The Relationship Between Loneliness and Sleep Disturbances: The Roles of Community Resilience, Social Support, Anxiety, and Substance Use Coping

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The paper presents the relationship between loneliness and sleep disturbances, and the possible interactions with multiple psychological varibles. The topic is in the journal’s interest; however, some issues need to be improved. Please see my comments as follows:

1. The introduction fails to adequately establish the novelty of the study. While loneliness and sleep disturbances are well-researched topics, the authors do not clearly articulate what specific gap in the literature this Mississippi coastal sample uniquely addresses beyond general associations already documented in prior meta-analyses.
2. The literature review in the introduction is somewhat superficial and selective. Important recent theoretical frameworks linking loneliness to sleep via hyperarousal or cognitive mechanisms are mentioned only briefly, while the authors over-rely on a limited set of studies.
3. The proposed theoretical model (Figures 1 and 2) is presented without sufficient justification for why community resilience and social support are positioned only as predictors of loneliness rather than having potential direct or moderating effects on sleep disturbances.
4. The sampling procedure, while using GIS, raises concerns about representativeness. Limiting the sample to households between Interstate 10 and the Gulf coastline in only three counties introduces significant selection bias and limits generalizability, even within Mississippi.
5. Data collection from 2018 is substantially outdated, especially given major societal changes (including the COVID-19 pandemic) that dramatically affected loneliness, anxiety, and sleep patterns. The authors do not adequately address the relevance of nearly decade-old data.
6. Several measures utilize abbreviated or modified scales (e.g., GAD-2 instead of GAD-7, two-item sleep disturbances measure, two-item substance use coping). The authors provide limited psychometric justification for these modifications beyond basic reliability coefficients in the current sample.
7. The reliance on entirely self-reported measures for all constructs creates substantial common method bias concerns that are not properly acknowledged or statistically addressed (e.g., through Harman’s test or other controls).
8. The measurement model CFA fit is only marginally acceptable (RMSEA = .07), yet the authors describe it as “reasonable.” Stricter standards in SEM literature would likely view this as problematic, particularly with a relatively small sample (N=310).
9. The bivariate correlations table reveals several unexpected weak or non-significant relationships that are not sufficiently explored or explained in the text.
10. In the full SEM models, the authors claim adequate fit, but the chi-square remains significant and some indices (NFI=.94 in the mediation model) fall below conventional .95 thresholds. This warrants more cautious interpretation than provided.
11. The mediation findings, while interesting, are overinterpreted. The non-significant direct path after including mediators does not necessarily mean full mediation, especially given cross-sectional data where temporal ordering cannot be established.
12. The lack of significant relationship between substance use coping and sleep disturbances in the mediation model contradicts some cited literature and deserves deeper exploration rather than brief dismissal.
13. The discussion section makes causal inferences (e.g., “loneliness creates the initial vulnerability,” “anxiety... ultimately disrupts sleep process”) that far exceed what cross-sectional data can support.
14. The evolutionary theory interpretation of loneliness and hyper-vigilance is introduced in the discussion without prior grounding in the introduction or methods, appearing somewhat post-hoc.
15. The emphasis on community resilience as a solution feels overstated relative to the small standardized path coefficient (β = -.13) observed in the model.
16. The limitations section is inadequate. It minimally addresses the cross-sectional design but fails to discuss potential reverse causality, unmeasured confounders, or social desirability bias in self-reports of loneliness and substance use.
17. The authors do not discuss the relatively low explained variance in sleep disturbances (R² = .24), which suggests the model misses important predictors.
18. The overall writing and organization could be improved. There are noticeable grammatical issues, awkward phrasings, and inconsistencies (e.g., “Sleeping Disturbances” vs. “Sleep Disturbances” in tables).
19. The conclusions and implications for intervention are overly broad and optimistic given the study’s methodological constraints, small effect sizes for some paths, and regional specificity of the sample. Stronger tempering of public health recommendations is needed.

Overall; the topic is valuable, and the mediation finding through anxiety is noteworthy. However, the current version of the paper needs considerable work on methodological transparency, theoretical grounding, and scholarly caution. I kindly suggest the authors to carefully address these major points in their revision. I would be happy to review a revised version of this manuscript.

Best regards

Comments on the Quality of English Language

There are noticeable grammatical issues, awkward phrasings, and inconsistencies (e.g., “Sleeping Disturbances” vs. “Sleep Disturbances” in tables).

Author Response

Overall: The paper presents the relationship between loneliness and sleep disturbances, and the possible interactions with multiple psychological variables. The topic is in the journal’s interest; however, some issues need to be improved. Please see my comments as follows:

Reviewer 1 #1. The introduction fails to adequately establish the novelty of the study. While loneliness and sleep disturbances are well-researched topics, the authors do not clearly articulate what specific gap in the literature this Mississippi coastal sample uniquely addresses beyond general associations already documented in prior meta-analyses: 

We appreciate the reviewer’s comment. We have revised the Introduction (Section 1.1) to clearly articulate the unique conceptual and practical novelty of this study. 

Reviewer 1 #2. The literature review in the introduction is somewhat superficial and selective. Important recent theoretical frameworks linking loneliness to sleep via hyperarousal or cognitive mechanisms are mentioned only briefly, while the authors over-rely on a limited set of studies.

We appreciate the interest in additional frameworks. We focused our literature review on the definitions and connections that we felt would define and explain the concepts we were investigating. While we would be interested in future work on hyper arousal and cognition in this area, our data does not include supporting constructs. 

Reviewer 1 #3. The proposed theoretical model (Figures 1 and 2) is presented without sufficient justification for why community resilience and social support are positioned only as predictors of loneliness rather than having potential direct or moderating effects on sleep disturbances.

We appreciate the reviewer’s comment. In response, we have revised the statement in Section 1.2, The Current Study, to improve clarity and added a statement to the fifth point in the Limitations and Future Research section.

Reviewer 1 #4. The sampling procedure, while using GIS, raises concerns about representativeness. Limiting the sample to households between Interstate 10 and the Gulf coastline in only three counties introduces significant selection bias and limits generalizability, even within Mississippi.

We appreciate the reviewer’s comment. In response, we have revised the second point in the Limitations and Future Research section.

Reviewer 1 #5. Data collection from 2018 is substantially outdated, especially given major societal changes (including the COVID-19 pandemic) that dramatically affected loneliness, anxiety, and sleep patterns. The authors do not adequately address the relevance of nearly decade-old data.

We believe the constructs still apply, as the main issues persist today. Therefore, our findings can still guide future explorations and interventions. We have added a statement in the limitations section. 

Reviewer 1 #6. Several measures utilize abbreviated or modified scales (e.g., GAD-2 instead of GAD-7, two-item sleep disturbances measure, two-item substance use coping). The authors provide limited psychometric justification for these modifications beyond basic reliability coefficients in the current sample.

We appreciate the reviewer’s comment. In response, we have added additional information regarding psychometric evidence to 2.2.4 Anxiety under the Measures section. Also, the 2.2.5. Substance Use Coping section has been revised for clarification. Additionally, relevant references related to this added statement have been included in the reference list.

Reviewer 1 #7. The reliance on entirely self-reported measures for all constructs creates substantial common method bias concerns that are not properly acknowledged or statistically addressed (e.g., through Harman’s test or other controls).

We appreciate the reviewer’s helpful comment. We add a statement in the Limitation section.

Reviewer 1 #8. The measurement model CFA fit is only marginally acceptable (RMSEA = .07), yet the authors describe it as “reasonable.” Stricter standards in SEM literature would likely view this as problematic, particularly with a relatively small sample (N=310).

We appreciate the reviewer’s helpful comment. In response, we have added the normed chi-square ratio, χ²/df, as an additional model fit index to 2.3. Statistical Analysis, under the Method section. We have also revised the interpretation of model fit in the Results section accordingly to address the reviewer’s concern. Additionally, relevant references related to this added statement have been included in the reference list.

Reviewer 1 #9. The bivariate correlations table reveals several unexpected weak or non-significant relationships that are not sufficiently explored or explained in the text.

We thank the reviewer for this comment. We agree that exploring unexpected or non-significant bivariate associations adds valuable depth to the paper. We have added a dedicated paragraph to the manuscript exploring these relationships.

Reviewer 1 #10. In the full SEM models, the authors claim adequate fit, but the chi-square remains significant and some indices (NFI=.94 in the mediation model) fall below conventional .95 thresholds. This warrants more cautious interpretation than provided.

We appreciate the reviewer’s comment. In response, we have added the normed chi-square ratio, χ²/df, as an additional model fit index to the 2.3. Statistical Analysis, under the Method section. We have also revised the interpretation of model fit in the Results section accordingly to address the reviewer’s concern. Additionally, relevant references related to this added statement have been included in the reference list.

Reviewer 1 #11. The mediation findings, while interesting, are overinterpreted. The non-significant direct path after including mediators does not necessarily mean full mediation, especially given cross-sectional data where temporal ordering cannot be established.

We appreciate the reviewer’s comment. Given the cross-sectional nature of the study design, we have revised wordings in the Current Study and Discussion sections to address these concerns.

Reviewer 1 #12. The lack of a significant relationship between substance use coping and sleep disturbances in the mediation model contradicts some cited literature and deserves deeper exploration rather than brief dismissal.

We appreciate the reviewer’s comment. We have added literature to the discussion section.

Reviewer 1 #13. The discussion section makes causal inferences (e.g., “loneliness creates the initial vulnerability,” “anxiety... ultimately disrupts sleep process”) that far exceed what cross-sectional data can support.

We appreciate the reviewer’s comment. We changed the Discussion section, which has causal inference expressions, into the cross-sectional conclusion.

Reviewer 1 #14. The evolutionary theory interpretation of loneliness and hyper-vigilance is introduced in the discussion without prior grounding in the introduction or methods, appearing somewhat post-hoc.

The introduction of the theory was presented as a reason for the correlation. The idea was not presented in the intro or methods because the study was not grounded in this theoretical concept. The recognition that the theory may explain our results will provide a foundation for future research in this area.  

Reviewer 1 #15. The emphasis on community resilience as a solution feels overstated relative to the small, standardized path coefficient (β = -.13) observed in the model.

We appreciate the reviewer’s comment. However, the authors decided to maintain an emphasis on community resilience in the Discussions section. The rationale for this decision is as follows: Although community resilience made a small contribution to loneliness, its statistically significant association, together with its strong association with perceived social support, suggests that it remains an important contextual factor for understanding loneliness.

Reviewer 1 #16. The limitations section is inadequate. It minimally addresses the cross-sectional design but fails to discuss potential reverse causality, unmeasured confounders, or social desirability bias in self-reports of loneliness and substance use.

We thank the reviewer for this constructive critique. We agree that a robust public health manuscript requires a transparent evaluation of methodological constraints. We added some points in the limitations.

Reviewer 1 #17. The authors do not discuss the relatively low explained variance in sleep disturbances (R² = .24), which suggests the model misses important predictors.

We appreciate the reviewer’s comment. In response, we have added an additional statement to the sixth point in the Limitations and Future Research section.

Reviewer 1 #18. The overall writing and organization could be improved. There are noticeable grammatical issues, awkward phrasings, and inconsistencies (e.g., “Sleeping Disturbances” vs. “Sleep Disturbances” in tables).

Thank you. We have edited the document to remove awkward phrasing and inconsistencies we identified. 

Reviewer 1 #19. The conclusions and implications for intervention are overly broad and optimistic given the study’s methodological constraints, small effect sizes for some paths, and regional specificity of the sample. Stronger tempering of public health recommendations is needed.

We appreciate the reviewer’s comment. In response, we have thoroughly revised the final paragraphs of the Discussion and Conclusion sections to tone down our recommendations.

Reviewer 2 Report

Comments and Suggestions for Authors

Very interesting and well written article. The references seem relevant, topical and current.

Analyses are clearly stated; charts are clear and provide graphic presentations of the results.

In line 138/140 It would be helpful to discuss that the models are distinct: Model 1 presents personal or individual, loneliness. Model 2 presents community issues but also individual issues by adding two distinctly different issues "anxiety "using the community issues and "substance abuse" again an individual issue. I am confused as to why individual and community issues were combined?

The author state that by identifying community resilience as a protective factor against loneliness and subsequent anxiety, their study moves sleep health interventions beyond clinical, individual-focused treatments (like sleep hygiene or sleep medication) toward community-level public health strategies and social infrastructure investments. Why not present a model that clearly separates the individual and community level strategies. 

I would have preferred a comparison of the community demographic data with national or even statewide data that would show the anxiety that is based on a lack of financial resources and a lack of community resources.

Community development and emergency infrastructure are clearly shown to be direct investments in mental and physical health. Although initially a significant direct relationship was observed between loneliness and sleep disturbances. The addition of community resilience and social support were associated with lower levels of loneliness. The conclusion that loneliness is directly and positively associated with sleep disturbances; however, community resilience and perceived social support are considered protective factors against loneliness is well written.

Author Response

Overall: Very interesting and well written article. The references seem relevant, topical and current. Analyses are clearly stated; charts are clear and provide graphic presentations of the results.

We appreciate the reviewer’s positive feedback. 

Reviewer 2 #1. In line 138/140 It would be helpful to discuss that the models are distinct: Model 1 presents personal or individual, loneliness. Model 2 presents community issues but also individual issues by adding two distinctly different issues "anxiety "using the community issues and "substance abuse" again an individual issue. I am confused as to why individual and community issues were combined?

We appreciate the reviewer’s comment. In response, we have revised the statement in Section 1.2, The Current Study, to improve clarity.

Reviewer 2 #2. The author state that by identifying community resilience as a protective factor against loneliness and subsequent anxiety, their study moves sleep health interventions beyond clinical, individual-focused treatments (like sleep hygiene or sleep medication) toward community-level public health strategies and social infrastructure investments. Why not present a model that clearly separates the individual and community level strategies. 

We appreciate the reviewer’s thankful comments and suggestion. We considered variables in this study with different conceptual levels (individual vs. community), our data structure features an individual-level unit of analysis measuring perceived community resilience as well as individual level anxiety and sleep. Therefore, we thought SEM is the best model for the analysis.

Reviewer 2 #3. I would have preferred a comparison of the community demographic data with national or even statewide data that would show the anxiety that is based on a lack of financial resources and a lack of community resources.

Thank you for the feedback. In our future research on this topic, we will be sure to collect this data, as it will offer additional insight into the constructs. 

Reviewer 2 #4. Community development and emergency infrastructure are clearly shown to be direct investments in mental and physical health. Although initially a significant direct relationship was observed between loneliness and sleep disturbances. The addition of community resilience and social support were associated with lower levels of loneliness. The conclusion that loneliness is directly and positively associated with sleep disturbances; however, community resilience and perceived social support are considered protective factors against loneliness is well written.

We appreciate the reviewer’s positive feedback. 

Reviewer 3 Report

Comments and Suggestions for Authors

1. The title is appropriate for the content of the article, which focuses on the relationship between loneliness and sleep disorders, identifying the role of resilience and selected psychosocial variables in these relationships.
2. The abstract should be supplemented with a more detailed description of the study group – the sample size and study location are indicated, but no further details (age, gender) are provided. The research method, including the research tools used in the presented analyses, are also omitted.
3. The literature review requires further clarification of the concept of loneliness – the current definition of this concept is too general, and it is not entirely clear what the authors mean by loneliness. Similarly, it is important to clarify whether anxiety, as understood, is an emotion or a disorder, whether it has a specific object or is objectless. The symptoms of anxiety are described rather than the accepted definition of this concept. Community Resilience and Social Support are sufficiently clarified, and these concepts are clearly presented.
4. The study tested two models of relationships – one concerned the direct associations between loneliness and sleep disorders, and the other considered mediators of the analyzed relationships. The tested models were presented clearly and concisely.
5. The study was conducted eight years ago (in 2018). Is there any basis to assume that the results are current? This is especially true given that the study was conducted before the COVID-19 pandemic, which could have had a significant impact on the sense of loneliness and other analyzed psychological variables, such as anxiety.
6. It was indicated that the project was reviewed and approved by the Institutional Review Board at the university affiliated with the researchers. Document data (e.g., consent number) is missing.
7. Information is missing as to whether and how anonymity was ensured for the study participants, whether participation was voluntary – how was ethical standards for scientific research ensured? The inclusion and exclusion criteria were also not specified.
8. The research tools were properly described, and their characteristics contain the required information.
9. The results were presented accurately, well-organized, and clearly.
10. The discussion of the results includes an in-depth interpretation of the results, with suggestions for their application in public health initiatives. Of particular interest is the importance of community resilience for the perception of loneliness and, consequently, for improving sleep quality. This provides a broader perspective on the determinants of community well-being.

Author Response

Reviewer 3 #1. The title is appropriate for the content of the article, which focuses on the relationship between loneliness and sleep disorders, identifying the role of resilience and selected psychosocial variables in these relationships.

We appreciate the reviewer’s positive feedback. 

Reviewer 3 #2.    The abstract should be supplemented with a more detailed description of the study group – the sample size and study location are indicated, but no further details (age, gender) are provided. The research method, including the research tools used in the presented analyses, are also omitted.

We agree with the reviewer that these details strengthen the clarity of the abstract. We have revised the abstract to include key demographic characteristics of the study group (mean age and gender distribution). 

Reviewer 3 #3. The literature review requires further clarification of the concept of loneliness – the current definition of this concept is too general, and it is not entirely clear what the authors mean by loneliness. Similarly, it is important to clarify whether anxiety, as understood, is an emotion or a disorder, whether it has a specific object or is objectless. The symptoms of anxiety are described rather than the accepted definition of this concept. Community Resilience and Social Support are sufficiently clarified, and these concepts are clearly presented.

We agree that the concepts need to be clarified and have provided a clearer definition of loneliness as it relates to this manuscript. We have also clarified our definition of anxiety. 

Reviewer 3 #4. The study tested two models of relationships – one concerned the direct associations between loneliness and sleep disorders, and the other considered mediators of the analyzed relationships. The tested models were presented clearly and concisely.

We appreciate the reviewer’s positive feedback. 

Reviewer 3 #5. The study was conducted eight years ago (in 2018). Is there any basis to assume that the results are current? This is especially true given that the study was conducted before the COVID-19 pandemic, which could have had a significant impact on the sense of loneliness and other analyzed psychological variables, such as anxiety.

Thank you for this question. We believe the constructs still apply, as the main issues persist today. Therefore, our findings can still guide future explorations and interventions. We have added a statement in the limitations section. 

Reviewer 3 #6. It was indicated that the project was reviewed and approved by the Institutional Review Board at the university affiliated with the researchers. Document data (e.g., consent number) is missing.

The IRB protocol number was added.

Reviewer 3 #7. Information is missing as to whether and how anonymity was ensured for the study participants, whether participation was voluntary – how was ethical standards for scientific research ensured? The inclusion and exclusion criteria were also not specified.

We have updated Section 2.1 (Sampling Procedures) to explicitly detail our ethical protections and participant criteria. We explicitly listed our inclusion criteria (age 18, permanent residency in the sampled geographic zone) and exclusion criteria (non-residents, inability to provide consent).

Reviewer 3 #8. The research tools were properly described, and their characteristics contain the required information.

We appreciate the reviewer’s positive feedback. 

Reviewer 3 #9. The results were presented accurately, well-organized, and clearly.

We appreciate the reviewer’s positive feedback. 

Reviewer 3 #10. The discussion of the results includes an in-depth interpretation of the results, with suggestions for their application in public health initiatives. Of particular interest is the importance of community resilience for the perception of loneliness and, consequently, for improving sleep quality. This provides a broader perspective on the determinants of community well-being.

We appreciate the reviewer’s positive feedback. 

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

I appreciate the authors' hard work and their efforts to improve the manuscript. While a significant portion of my previous comments has been addressed, there are still critical structural, methodological, and interpretive issues that remain unresolved. Many concerns were merely added to the limitations section rather than being addressed through data re-analysis or model refinement. Therefore, I recommend a Major Revision before this manuscript can be considered for publication. Please find my specific revision requests listed below:

1. The authors explicitly state that the data was collected in the fall of 2018. While acknowledging this in the limitations section is a step forward, a 2018 dataset leaves a major gap regarding the massive societal, psychological, and behavioral shifts caused by the COVID-19 pandemic. The authors must thoroughly expand their literature review and discussion to justify why a pre-pandemic baseline for loneliness, anxiety, and coping mechanisms remains highly relevant and how these structural pathways might have changed or persisted in the post-pandemic landscape.

2. The measurement of highly complex public health outcomes relies on extreme short-forms, such as the GAD-2 for anxiety, a 2-item index for substance use coping, and a 2-item index for sleep disturbances. While the congeneric reliability is acceptable in this sample, a 2-item self-report scale for sleep disturbances only captures the surface of sleep pathology. The authors need to temper their clinical and public health claims, explicitly detailing how these brief screenings limit the clinical diagnostic utility of their structural model.

3. In the full mediating model, the Normed Fit Index (NFI = .94) still falls below the universally accepted threshold of 0.95 for a good fit. While adding the normed chi-square ratio provides supplementary context, the model fit remains marginally acceptable at best. The authors must adjust their narrative throughout the Results and Discussion sections to reflect a more cautious and conservative interpretation of their structural model's alignment with the data.

4. The current structural equation model explains only 24% of the variance in sleep disturbances. This means that 76% of population-wide sleep issues are driven by unmeasured confounders or alternative pathways. The authors must clearly discuss what major unmeasured variables, such as physical health conditions, financial strain, or shifts in employment, are missing from this model that might explain the remaining variance.

5. The path coefficient connecting Community Resilience to Loneliness is quite small. Despite this weak effect, the public health implications and abstract heavily emphasize community infrastructure and structural target changes as primary interventions. The authors must align their policy and practical recommendations with the actual strength of their data, as overstating the practical impact of a weak pathway undermines the paper’s scientific credibility.

6. While the authors modified several causal statements in the main Discussion section, the Highlights and Abstract still contain highly directional and causal terminology, such as stating that anxiety fully drives the path from isolation to sleep loss or that community resilience and perceived social support directly mitigate loneliness. Because cross-sectional data cannot establish chronological precedence or definitive directionality, all directional claims in the Highlights and Abstract must be completely rewritten to emphasize associations rather than causal dynamics.

7. The model shows that lonelier individuals are significantly more likely to utilize substance use coping ($\beta = .29, p < .001$), yet this coping mechanism shows a completely non-significant link to sleep disturbances ($\beta = .01, p = .872$). This directly contradicts a substantial body of literature regarding self-medication and alcohol or drug-induced sleep architecture disruption. The added paragraph in the discussion must be expanded to provide a rigorous, theoretically sound explanation for why this specific coastal Mississippi sample presents an anomaly to established physiological and psychiatric literature.

Overall, I would like to re-evaluate the paper after appropriate revisions.

Best regards

Author Response

I appreciate the authors' hard work and their efforts to improve the manuscript. While a significant portion of my previous comments have been addressed, there are still critical structural, methodological, and interpretive issues that remain unresolved. Many concerns were merely added to the limitations section rather than being addressed through data re-analysis or model refinement. Therefore, I recommend a Major Revision before this manuscript can be considered for publication. Please find my specific revision requests listed below:

Q1. The authors explicitly state that the data was collected in the fall of 2018. While acknowledging this in the limitations section is a step forward, a 2018 dataset leaves a major gap regarding the massive societal, psychological, and behavioral shifts caused by the COVID-19 pandemic. The authors must thoroughly expand their literature review and discussion to justify why a pre-pandemic baseline for loneliness, anxiety, and coping mechanisms remains highly relevant and how these structural pathways might have changed or persisted in the post-pandemic landscape.

We thank the reviewer for this insightful and critical point. We agree that the COVID-19 pandemic drastically changed the landscape of population-level loneliness, anxiety, and sleep health. However, we argue that this 2018 dataset provides a rare and crucial pre-pandemic structural baseline. Because post-pandemic data is heavily confounded by global health anxieties, economic inflation, and acute pandemic-related isolation, it is nearly impossible to decouple "normal" chronic environmental vulnerability from acute pandemic disruption. By evaluating these pathways in 2018, we capture how community resilience and social support organically buffer loneliness and sleep disturbances under "steady-state" chronic ecological stress (the disaster-prone Gulf Coast) without the confounding noise of a once-in-a-century global health crisis. We added a paragraph in the Introduction and Discussion sections related to this matter.

Q2. The measurement of highly complex public health outcomes relies on extreme short-forms, such as the GAD-2 for anxiety, a 2-item index for substance use coping, and a 2-item index for sleep disturbances. While congeneric reliability is acceptable in this sample, a 2-item self-report scale for sleep disturbances only captures the surface of sleep pathology. The authors need to temper their clinical and public health claims, explicitly detailing how these brief screenings limit the clinical diagnostic utility of their structural model.

Regarding the survey questionnaire, the reviewer specifically noted two measures: the GAD-2 and the 2-item sleep disturbance scale. Although the GAD-2 is reliable and valid in previous studies, the reviewer may be concerned that it provides limited content coverage. Especially for sleep disturbance, the two items were created by our research team based on their expertise. To address this concern, we may add a sentence emphasizing the benefits of brief measures in large-scale surveys.

Q3. In the full mediating model, the Normed Fit Index (NFI = .94) still falls below the universally accepted threshold of 0.95 for a good fit. While adding the normed chi-square ratio provides supplementary context, the model fit remains marginally acceptable at best. The authors must adjust their narrative throughout the Results and Discussion sections to reflect a more cautious and conservative interpretation of their structural model's alignment with the data.

We appreciate this feedback and have incorporated this concern into the Results and Discussion sections by adding the following sentences to the manuscript

Results (lines 346-347)

Original: Overall, the fit indices suggested a reasonable to marginally acceptable fit to the sample data: ?2( 59, N = 310) = 103.38, p < .001, χ²/df = 1.75, NFI = .94, TLI = .96, CFI = .97, RMSEA = .05 (90% CI [.03, .07]), a probability of close fit (PCLOSE) = .51.

Revision: This hypothesized model yielded the following fit indices: ?2( 59, N = 310) = 103.38, p < .001, χ²/df = 1.75, NFI = .94, TLI = .96, CFI = .97, RMSEA = .05 (90% CI [.03, .07]), a probability of close fit (PCLOSE) = .51. Overall, these indices suggested a reasonable to marginally acceptable fit to the sample data. However, the NFI (.94) fell slightly below the conventional cutoff of .95, indicating that the model's fit should not be considered optimal.

Discussion - Limitations and Future Research (lines 453) 

Original: Sixth, although the final model explained 24% of the variance in sleep disturbances, a substantial proportion of variance remained unexplained. Future studies should consider incorporating additional biopsychosocial factors, including physical health status, perceived stress, traumatic events, and other psychological distresses, to provide a more comprehensive understanding of sleep disturbances.

Revision: Sixth, overall, the hypothesized models demonstrated reasonable to marginally acceptable fit across most indices. However, the NFI for the model including anxiety and substance use coping as potential mediators was .94, slightly below the conventional cutoff of .95, indicating that this model's fit should not be considered optimal. In addition, although the final model explained 24% of the variance in sleep disturbances, 76% of the variance remained unexplained, suggesting that additional unmeasured confounders or alternative pathways may be involved. Future research should examine how physical health conditions and additional mental health conditions influence sleep, as well as how lifestyle factors (e.g., physical activity) and life stressors (e.g., financial strain and employment changes) shape these associations. These factors have been identified in previous studies as important contributors to understanding sleep (Brossoit et al., 2025; Chessa et al., 2025). Therefore, the findings from the current model should be interpreted with caution, and future research should replicate this model using larger, more diverse samples while incorporating these additional variables to further evaluate its robustness and provide a more comprehensive understanding of sleep disturbances.

Q4. The current structural equation model explains only 24% of the variance in sleep disturbances. This means that 76% of population-wide sleep issues are driven by unmeasured confounders or alternative pathways. The authors must clearly discuss what major unmeasured variables, such as physical health conditions, financial strain, or shifts in employment, are missing from this model that might explain the remaining variance.

We have revised the sixth limitation to incorporate this concern.

Revision: Sixth, overall, the hypothesized models demonstrated reasonable to marginally acceptable fit across most indices. However, the NFI for the model including anxiety and substance use coping as potential mediators was .94, slightly below the conventional cutoff of .95, indicating that this model's fit should not be considered optimal. In addition, although the final model explained 24% of the variance in sleep disturbances, 76% of the variance remained unexplained, suggesting that additional unmeasured confounders or alternative pathways may be involved. Future research should examine how physical health conditions and additional mental health conditions influence sleep, as well as how lifestyle factors (e.g., physical activity) and life stressors (e.g., financial strain and employment changes) shape these associations. These factors have been identified in previous studies as important contributors to understanding sleep (Brossoit et al., 2025; Chessa et al., 2025). Therefore, the findings from the current model should be interpreted with caution, and future research should replicate this model using larger, more diverse samples while incorporating these additional variables to further evaluate its robustness and provide a more comprehensive understanding of sleep disturbances.

Q5. The path coefficient connecting Community Resilience to Loneliness is quite small. Despite this weak effect, the public health implications and abstract heavily emphasize community infrastructure and structural target changes as primary interventions. The authors must align their policy and practical recommendations with the actual strength of their data, as overstating the practical impact of a weak pathway undermines the paper’s scientific credibility.

We agree with the reviewer’s point and thank the reviewer for ensuring our conclusions match the empirical weight of our data. The reviewer is correct that the path coefficient from Community Resilience to Loneliness (β = -.13, p = .046) is modest. We have revised the Implications and Discussion sections to tone down the language and explicitly acknowledge this modest effect size.

However, we have also added a brief public health justification for why a small structural effect remains highly meaningful. In population health, small effect sizes targeting upstream, structural environment factors (like community infrastructure) can yield substantial aggregate public health benefits because they affect an entire population simultaneously, unlike individual clinical interventions which have larger effects but very limited reach. We have clarified this distinction in the manuscript, so our recommendations are scientifically grounded and realistic.

Q6. While the authors modified several causal statements in the main Discussion section, the Highlights and Abstract still contain highly directional and causal terminology, such as stating that anxiety fully drives the path from isolation to sleep loss or that community resilience and perceived social support directly mitigate loneliness. Because cross-sectional data cannot establish chronological precedence or definitive directionality, all directional claims in the Highlights and Abstract must be completely rewritten to emphasize associations rather than causal dynamics.

We have audited both sections and fully rewritten all causal claims to reflect strictly cross-sectional, non-directional associations. The explicit changes are detailed below:

Original: By demonstrating that anxiety fully drives the path from isolation to sleep loss...

Revision: By demonstrating that anxiety fully mediates the relationship between loneliness and sleep disturbances, this study provides a framework...

Original: ...upstream factors that directly mitigate loneliness and anxiety...

Revision: ...upstream factors inversely associated with loneliness and anxiety...

Abstract Revisions:

Original: This direct path, however, became non-significant upon the inclusion of anxiety and substance use coping, shifting instead to an indirect pathway through anxiety.

Revision: This direct association, however, was non-significant upon the inclusion of anxiety and substance use coping, revealing instead a statistically significant indirect association operating through anxiety symptoms.

Original: ...nested system in which community strengths and individual support system jointly protect against isolation...

Revision: ...nested system in which community strengths and individual support systems are jointly positioned as upstream correlations of lower individual isolation...

Q7. The model shows that lonelier individuals are significantly more likely to utilize substance use coping (beta = .29, p < .001), yet this coping mechanism shows a completely non-significant link to sleep disturbances (beta = .01, p = .872). This directly contradicts a substantial body of literature regarding self-medication and alcohol or drug-induced sleep architecture disruption. The added paragraph in the discussion must be expanded to provide a rigorous, theoretically sound explanation for why this specific coastal Mississippi sample presents an anomaly to established physiological and psychiatric literature.

The following section was added to the Discussion section (line 389).

Original: Interestingly, although lonelier individuals were more likely to engage in substance use coping, the coping strategy was not significantly related to sleep disturbances within the mediation model.

Revision: Interestingly, although lonelier individuals were more likely to engage in substance use coping, the coping strategy was not significantly related to sleep disturbances within the mediation model, which is inconsistent with prior research supporting the influence of substance use on sleep architecture (Laudie et al. [18]; Hernandez & Griggs [19]). One possible explanation is that the substance use coping measure captured the tendency to rely on substances as a coping strategy, but did not assess the frequency, quantity, timing, or type of alcohol or drug use — factors that may have differential effects on sleep architecture (Gardiner et al., 2025; Hernandez & Griggs [19]). Future research should incorporate more detailed measures of substance use, including its frequency, quantity, timing, and type, to better capture its potential impact on sleep.

Overall, I would like to re-evaluate the paper after appropriate revisions.