Cronbach’s alpha of 0.79 in Indian populations.²⁰

WEMWBS: Used to assess mental well-being. The Hindi version has previously demonstrated a Cronbach’s alpha of 0.92.^21,22

Demographics

Participants provided demographic information, including age, gender, education, relationship to the deceased, time since loss, and cause of death. These variables were collected to contextualize results and explore potential influences on PG-13-R-H performance. Given that grief expression may be shaped by literacy and cultural practices, special attention was paid to the educational distribution of the sample.

Data Analysis

All statistical analyses were conducted using RStudio (version 2024.12.1) with base R (version 4.4.1). Before analysis, the dataset underwent preprocessing to ensure data integrity and reliability. This included removing duplicate responses identified by Internet Protocol (IP) addresses and name inconsistencies, and excluding incomplete cases. After eliminating incomplete or duplicate entries, 527 unique, complete responses (44.30% of the original sample) were retained for analysis; these are referred to as “empirically validated responses.”

Descriptive statistics were computed to summarize demographic characteristics and scale scores. Each psychological measure was examined independently, with summed scores categorized according to standardized diagnostic guidelines. The WEMWBS scores were classified into low, medium, and high mental well-being categories based on a one-standard-deviation cutoff from the mean. The PHQ-9 diagnostic categorization was conducted using two approaches: First, symptom severity was classified based on the number of endorsed severe responses; second, a total score-based classification method was applied following PHQ-9 standard scoring recommendations according to PGD classification using the PG-13-R was determined based on the total score, the response to the diagnostic criterion (Item 13), and whether the loss occurred more than a year ago, following established PGD diagnostic thresholds.²³ In addition, Pearson’s correlation analyses were conducted between demographic variables (age, education) and scales. For this analysis, education was refactored into a five-level scale, where a higher value indicated a higher level of education.

Internal consistency was assessed using Cronbach’s alpha, with 95% confidence intervals generated through 1,000 bootstrap samples to enhance robustness. Cronbach’s alpha was calculated separately for the PG-13-R, PHQ-9, and WEMWBS to evaluate the reliability of each measure. For PG-13-R, an alternative Cronbach’s alpha was calculated without item 13, a binary item, to affirm the scale’s internal consistency. In addition, factor analysis via principal component analysis (PCA) was conducted for PG-13-R responses to confirm the unitary structure of the translated scale. Convergent and discriminant validity were examined using Pearson correlation coefficients to assess the relationships between total scores on the PG-13-R, PHQ-9, and WEMWBS. Holm’s method was applied to adjust for multiple comparisons to reduce the risk of type I error. A multi-trait-multimethod matrix (MTMM) approach was employed to provide a more granular assessment of validity. Each scale’s individual items were grouped by their respective measures, and inter-item correlations were examined both within and across scales. The MTMM framework allowed for a detailed evaluation of whether the PG-13-R demonstrated strong within-scale coherence while maintaining distinctiveness from related but non-overlapping constructs, such as depression, and general mental well-being. All statistical tests were conducted at a two-tailed significance level of 0.05. Missing data were handled using listwise deletion. Assumptions of normality, homoscedasticity, and multicollinearity were assessed before inferential analyses, and no substantial violations were observed. The data were analyzed using complete cases only to maintain the validity of the statistical inferences.

Justification for the Reliability of Comparator Scales

We computed internal consistency (Cronbach’s α with 95% CIs) for the PHQ-9 and WEMWBS in our sample to ensure that the convergent and discriminant validity tests of the PG-13-R-H were based on reliable comparator measures in this specific population (United States–resident Hindi speakers, online survey context, varied education/literacy levels). Reliability is sample– and context–dependent; coefficients established in previous Hindi validations may not transfer unchanged to our demographic, modality (self-administered online), or grief context. Adequate internal consistency minimizes attenuation of correlations in the MTMM and bivariate analyses, allowing fair inferences about construct distinctiveness. In our data, PHQ-9 and WEMWBS showed acceptable internal consistency (α ≈ 0.73 and α ≈ 0.74, respectively), supporting their use as validity anchors for PG-13-R-H. (Refer to Table 3).

Results

The final analytic sample consisted of 527 participants after data cleaning. Table 1 presents the demographic characteristics of the sample, which primarily consisted of participants aged 26–50 years old (92.6%), with a relatively even gender distribution (55.4% female, 44.4% male, and 0.2% non-binary). Most participants had experienced the loss of a close family member, with 43.1% losing a mother and 19.3% losing a grandfather. A large majority (88.6%) reported experiencing an unexpected or sudden loss, while 41.7% specifically identified COVID-19 as the cause of death.^7,24

Table 1.

Descriptive Statistics of the Sample.

Variable	Count	%	Variable	Count	%
Age			Number of Losses
18–25	38	7.21	1	284	53.99
26–35	238	45.16	2	127	24.14
36–50	250	47.44	3	90	17.11
51–65	1	0.19	4	20	3.8
Gender			5	2	0.38
Female	292	55.41	6	1	0.19
Male	234	44.4	7	1	0.19
Non-binary	1	0.19	20	1	0.19
Education			Time Since Loss
Bachelor’s degree	192	36.43	Less than a year	242	45.92
Master’s degree	9	1.71	One year or more	285	54.08
Associate degree	177	33.59	Years Since Loss
Doctorate degree	1	0.19	Less than a year	242	0.46
High school graduate, diploma, or equivalent	15	2.85	1	24	0.05
Professional degree	1	0.19	2	103	0.2
Some college credit, no degree	66	12.52	3	91	0.17
Some high school, no diploma	4	0.76	4	43	0.08
Some secondary schools	1	0.19	Over five years	24	0.05
Trade/technical/vocational training	61	11.57	Timing of Death
Most Significant Loss			Expected death	60	11.39
Aunt	17	3.23	Sudden/unexpected death	467	88.61
Brother	37	7.02	Cause of Death
Child	1	0.19	Accident	103	19.54
Cousin	5	0.95	Illness	420	79.7
Father	29	5.5	Suicide	4	0.76
Friend	15	2.85	Death by COVID
Grandfather	102	19.35	No	245	58.33
Grandmother	34	6.45	Yes	175	41.67
Husband	2	0.38
Mother	227	43.07
Other (please specify)	1	0.19
Significant other/partner	1	0.19
Sister	28	5.31
Teacher	2	0.38
Uncle	21	3.98
Wife	5	0.95
Friend	1	100

The study also captured variations in time since loss: 45.9% of respondents experienced a loss within the past year (which cannot be used to evaluate PGD, as it requires a year post-loss), and 54.1% reported a loss that occurred a year or more ago. The number of losses individuals experienced ranged from 1 to more than 7, with 53.9% having lost only one significant individual and 24.1% having experienced two losses.

Table 2 provides an overview of the psychological well-being and mental health status of the sample. Based on the WEMWBS, 20.1% of participants were classified as having low mental well-being, 68.1% as having moderate levels, and only 11.8% as having high mental well-being. The PHQ-9, which assesses depressive symptoms, indicated that 35.5% of participants exhibited severe depression risk, with an additional 51.9% reporting moderate symptoms. The PG-13-R assessment of PGD revealed that 15.6% of participants scored over 30, experienced loss more than a year ago, and stated to have significant impairment in regular functioning. Of them, 29% (n = 24) experienced a loss due to COVID-19. Correlation analysis on age indicated significant correlation with PHQ-9 (r = 0.265, p < .01) and WEMWBS (r = 0.208, p < .01). Correlations for education were significant for all three scales, with PG-13-R (r = −0.194, p < .01), PHQ-9 (r = 0.314, p < .01), and WEMWBS (r = 0.351, p < .01).

Table 2.

Descriptive Statistics of Scale Test Results.

Scale	Count	%
WEMWBS
Low mental health	106	20.11
Medium mental health	359	68.12
High mental health	62	11.76
PHQ-Initial diagnosis
Minimal	94	17.84
Moderate	246	46.68
Severe	187	35.48
PHQ-Score diagnosis
Minimal	13	2.48
Mild	122	23.28
Moderate	272	51.91
Moderately severe	103	19.66
Severe	14	2.67
PG-13-R
Less likely	410	0.78
Likely	117	0.22

Reliability analyses demonstrated that the PG-13-R, PHQ-9, and WEMWBS all exhibited acceptable internal consistency (see Table 3). Specifically, Cronbach’s alpha for the PG-13-R was 0.75 (95% CI: 0.70–0.78), with the alternative alpha of 0.76 (95% CI: 0.72–0.80). PCA results on PG-13-R indicated that one principal component accounted for 32.12% of the variance, followed by 9.38%. PHQ-9 and WEMWBS also met reliability thresholds, with alpha values of 0.73 and 0.74, respectively. These findings suggest adequate internal consistency across the scales, although the lower bounds of the confidence intervals for PHQ-9 and WEMWBS approached the 0.70 threshold.

Table 3.

Cronbach’s Alpha with 95% Confidence Interval.

Scale	Alpha	95% CI
PG-13-R	0.75	[0.70, 0.78]
PHQ-9	0.73	[0.68, 0.77]
WEMWBS	0.74	[0.69, 0.78]

Cronbach’s alpha values above 0.70 are generally considered acceptable, indicating adequate internal consistency reliability for the scales.

To examine convergent and discriminant validity, Pearson correlation analyses were conducted (Table 4). The PG-13-R exhibited a significant positive correlation with the PHQ-9 (r = .23, p < .001), suggesting that prolonged grief, and depressive symptoms are related but distinct constructs. Similarly, the PHQ-9 correlated significantly with WEMWBS (r = .27, p < .001), highlighting the expected inverse relationship between depression and well-being. However, the PG-13-R did not exhibit a significant correlation with WEMWBS (r = −.05, p = .34), further supporting the distinctiveness of prolonged grief from general mental well-being as well as depression.

Table 4.

Correlation Analysis.

	PG-13-R	WEMWBS	PHQ-9
PG-13-R	1
WEMWBS	−0.05	1
PHQ-9	0.23*	0.27*	1

A more granular evaluation of validity was conducted using the MTMM approach (Table 5). The MTMM matrix revealed consistent positive correlations among items within each scale, indicating strong construct validity. However, an exception was noted for Item 13 of the PG-13-R, which exhibited a lower-than-expected correlation with other PG-13-R items. Figure 1 highlights the differing levels of correlation between PG-13-R and each scale item. While it shows a steady, positive correlation with most items within, PG-13-R shows a weak positive correlation with PHQ-9 items and almost no correlation with WEMWBS items.

Table 5.

MTMM Correlation of Scale Items to Each Scale.

Item	Correlation
Item	PG-13-R	PHQ-9	WEMWBS
PG-13-R
Q3	0.38*	0.07	0
Q4	0.41*	0.1	−0.1
Q5	0.43*	0.09	−0.07
Q6	0.4*	0.15*	0.04
Q7	0.45*	0.15*	−0.02
Q8	0.42*	0.08	0.02
Q9	0.46*	0.14*	−0.06
Q10	0.37*	0.13	−0.08
Q11	0.43*	0.13	0
Q12	0.51*	0.1	−0.02
Q13	−0.1	0	−0.22*
PHQ-9
Q1	0.11	0.31*	0.02
Q2	0.07	0.3*	0.12
Q3	0.15*	0.31*	0.06
Q4	0.11	0.4*	0.15*
Q5	0.11	0.47*	0.19*
Q6	0.13*	0.45*	0.23*
Q7	0.13	0.5*	0.2*
Q8	0.19*	0.4*	0.19*
Q9	0.13	0.38*	0.14*
WEMWBS
Q1	−0.03	0.32*	0.17*
Q2	0.04	0.18*	0.4*
Q3	0.04	0.18*	0.35*
Q4	−0.04	0.14*	0.31*
Q5	0.02	0.16*	0.37*
Q6	−0.1	0.07	0.3*
Q7	−0.03	0.19*	0.42*
Q8	−0.03	0.01	0.23*
Q9	−0.06	0.13	0.43*
Q10	−0.04	0.14*	0.35*
Q11	0.02	0.11	0.29*
Q12	−0.04	0.09	0.36*
Q13	0	0.2*	0.42*
Q14	0.01	0.13	0.31*
Q15	−0.02	0.13*	0.4*

Figure 1.

Correlation of Each Scale Item to Prolonged Grief-13-Hindi (PG-13-H).

Observed α’s for PHQ-9 and WEMWBS in this Hindi-speaking United States sample were comparable to conventional thresholds, indicating that depression and well-being were measured with sufficient precision to (a) detect the expected positive association between PGD and depression and (b) document a near-null association with general well-being, thereby reinforcing construct distinctiveness observed in our MTMM matrix

Discussion

This study validated the Hindi version of the PG-13-R-H, addressing a critical gap in bereavement research for Hindi- speaking populations. Despite Hindi’s global prevalence, no grief assessment tool had previously been culturally adapted for this group. The inclusion of PGD in the ICD-11 and DSM-5-TR,¹⁹ further underscores the necessity of culturally and linguistically relevant measurement tools.¹

The PG-13-R-H demonstrated adequate internal consistency (α = 0.75), aligning with other language validations.¹ About 15% of participants met PGD criteria. The sample comprised predominantly midlife adults (26–50 years), a younger age group than the typical bereavement cohort. Notably, 88.6% experienced an unexpected loss, a known PGD risk factor.^7,8

Additionally, 41.7% reported a COVID-19–related death, reflecting the pandemic’s disproportionate effect.^9–12 These contextual stressors likely contributed to the elevated prevalence of PGD.

Crucially, the PG-13-R-H distinguished PGD from depression and well-being, with only a modest correlation with depression (r = .23, p < .001) and no significant association with well-being (r = –.05, p = .34). This highlights PGD’s distinctiveness and underscores the necessity for grief-specific interventions.^7,12,13

Our findings particularly illuminate the experiences of Hindi-speaking Americans, a linguistically defined population that spans recent immigrants, long-term residents, and United States–born individuals. Although highly educated (which likely aided comprehension), education inversely correlated with PGD symptoms (r = –.19, p < .01), indicating that vulnerability exists regardless of literacy.

In South Asian families, grief is often managed through collectivist practices such as shared rituals, silence, and communal presence, with implicit support preferred over explicit discussion to preserve family harmony.²⁵ Research shows that explicit support sometimes increases distress in Asian cultural contexts, whereas implicit support is associated with better psychological outcomes.^26,27

For Hindi-speaking Americans, many bereavements occurred under circumstances of social isolation, travel restrictions, and disrupted rituals. Diaspora mourning often lacks communal rituals embedded in South Asian grief traditions (e.g., extended family gatherings, religious ceremonies), and this loss of ritualized grieving spaces may lead to disproportionately elevated grief severity.²⁶

Here, our PGD prevalence (15.6%) exceeded the 13.4% found in a diverse United States college sample.²⁸ This finding suggests that pandemic-related disruptions to support systems and mourning rituals likely heightened grief vulnerability.

Collectively, these results suggest that Hindi-speaking Americans face layered bereavement challenges: Modal transitions in cultural mourning, reduced access to traditional community and family support, and pandemic-mediated isolation. By providing a validated grief measure in Hindi for this context, our study furnishes clinicians, and community stakeholders with a reliable, culturally sensitive tool to detect and address prolonged grief in a diasporic population.

Limitations

This study sheds light on PGD in Hindi-speaking communities, but has several limitations. First, the sample was drawn from Hindi speakers in the United States rather than from India or other regions where Hindi is predominant. The experiences of Hindi-speaking Americans are heterogeneous, encompassing recent immigrants, long-term residents, and United States–born individuals. However, we did not collect data on the length of residence in the United States, which may have influenced participants’ acculturation levels, access to support systems, and ability to participate in culturally specific mourning practices. Future studies should include measures of both nativity (United States–born vs. foreign-born) and duration of residence to contextualize grief experiences better.

Second, the study used convenience and snowball sampling within Indian communities in Queens, New York, which may have introduced selection bias. Individuals who were more socially connected or active online may have been overrepresented, while socially isolated individuals may have been underrepresented. Future studies could benefit from randomized or stratified sampling to better represent Hindi-speaking populations, including rural and less-connected individuals.

Third, only 44.30% of the initial responses were included in the final analysis due to duplicates, incomplete entries, or suspected non-authentic cases. While strict data cleaning procedures (e.g., full-name and IP-address checks) improved data quality, some bias may remain. Similarly, reliance on an online survey format raises the possibility of bot responses, despite screening methods. The online modality may have excluded those who are less technologically inclined.

Final, the study’s cross-sectional design and reliance on self-reports limit causal inference. Participants may have underreported or exaggerated symptoms, and we were unable to assess test–retest reliability or changes in symptoms over time. Longitudinal, clinically validated studies are needed to confirm the stability and predictive validity of the PG-13-R-H.

Conclusions

Overall, the validation of the PG-13-R-H holds significant implications for public health and clinical practice. Conducted among Hindi-speaking adults in the United States, this study provides a reliable, standardized assessment tool for identifying individuals at risk for complicated bereavement reactions in this population. Additionally, given the strong correlation between PGD and symptoms of depression, it is vital for mental health professionals to distinguish between prolonged grief and other mood disorders. Misdiagnosis can lead to ineffective treatments, as grief-specific interventions such as PGD treatment are crucial for addressing this unique mental health challenge among vulnerable United States–based Hindi-speaking populations.²⁹

Supplementary Material

Supplementary material for this article is available online.

Supplementary Material

Supplementary material for this article is available online.

Footnotes

Acknowledgements

We are sincerely grateful to the Indian and Hindu societies in Queens, NY, for allowing us to collect data at their sites, and Dr. Raja Kaur for making introductions. We also thank Dr. Collette Brown, Dr. Aditi Puri for their support with data collection. Most importantly, we acknowledge with deep appreciation the efforts of our certified Hindi translator, Dr. Santwana G. Mishra, based in India.

Consent to Participate

Informed consent was obtained from all participants before their participation.

Consent for Publication

Not applicable.

Data Availability

Data supporting this study’s findings are available upon reasonable request from the corresponding author.

Declaration of Conflicting Interests

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

Declaration Regarding the Use of Generative AI

Perplexity version 2.25 was used as the source for the literature review. ChatGPT version 5 was used to draft the abstract and to verify the accuracy of the bibliography across article drafts. It was also used to bolster the article’s limitations section.

Ethics Approval

This study was approved by the IRB and conducted according to the Declaration of Helsinki and APA ethical guidelines.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Funding for the incentives and translation services was provided by [redacted University].

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