Are smartphone use and nature contact predictive of depression in a UK university population?

Ethan Dewar (School of Psychology, University of Birmingham Edgbaston Campus, Birmingham, UK.)
Jonathan Catling (School of Psychology, University of Birmingham Edgbaston Campus, Birmingham, UK.)

The Journal of Mental Health Training, Education and Practice

ISSN: 1755-6228

Article publication date: 2 April 2024

Issue publication date: 15 April 2024

70

Abstract

Purpose

The number of university students exhibiting mental health concerns have surged considerably in the past decade. Amongst a number of potential contributing factors, this study aims to assess the role of a broader societal phenomenon; the shift in emphasis in our interactions from the physical to the virtual environments. Specifically, a decrease in nature contact and a contrasting increase in smartphone use are identified as two pathways in which this shift may impact negatively on mental health. Previous research evidences both facets as consistent correlates of depression, although limited research extends these associations to the student population or attempts to establish an interaction between the two.

Design/methodology/approach

The current study recruited a sample of 380 first-year undergraduate students, via an online survey, to assess if problematic smartphone use (SAS-SV) and nature contact (NCQ) were significant predictors of depression (PHQ-9).

Findings

Nature contact frequency and smartphone use were significant predictors of depression.

Originality/value

This is the first study to concurrently assess the impact of smartphone use and nature contact in a student population.

Keywords

Citation

Dewar, E. and Catling, J. (2024), "Are smartphone use and nature contact predictive of depression in a UK university population?", The Journal of Mental Health Training, Education and Practice, Vol. 19 No. 2, pp. 74-85. https://doi.org/10.1108/JMHTEP-10-2022-0081

Publisher

:

Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited


Introduction

The number of students at UK universities disclosing a mental health condition to their higher education institution grew by 492% in the span of a decade from 2007 to 2017 (9,675 to 57,305), despite student populations remaining relatively stable (2,362,815 to 2,317,880; Universities UK, 2018). This increase can be attributed, in part, to a shift in the UK’s collective conscience during this period, towards an improved understanding and acceptance of mental health issues. Ultimately this has helped to reduce previously widespread stigmas (Henderson et al., 2020) and encouraged help seeking behaviours (Eisenberg et al., 2009). Nonetheless, it is critical that we do not overstate this effect and risk overlooking the very real deterioration in student mental health, tragically evidenced by the substantial increases in suicides observed over a similar period to an all-time high of 182 in 2019 (ONS, 2020). Despite an acceleration in university investment in mental health services in recent years to keep pace with the surging demand (Thorley, 2017), a freedom for information request revealed lengthy waiting times for access to services averaging 7.5 weeks (Richardson, 2019).

As well as the personal, social and academic challenges typically faced by university students, a number of novel factors have emerged that may be driving the unprecedented decline in student mental health. One consideration is that groups at heightened risk of developing mental illnesses are increasing across higher education as access to universities broadens and students more accurately represent the socio-demographic ranges found within the UK (Reiss, 2013; Klepac Pogrmilovic et al., 2021; Knifton, 2012). Furthermore, students entering higher education in recent times face an ever-increasing pressure to achieve a high degree classification (Brown, 2016) resulting from a competitive, oversaturated graduate job market (Thorley and Cook, 2017) and record-high levels of student debt (Student Loans Company, 2020). With the background of these changes in the student experience, the current study proposes a critical role of a broader societal shift that has accelerated since the turn of the millennium concerning the way in which we interact with each other and the world more generally. This is a move from the physical to the virtual environment, specifically, an increasing reliance on technology and a decreasing amount of interaction with the natural world.

Exponential technological developments in the 21st century have facilitated large advancements in the utility of personal computing devices that, in conjunction with increasing affordability, have led to rapid rises in popularity. This is particularly emphasised in young adults (16–24), where smartphone ownership has risen from 29% in 2008 to 96% in 2021 (Statista, 2021). Facilitated by gains in popularity and utility, smartphones have increasingly integrated entertainment, communication and work-related features, inevitably increasing the users time occupied by them (BOND, 2019). It has also had the consequence of a pervasive increase in individuals exhibiting problematic smartphone usage (Olson et al., 2022). Although the relationship between humans and smartphones remains in its infancy, research has shown concerning impacts on mental health outcomes, particularly regarding more problematic smartphone usage. Problematic smartphone use (PSU) has been defined as “an inability to regulate one’s use of the mobile phone, which eventually involves negative consequences in daily life (e.g. financial problems)” (Billieux, 2012).

Liu et al. (2016) have established a dose–response relationship between smartphone screen time and depression risk amongst young adults, in a broad meta-analysis study. However, subsequent reviews have failed to replicate this straightforward association, emphasising that any relationship between screen time and depression is primarily dependent upon type of use (Tang et al., 2021). This is likely to be linked to the varied ways in which individuals interact with these versatile devices and their equally heterogenous impacts. The current research will therefore focus specifically on PSU, which has been shown to exhibit stronger and more consistent associations with depressive symptoms (Elhai et al., 2017). Demirci et al., (2015) offer preliminary evidence of this association holding within university populations, although findings have not been reproduced outside of this study.

There are a range of pathways theorised to link PSU to worsened mental health outcomes. In accordance with the wider addiction literature, the temporary absence of smartphone engagement amongst compulsive users is posited to result in dopamine deficiency states (Sharma et al., 2021); specifically, it is suggested that PSU could have a neurophysiological basis that shares common mechanisms with other known conventional drug addictions, through neurotransmitter mechanisms (e.g. the serotonergic and mesolimbic dopamine systems). Another potential pathway is through a lack of adequate sleep, demonstrated to commonly precede depression (Alvaro et al., 2013; Zhang et al., 2022). Sleep may be disturbed due to an inhibition of melatonin production caused by viewing screens close to sleeping hours (Cain and Gradisar, 2010) as well as auditory and visual disturbances of notifications, with the majority of young adults sleeping within close proximity of their smartphones (Lemola et al., 2015).

In contrast to the recent emergence of interactions with personal technology, our species-old relationship with nature appears to be inextricably tied to our human nature. In the late 20th century, The Biophilia Hypothesis postulated the inherent tendency for humans to seek connections with the natural world resulting from our primal evolutionary past, evidenced by ubiquitous “biophilic tendencies” Ulrich (1993). This contrasts trends across the developed world recording the ever-increasing movement of humans indoors (Evans and McCoy, 1998), and brought about the new scientific enquiry into the effect of natural environments on health outcomes. Additionally, there is evidence to suggest that young people are specifically spending less time outdoors compared to previous generations (Hand et al., 2018; Soga and Gaston, 2016). Moreover, the declining visitation rates to national parks in multiple countries during the past two decades (Rigolon, 2017) is representative of a more general downward trend in nature-based recreation that has been observed (e.g. Larson et al., 2019). Among the many possible reasons for this, some argue that the rise of electronic media, especially the advent of the smartphone, can partially explain these trends, specifically the substitution of time spent outdoors with time spent indoors in front of screens (Eyler et al., 2021; Louv, 2005; Pergams and Zaradic, 2006).

It is well established that experiences with nature are beneficial across a multitude of physical health domains (e.g. Gascon et al., 2018; Seresinhe et al., 2015; Yao et al., 2021), with a growing body of literature demonstrating similar psychological effects. Furthermore, preliminary meta-analysis findings revealed that mood disorders were significantly less common within rural populations compared to their socio-demographically matched, urban residing counterparts (Peen et al., 2010). This was subsequently corroborated by White et al. (2013), who detailed significantly lower mental distress and higher general well-being amongst urban populations inhabiting neighbourhoods containing greater expanses of vegetation. Critically, this association was not observed independently but rather alongside individuals spending a greater amount of time in these organically rich environments. More contemporary research has attempted to quantify more specific associations between various nature-doses and depression, yielding observations that even relatively low nature exposure results in significantly fewer instances of depression, with further incremental benefits as contact increases (Shanahan et al., 2016; Cox et al., 2017). Despite this breadth of literature, no prior research has attempted to quantify the link between nature contact and depressive outcomes in the relatively high-risk population of students.

The prevailing mechanistic pathway underlying the association between nature experiences and mental health outcomes is outlined in the stress reduction theory (SRT; Ulrich, 1983). SRT posits landscapes containing natural features such as vegetation, water and wildlife moderate mental states of arousal, a mechanism originally evolved to attract humans to “savannah-like” expanses most advantageous for survival. Scenery containing natural features elicits heightened activation of the parasympathetic nervous system (Ulrich et al., 1991), the facet of the autonomic nervous system responsible for regulating “stressed” states through opposing psycho-physiological pathways (Hartig et al., 2003).

The current research aims to consolidate the evidential links between nature contact and PSU on mental health outcomes within a UK university population. The current study also aims to extend the field, assessing whether the observed shift from physical to virtual environments, measured by both nature contact and smartphone usage, can predict depression within a student population. In line with the weight of the current evidence, we predict that both nature contact and PSU will be significant predictors of depression.

Method

Participants

In total, 527 first-year psychology students from the University of Birmingham were recruited via a research participation scheme for which they received credits for completing the questionnaire. Data was collected over a period of three months from November 2021 to January 2022. In accordance with the exclusion criteria (participants must be from the first year of the programme), 147 participants were omitted from the final sample; ineligible year of study (N = 90) and incomplete questionnaire items (N = 57). The final sample for data analysis therefore consisted of 380 first-year students, ranging in age from 17 to 51 years (M = 18.70, SD = 2.21).

Materials

Patient health questionnaire (PHQ-9).

The patient health questionnaire (PHQ-9) (Kroenke et al., 2001) is a nine-item questionnaire assessing symptoms of depression. Participants are asked “Over the past 2 weeks, how often have you been bothered by any of the following problems?” Participants then score statements, such as “Feeling down, depressed, or hopeless” or “Poor appetite or overeating” on a four-point scale ranging from 0 – “Not at all” to 3 – “Nearly every day”, resulting in a possible score of 27. Higher scores indicate more depressive symptoms. It has been validated in clinical settings (Gilbody et al., 2007) and the general population (Martin et al., 2006).

Smartphone addiction scale – short version (SAS-SV).

The smartphone addiction scale – short version (SAS-SV) (Kwon et al., 2013) is a ten-item assessment measures the levels of SA in students. Participants rate statements on a six-point Likert scale, from “strongly disagree” (1) to “strongly agree” (6). An example item is: “Won’t be able to stand not having a smartphone”. The total score ranges from 0 to 60, with a higher number indicating stronger smartphone addiction (SA). For assessing SA, the SAS-SV has excellent internal consistency. The scale has excellent validity and reliability, with an r = 0.814 on the test-retest reliability and a Cronbach’s alpha coefficient of 0.947 (Demirci et al., 2014).

Nature contact questionnaire (NCQ).

The nature contact questionnaire (NCQ) (Shanahan et al., 2015) is a two-item self-report of nature contact adapted from a standardised nature contact measure (Holland et al., 2021). Natural environments were defined at the start of the questionnaire block as “as any contact with vegetation or non-human animals in settings ranging from personal gardens to larger urban parks to relatively pristine wilderness” (Holland et al., 2021). The first item probes participants about how regularly they usually visit and/or pass-through natural environments for any reason on a nine-point scale between “Never” and “6–7 days a week”. The second item asks participants to recall the average duration of each contact with natural environments within the past week on an eight-point scale between “No contact” and “4 or more hours”. A succinct and recent time frame was used to improve the accuracy of participant recall (Schwarz and Oyserman, 2001).

Procedure

Data was gathered through an online survey using Qualtrics.com. Participants were compensated credit towards their research participation requirements for the semester.

Ethical considerations

Prior to commencement, the current study was authorised by the University of Birmingham’s ethics committee. Participation through the Research Participation Scheme is voluntary. All participants were informed about the nature of the study and their right to withdraw at any point. Written consent was provided by all participants prior to questionnaire completion.

Results

The final sample was comprised of predominantly female participants (N = 320; 84.2%), reflecting gender disparities in undergraduate psychology students. Male participants made up a further 13.4% (N = 51) of the sample, with non-binary individuals (N = 3) and those who elected not to state a gender (N = 6) making up the final 2.4% (see Figures 1 and 2).

Bivariate correlations with the criterion variable were undertaken using Spearman’s correlation analysis (this was chosen due to all variables being shown to be significantly different from the normal distribution – tested through a Kolmogorov–Smirnoff test for normality; see Table 1 for descriptive statistics of all variables). This analysis (see Table 2) revealed a significant positive relationship between depression and smartphone use (r = 0.249, N = 380, p < 0.01). A significant negative relationship was found between depression and nature contact duration (r = −0.126, N = 380, p < 0.05); furthermore, a significant negative relationship was observed between depression and nature contact frequency (r = –0.104, N = 380, p < 0.05) as a sole measure. Bivariate correlations were then examined between independent variables to test the suitability of factors for a multiple regression analysis. No relationship was observed between smartphone use and nature contact duration (r = –0.076, N = 380, p = 0.140) or frequency of nature contact visits (r = 0.028, N = 380, p = 0.585). Inevitably, nature contact duration and frequency of nature contact showed a very significant positive correlation (r = 0.214, N = 380, p < 0.001). Two separate multiple linear regressions were therefore conducted to avoid any multicollinearity between these two variables within the regression models.

The first multiple linear regression model predicted depression based on smartphone use and total nature contact from which a significant regression model emerged: F (2,377) = 11.912, p < 0.001. The model explains 5.4% of the variance in depression amongst first-year university students (adjusted R-squared = 0.054). Collinearity for the predictor variables tolerance was above 0.9. Within the model, smartphone use was a significant predictor of depression (β = 0.227, p < 0.001), whilst total nature contact was a non-significant predictor (β = –0.083, p = 0.097).

The second multiple linear regression model predicted depression based on smartphone use and frequency of nature visits as a sole measure of nature contact. This yielded another significant regression model: F (2, 377) = 13.439, p < 0.001, which explained 6.2% of the variance in depression (adjusted R-squared = 0.062). Collinearity for the predictor variables tolerance was above 0.9. Within this model, both smartphone use (β = 0.233, p < 0.001) and nature contact frequency (β = –0.118, p < 0.05) were found to be significant predictors of depression.

Discussion

The current study was the first to explicitly investigate the association between nature contact and depression within a population of university students. Our analysis presented an inverse relationship between the regularity of nature exposure and levels of depression, supporting the widely cited psychologically beneficial qualities of frequent contact with natural environments (e.g. Shanahan et al., 2016; Cox et al., 2017). However, the absence of similar reductions in depression alongside extended periods in natural environments implies a proclivity towards short, frequent nature experiences as opposed to more lengthy, infrequent contacts. This proposition is somewhat substantiated by Cox et al. (2017), who observed both stronger and more significant negative associations with depression when the nature contact proxy used frequency as opposed to duration.

This emphasis on the frequency of nature exposure in preference to the duration theoretically aligns with the notion of SRT (Ulrich, 1983) in the context of our sample population. University students in the 2020s encounter a near continuous activation of stress-heightening conditions comprising unprecedented academic pressures (Brown, 2016) as well as novel global concerns such as eco-anxiety (Kelly, 2017) and the recent Covid-19 pandemic (Catling et al., 2022; Savage et al., 2020). The ongoing and encompassing nature of these stressors could lead to a somewhat unremitting activation of the sympathetic, “fight or flight” branch of the autonomic nervous system, which left unbalanced has been demonstrated to lead to depressive outcomes (Veith et al., 1994). It therefore follows that regular exposures to natural environments could moderate states of arousal through opposing psycho-physiological pathways (Hartig et al., 2003), and hence could reduce depressive symptom severity.

The current study also examined the reliability of preliminary findings that observed an association between PSU and depression within a university population (e.g. Catling and Sutton, 2023; Elhai et al., 2020). Our analysis demonstrated a positive relationship between the level of smartphone use and depression severity, substantiating the widely cited observation within the literature of a link between PSU and heightened depression risk (e.g. Yang et al., 2020). Within the context of a pervasive increase in individuals presenting PSU (Sohn et al., 2019) and the occurrence of PSU amongst students reported as high as 50% (Fatima et al., 2021), this finding is one of particular concern.

In regards to the proposed mechanistic pathways that underlie this association, the current study provides limited support for both dopamine deficiency states (Ulrich, 1993; Evans and McCoy, 1998) and lack of adequate sleep as two feasible pathways in which PSU may link to depressive outcomes, though no direct measures were taken to corroborate either explanation. These findings imply that the reduction in regular contact with nature and an increase in PSU, resulting from a general shift in contact from the physical to virtual environments, are significantly contributing to the decline of mental health within student populations. Although predictions only account for 6.2% of depression severity variance, the aggregation of effects across a university-wide population are likely to exert a significant effect on mental health outcomes. Mechanistically, this interaction may be facilitated by these variables’ differential impact on levels of rumination (Bratman et al., 2015) as a common mechanism relating risk factors to depression (Spasojević and Alloy, 2001).

Limitations

One possible limitation of the nature contact facet of the current study concerns the questionnaire used (NCQ). As previously mentioned, there is currently no standardised measure of nature contact (Holland et al., 2021), with the current study relying upon self-reported estimations of contact based on the most widely cited definition of nature. However, this definition could encompass a broad range of subjective phenomena, which could negatively impact on the reliability of results, potentially contributing to the lack of an association between nature contact duration and depression. A more reliable direct measure of nature contact in the absence of a standardised questionnaire would be the use of global positioning systems (GPS) tracking (Merry and Bettinger, 2019) from which participants time spent within areas above a predetermined threshold of vegetative cover (NDVI) could be calculated. While this may improve reliability, this method also has considerable limitations such as selection bias among other considerations outlined in Holland et al. (2021).

Within the smartphone use element of the present report, the demographics of the sample population present a limitation that confines the generalisability of results. Of the final sample of participants, only 13.4% of the sample were male, reflecting gender disparities in individuals studying psychology at undergraduate level. In consideration of numerous observations suggesting the differential depression risk associated with smartphone use between genders (Nishida et al., 2019; Twenge and Martin, 2020), conclusions should be drawn cautiously. Prior studies indicate that PSU carries an increased depression risk in females in comparison to males, suggesting the impact of potential differential predominant uses between genders. The sample of males in the current report was too limited to conduct an independent statistical analysis with suitable statistical power to examine potential gender differences within the current report.

Implications

We suggest that the results from the current study should inform preventative methods across a number of domains, centred around supporting individuals in developing proactive behaviours to support their own well-being, eliciting adaptive techniques and a beneficial sense of control (Mirowsky and Ross, 1990). Primarily, universities should explicitly emphasise the importance of frequent nature contact as a proactive method for supporting mental well-being, particularly amongst first-year student populations most susceptible to developing depression following the potentially stressful transition to university (Kendler et al., 1999). A consideration of these results should also advise universities’ campus planning decisions, ensuring that natural features are commonplace in proximity to academic and accommodation sites to maximise accessibility. (Neuvonen et al., 2007). Furthermore, university-wide workshops could be offered to educate students about the largely underestimated detrimental effects of PSU and techniques to tackle/prevent this widespread habit (Billieux, 2012; Liu et al., 2016). Lastly, the indication that a shift from physical to virtual environments is detrimental to student mental health should inform university decisions concerning the medium of future teaching, following the temporary shift to online teaching during the Covid-19 pandemic.

Future research

Future research should aim to more comprehensively understand the quality of natural features required to maximise restorative benefits, following suggestions that biodiversity may well account for a considerable proportion of these effects.

Declarations

Ethics approval and consent to participate: Ethics approval was sought for this study from the University of Birmingham Ethics committee – Review ERN_20-1093.

Ethical permission was obtained from the University of Birmingham’s Ethics committee. Participants consented to participate and were informed of their right to withdraw data from analysis prior to a given date. Student ID numbers were used, maintaining confidentiality. A variety of mental health service resources were highlighted should participants have any concerns relating to the content of the questionnaires.

All experimental protocols were approved by the University of Birmingham’s Ethics Committee.

All methods were carried out in accordance with relevant guidelines and regulations.

Informed written consent was obtained from all participants.

Availability of data and materials: All data generated or analysed during this study are available on request.

Competing interests: The authors declare there were no financial or non-financial competing interests.

Funding: There was no funding associated with this research.

Authors’ contributions: Ethan Dewar (ED); Jonathan Catling (JC). ED and JC were responsible for the conception and design of the study; ED collected all data; ED undertook the statistical analysis and interpretation of the data; ED and JC contributed equally to the drafting of the paper; JC was responsible for the redrafting of the paper; ED and JC approved the submitted version. ED and JC have agreed both to be personally accountable for their own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature.

Figures

Participants by gender

Figure 1

Participants by gender

Participants by age

Figure 2

Participants by age

Descriptive statistics

  Mean SD
Depression 10.6 6.1
Smartphone use 32.9 8.7
Nature contact (frequency) 6.2 2.1
Nature contact (duration) 3.2 1.5

Source: Author’s own work

Correlation analysis

  Depression Smartphone use Nature contact (frequency) Nature contact (duration)
Depression
Smartphone use 0.249**
Nature contact (frequency) –0.104 0.028
Nature contact (duration) –0.126 –0.076 0.214**  
Notes:
*

Significant at p < 0.05;

**

significant at p < 0.001

Source: Author’s own work

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Corresponding author

Jonathan Catling can be contacted at: j.c.catling@bham.ac.uk

About the authors

Ethan Dewar is based at the School of Psychology, University of Birmingham Edgbaston Campus, Birmingham, UK.

Jonathan Catling is based at the School of Psychology, University of Birmingham Edgbaston Campus, Birmingham, UK.

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