The Role of Psychological Factors in Young Adult Snacking: Exploring the Intention–Behaviour Gap

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

1. 'High consumption of unhealthy snacks, or 45 foods high in sugar, salt and fats, and low in nutrients [1] are associated with adverse 46 health implications. These include the development of chronic and non-communicable 47 diseases such as cardiovascular diseases, Type 2 diabetes, cancers, obesity and depression 48 [1, 7-12].'   are there any differences between male and female and in a developmental fashion? could the author address this?

2. 'This is known as the intention-behaviour gap and is commonly noted as a weakness 77 of the theory of planned behaviour [25, 26]. In subsequent attempts to improve the pre-78 dictive ability of the theory of planned behaviour, Hall and Fong [26] note that the theory 79 may best predict conscious, controllable and less habitual behaviours.'  again, maybe cite here which variables may be of interest

3. '

   Participants were aged between 18 and 30 years (M = 24.73, SD = 3.23) and most iden-127 tified as women (94.1%) while 5.9% identified as men. Most resided in Western Australia 128 (48%), while the remainder lived in Victoria (16.7%), New South Wales (15.8%), Queens-129 land (9.3%) Australian Capital Territory (4.3%), South Australia (4.3%) or Tasmania 130 (1.5%). During the data collection period, most (74.6%) indicated that they were currently 131 in a full COVID-19 lockdown period. Most participants (70.9%) also had a household in-132 come below $104,999, while the remainder (29.9%) had a household income between 133 $105,000 - $200,000 or greater. Almost half of all participants (48.6%) had a BMI measure 134 in the ‘healthy weight’ range between 18.5 to 24.9 (M = 26.14, SD = 6.48), did not experience.

   anxiety or depression (66.6%) and engaged in physical activity 2 to 3 days a week (M = 136 2.53, SD = 2.05).

   .' this reviewer thinks that alla this information could be summarized in a a table, particularly data on BMI and Psychological variables.

   How were data about anxiety or depression collected? questionaires? single items response?
4. statistical analyses and data results. Although the statistical method is valid and useful this section and consequently the results section is very hard to follow. I would suggest to use tables to describe the results.
5. Maybe to let the readers better follow thee statistical reasoning it would be easier to use a SEM model such as a moderation model rather than different logistic regressions.
6. the discussion should be modified if SEM is adopted.

thank you for the opportunity to revise this ms. the topic is really important and useful

Author Response

Response to Reviewers

Reviewer 1

Comment 1: “High consumption of unhealthy snacks, or foods high in sugar, salt and fats, and low in nutrients [1] are associated with adverse health implications. These include the development of chronic and non-communicable diseases such as cardiovascular diseases, Type 2 diabetes, cancers, obesity and depression [1, 7-12].” Are there any differences between male and female and in a developmental fashion? Could the author address this?

Response: Thank you for this request. We have added further information on gender differences in the development on non-communicable diseases. Please see this change highlighted in the revised manuscript and included below.

Line 48-52: These include the development of chronic and non-communicable diseases such as cardiovascular diseases, Type 2 diabetes, cancers, obesity and depression among others [1, 7-12]. Over the lifespan, men are more likely to develop cardiovascular disease [13], stroke and lung disease than women, while women are more likely to develop arthritis [14], depression and anxiety than men [15].

Comment 2: “This is known as the intention-behaviour gap and is commonly noted as a weakness of the theory of planned behaviour [25, 26]. In subsequent attempts to improve the predictive ability of the theory of planned behaviour, Hall and Fong [26] note that the theory may best predict conscious, controllable and less habitual behaviours.” Again, maybe cite here which variables may be of interest.

Response: Thank you for raising this. We have now included the specific variables of interest to improve the readability of the text. Please see this change highlighted in the revised manuscript and included below.

Line 84-91: In subsequent attempts to improve the predictive ability of the theory of planned behaviour, Hall and Fong [29] note that the theory may best predict conscious, controllable and less habitual behaviours. Contrary to the theory of planned behaviour, intention is only likely to directly and primarily influence discrete (one-off) behaviours in relatively supportive ecological contexts. Therefore, other variables may need to be considered when assessing unhealthy snacking, as it is often hedonically motivated, habitual and unintentionally performed due to lapses in self-control [27, 30, 31].

Comment 3: “Participants were aged between 18 and 30 years (M = 24.73, SD = 3.23) and most identified as women (94.1%) while 5.9% identified as men. Most resided in Western Australia (48%), while the remainder lived in Victoria (16.7%), New South Wales (15.8%), Queensland (9.3%) Australian Capital Territory (4.3%), South Australia (4.3%) or Tasmania (1.5%). During the data collection period, most (74.6%) indicated that they were currently in a full COVID-19 lockdown period. Most participants (70.9%) also had a household income below $104,999, while the remainder (29.9%) had a household income between $105,000 - $200,000 or greater. Almost half of all participants (48.6%) had a BMI measure in the ‘healthy weight’ range between 18.5 to 24.9 (M = 26.14, SD = 6.48), did not experience anxiety or depression (66.6%) and engaged in physical activity 2 to 3 days a week (M = 2.53, SD = 2.05).” This reviewer thinks that all this information could be summarized in a table, particularly data on BMI and Psychological variables. How were data about anxiety or depression collected? Questionnaires? Single items response?

Response: Thank you for this suggestion and query to clarify the paper. We have now included a table to summarise the demographic information. Data regarding anxiety and depression was collected by one item. However, we have removed this information following another reviewer’s suggestion as the results are not presented according to these variables. Please see the demographic information summarised in Table 1 in the revised manuscript and included below.

Line 139-141:

Table 1. Participant demographics (N = 323)

Note. * Assessed only from the proportion of respondents who were experiencing COVID-19 restrictions at the time of data collection.

Comment 5: Although the statistical method is valid and useful, this section and consequently the results section is very hard to follow. I would suggest to use tables to describe the results.

Response: Thank you for this feedback. We have updated Tables 3, 4 and 5 to summarise the results of the three hierarchical multiple regressions. Some repetitive information, which was previously outlined in-text and is now displayed in each table, was also removed to improve readability. Please see the changes in Tables 3, 4 and 5, and textual changes highlighted in the revised manuscript and included below.

Line 238-247: In step one, physical activity engagement was added to the model as a control variable. In step two, intention was added to the model. In step three, enjoyment of food and satiety responsiveness were added to the model. In the final step, stress was added to the model. The overall model accounted for a significant 6.4% of variance in sweet snack consumption, R² = .06, F (5, 316) = 4.31, p < .001. Physical activity engagement, and stress were the only significant factors. See Table 3 for the individual contributions of variables in each step of the model.

Table 3. Individual contributions of variables in the regression explaining sweet snack consumption

(N = 323).

Note. * p < .05, ** p < .001

Line 249-259: In step one, physical activity engagement was added to the model as a control variable. In step two, intention was added to the model. In step three, enjoyment of food and satiety responsiveness were added to the model. In the final step, stress was added to the model. The overall model accounted for a significant 6.6% of variance in savoury snack consumption, R² = .07, F (5, 316) = 4.48, p < .001. Physical activity engagement was the only significant factor. See Table 4 for the individual contributions of variables in each step of the model.

Table 4. Individual contributions of variables in the regression explaining savoury snack consumption (N = 323).

Note. * p < .05, ** p < .001

Line 261-270: In step one, physical activity engagement was added to the model as a control variable. In step two, intention was added to the model. In step three, enjoyment of food and satiety responsiveness were added to the model. In the final step, stress was added to the model. The overall model accounted for a significant 6.2% of variance in sugar-sweetened beverage consumption, R² = .06, F (5, 316) = 4.19, p < .001. Physical activity engagement and satiety responsiveness were the only significant factors. See Table 5 for the individual contributions of variables in each step of the model.

Table 5. Individual contributions of variables in the regression explaining savoury snack consumption (N = 323).

Note. * p < .05, ** p < .001

Comment 6: Maybe to let the readers better follow the statistical reasoning it would be easier to use a SEM model such as a moderation model rather than different logistic regressions.

Response: Thank you for this thoughtful suggestion. We considered using structural equation modelling to analyse our data. However, we instead chose to apply hierarchical multiple regression analyses as we did not plan for any moderation or mediation analyses, which required the advanced statistical capabilities of SEM [1]. Instead, we aimed to assess the incremental and unique contribution of each factor in explaining the outcome variables, which is suited for hierarchical regression analyses [2]. Additionally, SEM typically requires much larger sample sizes than ours to meet the assumptions of statistical power and to ensure stable and reliable parameter estimates [3]. Therefore, we believe that hierarchical regression offers a more robust and interpretable approach for our data. Please see this clarification highlighted in the revised manuscript and included below.

References:

1.Gunzler, D., et al., Introduction to mediation analysis with structural equation modeling. Shanghai Arch Psychiatry, 2013. 25(6): p. 390-4.

2.Jeong, Y. and M.J. Jung, Application and Interpretation of Hierarchical Multiple Regression. Orthopaedic Nursing, 2016. 35(5): p. 338-341.

3. Sim, M., S.-Y. Kim, and Y. Suh, Sample Size Requirements for Simple and Complex Mediation Models. Educational and Psychological Measurement, 2022. 82(1): p. 76-106.

Line 224-229: Hierarchical multiple regression analyses were applied instead of structural equation modelling due to much larger sample sizes typically required in structural equation modelling to achieve adequate statistical power and ensure stable and reliable parameter estimates [54] Additionally, there were no planned moderation or mediation analyses, which required these pathways to be assessed via structural equation modelling [55].

Comment 7: The discussion should be modified if SEM is adopted.

Response: Thank you for this recommendation to ensure continuity following any changes to the analysis. We have not applied structural equation modelling so that no changes were applied to the results and discussion.

Comment 8: Thank you for the opportunity to revise this manuscript. The topic is really important and useful.

Response: Thank you for taking the time to review the manuscript and for providing detailed comments to improve it. We hope the changes and clarifications above will be sufficient to address your concerns.

Reviewer 2 Report

Comments and Suggestions for Authors

Comments and Suggestions for Authors

Manuscript Nutrients-3768454

The objective of this study was to examine the determinants of unhealthy snack consumption among young adults (aged 18 to 30 years), with a focus on three major snack categories: sweet snacks, savory snacks, and sugar-sweetened beverages. The findings indicate that the psychological factors influencing consumption vary across snack types, highlighting the need for snack-type-specific interventions. Engagement in physical activity and perceived stress emerged as significant predictors of sweet snack consumption, whereas only physical activity engagement was significantly associated with savory snack consumption. Given its methodological rigor and practical implications for nutritional intervention strategies, this study presents valuable insights and may be considered for publication in Nutrients.

Below, I include some suggestions for the authors to improve the quality of the manuscript.

SUGGESTIONS

The title, summary, and keywords are appropriate.

INTRODUCTION

The introduction is clearly written and well-structured, albeit somewhat lengthy—understandably so, given the inclusion of three minor sub-sections. Nevertheless, it would benefit from a more thorough integration of recent, relevant literature to strengthen its contextual foundation.

MATERIAL AND METHODS

Clarified Version: At the end of the study, participants were thanked for their time and asked to provide their contact details so they could receive a reward. Everyone who completed the 20–25-minute online survey was entered into a prize draw to win one of six AUD $50 gift cards. This amount was slightly more than what someone would earn at minimum wage for the time it took to complete the survey.

As for how participants were excluded: could you clarify whether respondents were automatically screened out during the survey if they didn’t meet the required criteria (e.g., based on their answers to early questions), or whether all responses were collected first and then filtered later during data cleaning and processing?

Stress was assessed using a single-item measure: “On a scale from 1 to 10, with 1 being not stressed at all and 10 being extremely stressed, how would you rate your stress over the past 30 days?” Responses were recorded on a 10-point Likert-type scale (1 = not stressed, 10 = very stressed). A single-item approach was chosen to minimize participant burden, as the aim was to screen for general stress levels rather than conduct a detailed clinical evaluation. Prior research has demonstrated that single-item stress measures can yield acceptable levels of test-retest reliability and show strong concurrent validity with multi-item self-report instruments [44, 45]. Higher scores reflect greater perceived stress during the preceding 30 days.

However, it should be noted that retrospective self-assessment of stress over a 30-day period may be subject to recall biases, including potential overestimation or underestimation of stress levels. This limitation should be considered when interpreting the results, as memory-based judgments of stress can be influenced by recent events, mood at the time of reporting, and individual differences in cognitive bias.

Unhealthy snack consumption was assessed using a modified version of the Swiss Snack Consumption Scale. However, it remains unclear whether this modified scale has been previously validated on an Australian sample.

The research methods are thoroughly described and appropriately justified. The sampling strategy, measurement instruments, and analytical procedures are suitable and rigorously applied. Ethical standards have been duly observed throughout the study. The data collected demonstrate validity and reliability.

RESULTS

Results are presented with clarity and interpreted accurately in line with the research objectives.

DISCUSSION

The discussion would benefit from a clearer scientific grounding by integrating and contextualizing recent findings from similar studies, thereby better connecting them with the current research.

CONCLUSION

While the conclusions are substantiated by the data, I suggest they be revised in light of the recent modifications.

Recommendation:

Accept with minor changes

Author Response

Response to Reviewers

Reviewer 2

Comment 1: The objective of this study was to examine the determinants of unhealthy snack consumption among young adults (aged 18 to 30 years), with a focus on three major snack categories: sweet snacks, savory snacks, and sugar-sweetened beverages. The findings indicate that the psychological factors influencing consumption vary across snack types, highlighting the need for snack-type-specific interventions. Engagement in physical activity and perceived stress emerged as significant predictors of sweet snack consumption, whereas only physical activity engagement was significantly associated with savory snack consumption. Given its methodological rigor and practical implications for nutritional intervention strategies, this study presents valuable insights and may be considered for publication in Nutrients. Below, I include some suggestions for the authors to improve the quality of the manuscript.

Response: Thank you for taking the time to review the manuscript and for providing detailed comments to improve it. We hope the changes and clarifications to each of your points below will be sufficient to address your concerns.

Comment 2: The title, summary, and keywords are appropriate.

Response: Thank you for your detailed review to ensure the suitability of the title, summary and keywords.

Comment 3: The introduction is clearly written and well-structured, albeit somewhat lengthy—understandably so, given the inclusion of three minor sub-sections. Nevertheless, it would benefit from a more thorough integration of recent, relevant literature to strengthen its contextual foundation.

Response: Thank you for this feedback to improve the contextual relevance of this study. We have now integrated more literature in the Introduction. Please see the changes highlighted in the revised manuscript and included below.

Line 33-37: Driven by modern urbanisation and changing consumer lifestyles, which prioritise convenient food options, the global snacking industry accounts for over $135 billion annually, as of 2024 [2]. In Australia, snack food consumption increased by 10% per capita between 2018 and 2023, with 38.6% of total dietary energy intake derived from snack foods [3].

Line 57-63: During this period, young adults often note obstacles to healthy eating related to inefficient time management, preparation needs, low motivation and greater taste preference for unhealthy foods [18]. For university students, barriers include restricted physical environments (e.g., lack of cooking facilities and food availability), study commitments (e.g., timetables, exams), a lack in self-confidence in nutrition knowledge, and navigating personal factors including personal, cultural, and religious beliefs [19].

Line 67-69: The theory has been successfully applied to various dietary behaviours, including healthy food intake [21], snacking behaviour [22] and fast food consumption [23].

Line 104-106: University students with moderate to high anxiety during stressful periods, such as during COVID-19, report greater maladaptive satiety responsiveness, enjoyment of food and emotional over-eating [36].

Line 107-111: Generally, studies have linked higher stress with greater unhealthy food consumption [37, 38], including unhealthy snacking in university student populations [39]. During stressful situations, such as during COVID-19, young adults report higher consumption of unhealthy snacks than prior to the pandemic [40] and individuals may consume unhealthy snacks to cope with stress [41].

Comment 4: Clarified Version: At the end of the study, participants were thanked for their time and asked to provide their contact details so they could receive a reward. Everyone who completed the 20–25-minute online survey was entered into a prize draw to win one of six AUD $50 gift cards. This amount was slightly more than what someone would earn at minimum wage for the time it took to complete the survey.

Response: Thank you for this suggestion to improve the readability of the text. We have implemented this change and incorporated a suggestion to clarify the contact details requested in this section. Please see this highlighted in the revised manuscript and included below.

Line 151-156: At the end of the study, participants were thanked for their time and asked to provide their email address so they could receive a reward. Everyone who completed the 20–25-minute online survey was entered into a prize draw to win one of six AUD $50 gift cards. This amount was slightly more than what someone would earn at minimum wage for the time it took to complete the survey.

Comment 5: As for how participants were excluded: could you clarify whether respondents were automatically screened out during the survey if they didn’t meet the required criteria (e.g., based on their answers to early questions), or whether all responses were collected first and then filtered later during data cleaning and processing?

Response: Thank you for this query. Participants were automatically screened out of the survey if they did not meet all eligibility criteria. We have now clarified this in the revised manuscript. Please see this change highlighted in the revised manuscript and included below.

Line 147-149: Those who did not meet the eligibility criteria were automatically removed from the survey and thanked for their time.

Comment 6: Stress was assessed using a single-item measure: “On a scale from 1 to 10, with 1 being not stressed at all and 10 being extremely stressed, how would you rate your stress over the past 30 days?” Responses were recorded on a 10-point Likert-type scale (1 = not stressed, 10 = very stressed). A single-item approach was chosen to minimize participant burden, as the aim was to screen for general stress levels rather than conduct a detailed clinical evaluation. Prior research has demonstrated that single-item stress measures can yield acceptable levels of test-retest reliability and show strong concurrent validity with multi-item self-report instruments [44, 45]. Higher scores reflect greater perceived stress during the preceding 30 days. However, it should be noted that retrospective self-assessment of stress over a 30-day period may be subject to recall biases, including potential overestimation or underestimation of stress levels. This limitation should be considered when interpreting the results, as memory-based judgments of stress can be influenced by recent events, mood at the time of reporting, and individual differences in cognitive bias.

Response: Thank you for bringing up this limitation regarding the single item stress measure. We acknowledge the limitations of self-reported measures of stress and have included these in the discussion. Please see this change highlighted in the revised manuscript and included below.

Line 390-395: Similarly, stress was self-reported over a 30-day period and this data may be impacted by recall biases, including potential overestimation or underestimation of stress levels, recent events, mood at the time of reporting and individual differences in cognitive bias [75]. Although stress measures are most commonly self-reported, findings should be interpreted considering these limitations and differentiated from objective measures of physiological stress [76].

Comment 7: Unhealthy snack consumption was assessed using a modified version of the Swiss Snack Consumption Scale. However, it remains unclear whether this modified scale has been previously validated on an Australian sample. The research methods are thoroughly described and appropriately justified. The sampling strategy, measurement instruments, and analytical procedures are suitable and rigorously applied. Ethical standards have been duly observed throughout the study. The data collected demonstrate validity and reliability.

Response: Thank you for your feedback and for noting the strengths of our methodology. Although, we would like to apologise for an error in the original text and clarify that the behaviour measure was not a modified version of the Swiss Food Panel Food Frequency Questionnaire. Instead, the items were developed for this study and informed by the Swiss Food Panel Food Frequency Questionnaire and the Australian dietary guidelines. This clarification has been incorporated to accurately describe the origin and development of the measure. Although items were developed for this study, the process followed best-practice guidelines for dietary behaviour measurement by following established questionnaires and dietary guidelines. Previous studies have also developed study-specific snack consumption items to ensure relevance to the population (e.g., see [1, 2, 3]). Please see this change highlighted in the revised manuscript and included below.

References:

1.Dorina, I., et al., Utility of temporal self-regulation theory in health and social behaviours: A meta-analysis. British Journal of Health Psychology, 2023. 28(2): p. 397-438.

2.Evans, R., P. Norman, and T.L. Webb, Using Temporal Self-Regulation Theory to understand healthy and unhealthy eating intentions and behaviour. Appetite, 2017. 116: p. 357-364.

3.Gardner, B., et al., Towards parsimony in habit measurement: Testing the convergent and predictive validity of an automaticity subscale of the Self-Report Habit Index. International Journal of Behavioral Nutrition and Physical Activity, 2012. 9(1): p. 102.

Line 206-219: Unhealthy snack consumption was assessed by three items. Participants were provided a definition of unhealthy snacks and examples of foods that would be considered as sweet snacks, savoury snacks, and sugar-sweetened beverages. They were then instructed, “Please indicate how often you consume the following snacks on average using the scales provided.” Consumption of the three unhealthy snack types were assessed by one item each, “Sweet snacks (e.g., biscuits, cakes, lollies, chocolate bars, pastries, ice-cream)”, “Salty or savoury snacks (e.g., pies, pastries, biscuits, crisps/chips, processed meats)”, and “Sugar-sweetened beverages (e.g., soft drinks, mixers for alcohol, sugar-added juices, energy drinks, hot chocolate, iced tea, cordial, fruit drinks)”. Items were responded to on a 7-point Likert scale (1 = a couple of times per year, 7 = twice or more times per day). Items were developed based on an established food frequency questionnaire [51] and the Australian Dietary Guidelines [52] to best reflect foods commonly consumed by the Australian population. Higher scores indicate greater consumption of the three unhealthy snack types.

Comment 8: Results are presented with clarity and interpreted accurately in line with the research objectives.

Response: Thank you for this encouraging feedback.

Comment 9: The discussion would benefit from a clearer scientific grounding by integrating and contextualizing recent findings from similar studies, thereby better connecting them with the current research.

Response: Thank you for this suggestion. We have now integrated additional similar and recent studies in the Discussion to better compare the findings with existing literature. Please see the changes highlighted in the revised manuscript and included below.

Line 306-310: Findings contradict prior research, which found that intention was an important predictor of snacking behaviour [47, 59, 60]. Additionally, findings contradict the theory of planned behaviour [20] and recent meta-analytic findings, which indicate that intention is the largest predictor of dietary behaviours [61].

Line 316-318: Similarly, intention-behaviour relationships are generally weaker for behaviours that individuals often aim to avoid, such as unhealthy snacking [63].

Line 326-329: The influence of enjoyment of food on snacking behaviours are rarely assessed in young adult populations. But findings contradict prior research indicating that greater enjoyment of food in childhood is associated with greater appetites and overweight or obesity in later life [35].

Line 338-343: Findings contradict prior research indicating that low satiety responsiveness was associated with overall greater energy consumption [66, 67]. However, the current study differentiated the various snack types to highlight that satiety responsiveness was only a significantly factor of sugar-sweetened beverage consumption, and that higher satiety responsiveness influenced greater sugar-sweetened beverage consumption.

Line 352-359: Findings are partially consistent with recent research indicating that young adults are more likely to consume all snack types during stressful periods, such as COVID-19 [40] and results of a scoping review, which found that individuals experiencing high levels of stress most preferred energy dense snacks, followed by sweet, savoury and healthy options [71]. However, Mohamed, Mahfouz [72] found gender differences in snack type preferences among young adults experiencing high levels of stress, where women are more likely to prefer sweet snacks and men are more likely to prefer savoury snacks.

Comment 10: While the conclusions are substantiated by the data, I suggest they be revised in light of the recent modifications.

Response: Thank you for this feedback to ensure that the conclusions are consistent with the changes implemented. There were no major changes to the study findings, which needed to be reflected in the conclusion. But we have revised this section to also emphasise the implications of this study, following another reviewer’s suggestion. Please see this change highlighted in the revised manuscript and included below.

Line 413-424: Differences in the importance of psychological factors across unhealthy snack types were found and should be considered in tailored health behaviour change interventions to reduce the consumption of various snack types. Physical activity engagement and stress were significant factors of sweet snack consumption. Physical activity engagement was the only significant factor of savoury snack consumption. Physical activity engagement and satiety responsiveness were significant factors of sugar-sweetened beverage consumption. Findings indicate the psychological factors that could bridge the intention-behaviour gap in unhealthy snacking by considering both intentional and non-intentional processes of behaviour. Rational dietary decision making can be interrupted by less conscious cognitive or physiological processes. Therefore, health practitioners and health promotion campaigns may consider the involvement of psychologists to mitigate the influence of less conscious psychological factors to encourage healthy eating patterns.

Reviewer 3 Report

Comments and Suggestions for Authors

In the abstract, add the mean age (and standard deviation) of the respondents.

Line 106: among young adults (18 to 30 years) – please add: "in a sample of young adults from Australia".

Lines 132-135: What is the purpose of describing participants based on income and BMI if the results are not presented according to these variables? Please remove.

Line 136: What is the purpose of describing participants based on anxiety and depression if the results are not presented according to these variables? Furthermore, the method of assessing these variables is not specified. Please remove.

Line 136: engaged in physical activity 2 to 3 days a week (M =2.53,SD=2.05). Please add the %.

Add inclusion and exclusion criteria for the participants, instead of ‘‘A total of 440 responses were recorded, of which 323 were retained in the final dataset after excluding those who failed attention check questions, missing responses for entire scales, are pregnant or not residing in Australia‘‘.

Line 143-145: ~Participants then completed questions determining their eligibility. Those who did 143 not meet the eligibility criteria (i.e., those not aged between 18-30 years, were pregnant or 144 did not reside in Australia) were removed from the survey and thanked for their time. Participants who met all eligibility requirements~. Please remove.

Line 149: their contact details for reimbursement. What specific contact details were collected? And if participants did not agree to provide them, were they still included in the study?

Line 200:  Modified Swiss Food Panel Food Frequency Questionnaire [46]. The qustionanaire is validated in English? Please explain.

Discussion: Discuss the results also in light of the hypotheses formulated: whether they were confirmed, refuted, or partially supported, etc.

Conclusions: ,,The aim of this study was to identify the factors of unhealthy snack consumption 401 among young adults (18 to 30 years) across the three main snack types: sweet snacks, sa-402 voury snacks and sugar-sweetened beverages. We examined the role of physical activity 403 engagement as a control variable, and assessed the influence of intention, appetitive traits 404 (satiety responsiveness and enjoyment of food) and stress to explain unhealthy snack con-405 sumption and bridge the intention-behaviour gap~. The pragraph is repetitive, please remove.

To be added to the conclusions: the practical implications of the obtained results, such as the involvement of psychologists alongside medical professionals in health education, the promotion of a healthy diet, lifestyle, and so on.

The title should mention that the study was conducted during the COVID-19 lockdown. In the discussion section, it should be emphasized that during the pandemic, other factors — especially psychological ones — may have also interfered or influenced the results.

Author Response

Response to Reviewers

Reviewer 3

Comment 1: In the abstract, add the mean age (and standard deviation) of the respondents.

Response: Thank you for this feedback. We have included participants’ mean age and the standard deviation in the abstract. Please see this change below and highlighted in the revised manuscript.

Line 14-18: Australian young adults (N = 323, M = 24.73, SD = 3.23) completed an online questionnaire assessing their physical activity engagement, intention, appetitive traits (satiety responsiveness and enjoyment of food), stress and consumption of sweet snacks, savoury snacks and sugar-sweetened beverages.

Comment 2: Line 106: among young adults (18 to 30 years) – please add: "in a sample of young adults from Australia.”

Response: Thank you for this suggestion. We have now included this change. Please see this highlighted in the revised manuscript and below.

Line 114-116: The aim of this study was to identify the factors of unhealthy snack consumption in a sample of young adults from Australia (18 to 30 years) across the three main snack types: sweet snacks, savoury snacks and sugar-sweetened beverages.

Comment 3: Lines 132-135: What is the purpose of describing participants based on income and BMI if the results are not presented according to these variables? Please remove.

Response: Thank you for raising this. We included participants’ income and BMI to describe the current sample’s demographics. This information has now been removed. Please see this change reflected in Table 1, in line with another reviewer’s suggestion to summarise all demographic information in a single table. Please see Table 1 in the revised manuscript and included below.

Line 139-141:

Table 1. Participant demographics (N = 323)

Note. * Assessed only from the proportion of respondents who were experiencing COVID-19 restrictions at the time of data collection.

Comment 4: Line 136: What is the purpose of describing participants based on anxiety and depression if the results are not presented according to these variables? Furthermore, the method of assessing these variables is not specified. Please remove.

Response: Thank you for this query. We have also included information regarding anxiety and depression to describe the current sample’s demographics. This information has now been removed. Please see this change reflected in Table 1, in line with another reviewer’s suggestion to summarise all demographic information in a single table.

Comment 5: Line 136: engaged in physical activity 2 to 3 days a week (M = 2.53, SD = 2.05). Please add the %.

Response: Thank you for this request. We have now included the percentage of participants engaging in physical activity by frequency. Please see this included in Table 1, in line with another reviewer’s suggestion to summarise all demographic information in a single table.

Comment 6: Add inclusion and exclusion criteria for the participants, instead of ‘‘A total of 440 responses were recorded, of which 323 were retained in the final dataset after excluding those who failed attention check questions, missing responses for entire scales, are pregnant or not residing in Australia.”

Response: Thank you for raising this. We have clarified the eligibility criteria for this study. Please see this change highlighted in the revised manuscript and included below.

Line 130-134: Respondents were eligible to participate if they were aged between 18-30 years, residing in Australia and not pregnant. A total of 440 responses were recorded, of which 323 were retained in the final dataset after excluding those who failed attention check questions, missing responses for entire scales or did not meet the eligibility criteria.

Comment 7: Line 143-145: “Participants then completed questions determining their eligibility. Those who did 143 not meet the eligibility criteria (i.e., those not aged between 18-30 years, were pregnant or 144 did not reside in Australia) were removed from the survey and thanked for their time. Participants who met all eligibility requirements.” Please remove.

Response: Thank you for this suggestion. We have removed the repetitive information outlining the eligibility criteria in the procedure section. Only the relevant information to clarify the study procedure was included. Please see this change highlighted in the revised manuscript and included below.

Line 147-151: Participants then completed questions determining their eligibility. Those who did not meet the eligibility criteria were automatically removed from the survey and thanked for their time. The remaining participants completed measures assessing their demographics, snacking intentions, enjoyment of food, satiety responsiveness, stress, physical activity engagement and unhealthy snacking behaviours.

Comment 8: Line 149: their contact details for reimbursement. What specific contact details were collected? And if participants did not agree to provide them, were they still included in the study?

Response: Thank you for this query. Participants were asked to provide their email address to be reimbursed. If participants did not agree to provide them, their responses were still included in the study. Please see this clarification highlighted in the revised manuscript and included below.

Line 151-157: At the end of the study, participants were thanked for their time and asked to provide their email address so they could receive a reward ... Data from participants who did not provide their email address for reimbursement were still included in the final analyses.

Comment 9: Line 200: Modified Swiss Food Panel Food Frequency Questionnaire [46]. The questionnaire is validated in English? Please explain.

Response: Thank you for your feedback and for noting the strengths of our methodology. Although, we would like to apologise for an error in the original text and clarify that the behaviour measure was not a modified version of the Swiss Food Panel Food Frequency Questionnaire. Instead, the items were developed for this study and informed by the Swiss Food Panel Food Frequency Questionnaire and the Australian dietary guidelines. This clarification has been incorporated to accurately describe the origin and development of the measure. Although items were developed for this study, the process followed best-practice guidelines for dietary behaviour measurement by following established questionnaires and dietary guidelines. Previous studies have also developed study-specific snack consumption items to ensure relevance to the population (e.g., see [1, 2, 3]). Please see this change highlighted in the revised manuscript and included below.

References:

1.Dorina, I., et al., Utility of temporal self-regulation theory in health and social behaviours: A meta-analysis. British Journal of Health Psychology, 2023. 28(2): p. 397-438.

2.Evans, R., P. Norman, and T.L. Webb, Using Temporal Self-Regulation Theory to understand healthy and unhealthy eating intentions and behaviour. Appetite, 2017. 116: p. 357-364.

3.Gardner, B., et al., Towards parsimony in habit measurement: Testing the convergent and predictive validity of an automaticity subscale of the Self-Report Habit Index. International Journal of Behavioral Nutrition and Physical Activity, 2012. 9(1): p. 102.

Line 206-219: Unhealthy snack consumption was assessed by three items. Participants were provided a definition of unhealthy snacks and examples of foods that would be considered as sweet snacks, savoury snacks, and sugar-sweetened beverages. They were then in-structed, “Please indicate how often you consume the following snacks on average using the scales provided.” Consumption of the three unhealthy snack types were assessed by one item each, “Sweet snacks (e.g., biscuits, cakes, lollies, chocolate bars, pastries, ice-cream)”, “Salty or savoury snacks (e.g., pies, pastries, biscuits, crisps/chips, processed meats)”, and “Sugar-sweetened beverages (e.g., soft drinks, mixers for alcohol, sugar-added juices, energy drinks, hot chocolate, iced tea, cordial, fruit drinks)”. Items were responded to on a 7-point Likert scale (1 = a couple of times per year, 7 = twice or more times per day). Items were developed based on an established food frequency questionnaire [51] and the Australian Dietary Guidelines [52] to best reflect foods commonly consumed by the Australian population. Higher scores indicate greater consumption of the three unhealthy snack types.

Comment 10: Discuss the results also in light of the hypotheses formulated: whether they were confirmed, refuted, or partially supported, etc.

Response: Thank you for this feedback. We have integrated statements clarifying whether each hypothesis was supported in the Discussion. Please see the changes highlighted in the revised manuscript and included below.

Line 277-287: Findings do not support Hypothesis 1 as intention was not a significant factor of any snack type and did not account for unique variance beyond physical activity engagement. But findings provide partial support for Hypothesis 2. Specifically, physical activity engagement and stress were significant factors sweet snack consumption, with stress accounting for unique variance, over and above physical activity engagement and intention. However, physical activity engagement was the only significant factor of savoury snack consumption and no other factors could account for unique variance beyond physical activity engagement. For sugar-sweetened beverage consumption, physical activity engagement and satiety responsiveness were significant factors, with satiety responsiveness accounting for unique variance, over and above physical activity engagement and intention.

Comment 11: “The aim of this study was to identify the factors of unhealthy snack consumption 401 among young adults (18 to 30 years) across the three main snack types: sweet snacks, savoury snacks and sugar-sweetened beverages. We examined the role of physical activity engagement as a control variable, and assessed the influence of intention, appetitive traits (satiety responsiveness and enjoyment of food) and stress to explain unhealthy snack consumption and bridge the intention-behaviour gap.” The paragraph is repetitive, please remove.

Response: Thank you for this recommendation. We have removed this text to improve the readability of the manuscript. In this section, practical implications were also integrated, following the recommendations in Comment 12. Please see the changes highlighted in the revised manuscript and included below.

Line 413-424: Differences in the importance of psychological factors across unhealthy snack types were found and should be considered in tailored health behaviour change interventions to reduce the consumption of various snack types. Physical activity engagement and stress were significant factors of sweet snack consumption. Physical activity engagement was the only significant factor of savoury snack consumption. Physical activity engagement and satiety responsiveness were significant factors of sugar-sweetened beverage consumption. Findings indicate the psychological factors that could bridge the intention-behaviour gap in unhealthy snacking by considering both intentional and non-intentional processes of behaviour. Rational dietary decision making can be interrupted by less conscious cognitive or physiological processes. Therefore, health practitioners and health promotion campaigns may consider the involvement of psychologists to mitigate the influence of less conscious psychological factors to encourage healthy eating patterns.

Comment 12: To be added to the conclusions: the practical implications of the obtained results, such as the involvement of psychologists alongside medical professionals in health education, the promotion of a healthy diet, lifestyle, and so on.

Response: Thank you for this feedback. We have integrated the practical implications in the Conclusion as outlined above in Comment 11. The changes are also highlighted in the revised manuscript.

Comment 13: The title should mention that the study was conducted during the COVID-19 lockdown. In the discussion section, it should be emphasized that during the pandemic, other factors — especially psychological ones — may have also interfered or influenced the results.

Response: Thank you for this recommendation. However, we would like to apologise for an error in the original text and clarify that most participants (62.2%) were not experiencing any COVID-19 restrictions at the time of data collection. Only among the subset of those who were experiencing restrictions, most (74.6%) were under a full COVID-19 lockdown period. Therefore, we believe it would not be accurate to reference the study as having been conducted during the COVID-19 lockdown in the title. Nevertheless, we acknowledge that psychological changes during the pandemic may influence the responses of those who were experiencing COVID-19 restrictions. Please see the correction to this data reflected in Table 1 and limitations acknowledged as highlighted in the revised manuscript and included below.

Line 396-404: Additionally, it should be noted that data was collected during COVID-19, where some participants indicated that they were experiencing COVID-19 restrictions. For these individuals, it is possible that they may have experienced changes in unhealthy food and drink consumption [77], psychological states [78] and physical activity [79] during the data collection period. Notably, individuals’ decreased psychological wellbeing during COVID-19 [80], may influence the generalisability of results in a non-pandemic context. Nevertheless, the study provides valuable insights into the experiences of young adults in unprecedented global crises, which may be transferable to enhance future public health responses.

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

Dear authors,

All the comments were addressed, thank you and good luck.