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. 2023 Aug 30;70(1):59–69. doi: 10.1177/00207640231194489

Factors associated with mental health service use during the pandemic: Initiation and barriers

Helen-Maria Vasiliadis 1,2,✉, Jessica Spagnolo 1,2, Marie-Josée Fleury 3,4, Jean-Philippe Gouin 5,6, Pasquale Roberge 7,8, Mary Bartram 9,10, Sébastien Grenier 6,11, Grace Shen-Tu 12, Jennifer E Vena 12, JianLi Wang 13
PMCID: PMC10860360  PMID: 37646244

Abstract

Background:

Scarce are the studies focusing on initiation of new mental health service use (MHSU) and distinguishing individuals who have sought services but have been unsuccessful in accessing these.

Aims:

Assessing the factors associated with initiating new MHSU as compared to no MHSU due to self-reported no need, no MHSU due to health system and personal barriers and MHSU using resources already in place.

Methods:

The sample included participants (n = 16,435) in the five established regional cohorts of the Canadian Partnership for Tomorrow’s Health (CanPath) who responded to the CanPath COVID-19 health surveys (May–December 2020 and January–June 2021). Multinomial regression analyses were carried out to study MHSU since the pandemic (March 2020) as a function of predisposing, enabling and need factors. Analyses were carried out in the overall sample and restricted to those with moderate and severe symptoms (MSS) of depression and/or anxiety (n = 2,237).

Results:

In individuals with MSS of depression and/or anxiety, 14.4% reported initiating new MHSU, 22.0% had no MHSU due to barriers and personal reasons and 36.7% had no MHSU due to self-reported no need. Age, living alone, lower income, a decrease in income during the pandemic and health professional status were associated with MHSU. Younger adults were more likely to initiate MHSU during the pandemic than older adults who reported not being comfortable to seek mental health care or self-reported no need. Individuals living alone and with lower income were more likely to report not being able to find an appointment for mental health care.

Conclusions:

Awareness campaigns focusing on older adults that explain the importance of seeking treatment is needed, as well as sensitising health professionals as to the importance of informing and aiding individuals at risk of social isolation and lower socio-economic status as to available mental health resources and facilitating access to care.

Keywords: Barriers, mental health service use, initiating new use of services, depression, anxiety, inequities

Introduction

Global estimates during the COVID-19 pandemic showed an increase in the prevalence of anxiety and depression in comparison to the pre-pandemic era (Canadian Centre on Substance Use and Addiction and the Mental Health Commission of Canada, 2022; Mental Health Research Canada, 2022) and increased psychological distress over the first year of the pandemic (Gouin et al., 2023; Matovic et al., 2023). While mental health service needs increased during the pandemic (Nagata et al., 2022), data suggests that even with a shift to virtual consultations, 19% of individuals with mental health symptoms accessed virtually and 11% accessed in-person mental health treatment services (Canadian Centre on Substance Use and Addiction and the Mental Health Commission of Canada, 2021). Understanding barriers to access mental health services and associated factors is important not only for improving mental health services delivery but also for better preparation of future pandemics.

Studies during the first waves of the pandemic showed that socio-demographic factors and health inequities were associated with decreased mental health service utilisation (Asmundson et al., 2020; Coley & Baum, 2022; Miconi et al., 2020; Moyser, 2020; Public Health Agency of Canada, 2022). An overview of barriers to mental health care in Canada prior to the pandemic showed that the most important barriers were related to long wait times, not knowing where to get help and financial reasons such as the cost of services and issues of affordability (Moroz et al., 2020). With telehealth replacing in-person mental health consultations and giving access not otherwise possible during the lockdown, it does not seem that virtual care fully replaced in-person access or was able to keep pace with increasing needs during the pandemic; and this, despite the Canadian government giving hundreds of millions of dollars to virtual mental health supports and services (Smith, 2020). Among Canadians using mental health services prior to the pandemic, close to 59% reported still having mental health supports during the first wave of pandemic, while 41% did not (Mental Health Research Canada, 2020). Reports during the early phase as compared to prior to the pandemic showed that 4% versus 22% of Canadians consulted a mental health professional in person, 3% versus 4% consulted via online video, and 3% versus 5% consulted by telephone (Mental Health Research Canada, 2020). Barriers to patient uptake of virtual mental health care included technological, language, privacy and socio-economic barriers (Palmer et al., 2022; Siegel e al., 2021; Simon et al., 2022).

An important research gap in the literature is that mental health service use (MHSU) is usually assessed as use versus no use, ignoring individuals who have sought services but have been unsuccessful in accessing services. A better understanding of the personal, financial and health system barriers to MHSU during the pandemic is needed to better elucidate inequities in mental health care access given the health service changes that may persist post-pandemic. In a large Canadian sample of community living adults and older adults, the aim of the current study was to examine, according to Andersen’s model (Andersen, 1995) of health care use, the predisposing (e.g. socio-demographic), enabling (e.g. employment, economic) and need (e.g. health status) factors associated with MHSU up until the third wave of the pandemic in Canada. Assessing the factors associated with MHSU and barriers to MHSU (i.e. not receiving care) will help better characterise population subgroups with unmet mental health care needs, and in turn guide public health policies that aim to strengthen equitable access to mental health services.

Methods

Survey data

This study relied on data from adults participating in the five established regional cohorts of the Canadian Partnership for Tomorrow’s Health (CanPath) (formerly Canadian Partnership for Tomorrow Project, CPTP), British Columbia Generations Project (BCGP), Alberta’s Tomorrow Project (ATP), Ontario Health Study (OHS), Quebec’s CARTaGENE (CaG) and Atlantic Partnership for Tomorrow’s Health (Atlantic PATH). Recruitment and study design of CanPath has been detailed previously (Canadian Partnership for Tomorrow’s Health, 2020b; Dummer et al., 2018). The present sample consists of close to 20,000 CanPath participants who were recruited to collect antibodies to SARS-CoV-2 and also includes populations that were at higher risk of exposure to the virus including individuals living in urban and rural under-served communities and long-term care homes (CanPath) (Canadian Partnership for Tomorrow’s Health, 2020a). Data from a health and lifestyle questionnaire administered prior to the COVID-19 pandemic (in 2018) was used along with data collected from health questionnaires during the first and second as well as third wave of the pandemic (May to December 2020 and January to June 2021). Copies of the questionnaires are available via CanPath (www.canpath.ca). Only participants with complete data on the variables of interest for all three timepoints were included (n = 16,435). The study was approved by the institutional research ethics board of the CISSS Montérégie-Centre (#2021-563). Written informed consent was obtained from all participants included in the study.

Measures

The dependent variable of interest (MHSU) was based on self-reports assessed during the 2021 health survey by asking respondents whether they had accessed mental health services since March 2020, with responses categorised into six mutually exclusive groups: no, did not need it; no, was not comfortable seeking services; no, was not able to get appointment (i.e. regular mental health professional was not accepting appointments or could not find mental health professional who was accepting new clients); no, could not afford or lost health benefits; yes, using mental health services the individual already had in place; yes, individual started using new mental health services.

Predisposing factors considered were age, categorised into groups (35–44 years, 45–54 years, 55–64 years and ⩾65 years), sex (male, female) and race/ethnicity categorised by whether the respondent identified as Caucasian (White) (yes/no). Health behaviours included current smoking (yes/no), past-year cannabis use (yes/no) and past-year average weekly alcohol consumption (almost daily [6–7 times/week], less than daily [⩽5 times/week], never). Finally, the cohort the participant was recruited into (BCGP, ATP, OHS, CaG, Atlantic PATH) was also included.

Enabling factors included total household income before taxes (prior to the pandemic); self-reported decrease in income during the pandemic (yes/no); whether respondents worked as a medical professional (e.g. physician, nurse, hospital employee, first responder, pharmacist, with exposure to patients, yes/no); or an essential service provider (e.g. grocery store attendant, public transit, police, security with regular exposure to members of the public (yes/no). Respondents were asked about delays in seeing a healthcare professional for a new health problem (yes/no).

Need factors included presence of moderate or severe symptoms (MSS) of anxiety and depression, the presence of a chronic physical condition and having had COVID-19. The 7-item Generalized Anxiety Disorder scale (GAD-7, score range 0–21) was used in all surveys and a cut-off ⩾10 was used to identify the presence of MSS of anxiety (Spitzer, Kroenke, Williams, & Löwe, 2006). The 8-item Patient Health Questionnaire Depression Scale (PHQ-8, score range 0–24) was used to assess a positive screen of depression and a cut-off ⩾10 was used to identify the presence of MSS of depression (Kroenke et al., 2009). The presence of MSS of depression and/or anxiety was defined as a positive screen for anxiety and depression at either 2020 or 2021 survey. The presence of a chronic physical condition was based on self-reported lifetime physician diagnosis of cancer, diabetes, heart and circulatory conditions, cardiovascular disorder, respiratory system conditions, gastrointestinal diseases, liver or pancreatic conditions, renal disease, kidney conditions, neurological conditions, bone and joint conditions, and immune system conditions. Self-reported suspicion of ever having had COVID-19 was also assessed and categorised as ‘yes, no, don’t know’.

Analyses

Descriptive statistics and group comparisons were based on chi-square statistics. Multinomial regression analyses were carried out to assess study factors associated with MHSU in the overall sample (n = 16,435) as well as in the sample restricted to participants reporting MSS of depression and/or anxiety during the pandemic (i.e. positive screen in either 2020 or 2021) (n = 2,237). Adjusted odds ratios (OR) and 95% confidence intervals (CI) were computed to determine the strength of associations. Analyses were carried out using SAS version 9.4 (SAS Institute, 2013).

Results

Study sample characteristics are presented in Table 1. In the overall sample, 13.2% of participants reported MHSU and 6.3% reported no MHSU due to barriers and personal reasons and 80.4% reported no MHSU due to self-reported no need. When looking at individuals reporting MSS of depression and/or anxiety, 14.4% initiated new MHSU, 26.9% used mental health services they had already in place, 22.0% had no MHSU due to barriers and personal reasons and 36.7% had no MHSU due to self-reported no need.

Table 1.

Study sample characteristics according to mental health service use (MHSU).

Overall N = 16,435 Mental health service use (n = 16,435) p value
No MHSU, no need N = 13,220 (80.4%) No MHSU for various reasons N = 1,035 (6.3%) MHSU – using resources already in place N = 1,501 (9.1%) MHSU – initiating new services N = 679 (4.1%)
Predisposing factors
 Age group <.0001
  ⩽44 years 533 (3.2%) 283 (53.1%) 67 (12.6%) 103 (19.3%) 80 (15.0%)
  45–54 years 2,428 (14.8%) 1,605 (66.1%) 255 (10.5%) 364 (15.0%) 204 (8.4%)
  55–64 years 4,947 (30.1%) 3,849 (77.8%) 350 (7.1%) 517 (10.4%) 231 (4.7%)
  ⩾65 years 8,527 (51.9%) 7,483 (87.8%) 363 (4.2%) 517 (6.1%) 164 (1.9%)
 Sex <.0001
  Male 5,786 (35.2%) 5,033 (87.0%) 297 (5.1%) 302 (5.2%) 154 (2.7%)
  Female 10,649 (64.8%) 8,187 (76.9%) 738 (6.9%) 1,199 (11.3%) 525 (4.9%)
 Race/ethnicity (visible minority) .88
  Caucasian 15,255 (92.8%) 12,284 (80.5%) 953 (6.3%) 1,390 (9.1%) 628 (4.1%)
  Non-Caucasian 1,180 (7.2%) 936 (79.3%) 82 (7.0%) 111 (9.4%) 51 (4.3%)
 Lives alone <.0001
  Yes 2,612 (15.9%) 1,957 (74.9%) 219 (8.4%) 322 (12.3%) 114 (4.4%)
  No 13,823 (84.1%) 11,263 (81.5%) 816 (5.9%) 1,179 (8.5%) 565 (4.1%)
 Current smoking .0001
  Yes 606 (3.7%) 449 (74.1%) 55 (9.1%) 84 (13.8%) 18 (3.0%)
  No 15,829 (96.3%) 12,771 (80.7%) 980 (6.2%) 1,417 (8.9%) 661 (4.2%)
 Past-year cannabis use <.0001
  Yes 1,410 (8.6%) 938 (66.5%) 152 (10.8%) 212 (15.0%) 108 (7.7%)
  No 15,025 (91.4%) 12,282 (81.7%) 883 (5.9%) 1,289 (8.6%) 571 (3.8%)
 Past year average weekly alcohol consumption <.0001
  Never 2,315 (14.1%) 1,766 (76.3%) 175 (7.5%) 273 (11.8%) 101 (4.4%)
  Less than daily (⩽5 times/week) 11,695 (71.2%) 9,405 (80.4%) 728 (6.2%) 1,051 (9.0%) 511 (4.4%)
  Almost daily (6–7 times a week 2,425 (14.7%) 2,049 (84.5%) 132 (5.4%) 177 (7.3%) 67 (2.8%)
 CanPath regional cohorts <.0001
  British Columbia Generations Project (BCGP) 3,079 (18.7%) 2,451 (79.6%) 186 (6.0%) 297 (9.7%) 145 (4.7%)
  Alberta’s Tomorrow Project (ATP) 954 (5.8%) 776 (81.3%) 67 (7.0%) 72 (7.6%) 39 (4.1%)
  Ontario Health Study (OHS) 6,619 (40.3%) 5,098 (77.0%) 499 (7.5%) 720 (10.9%) 302 (4.6%)
  Quebec’s CARTaGENE (CaG) 2,873 (17.5%) 2,520 (87.7%) 114 (4.0%) 149 (5.2%) 90 (3.1%)
  Atlantic PATH 2,910 (17.7%) 2,375 (81.6%) 169 (5.8%) 263 (9.0%) 103 (3.6%)
Enabling factors
 Total household income in year prior to pandemic <.0001
  < $24,999 514 (3.1%) 373 (72.6%) 51 (9.9%) 65 (12.6%) 25 (4.9%)
  $25,000–$49,999 1,784 (10.9%) 1,434 (80.4%) 141 (7.9%) 156 (8.7%) 53 (3.0%)
  $50,000–$74,999 2,678 (16.3%) 2,192 (81.9%) 159 (5.9%) 233 (8.7%) 94 (3.5%)
  $75,000–$99,999 2,701 (16.4%) 2,175 (80.5%) 174 (6.5%) 224 (8.3%) 128 (4.7%)
  ⩾$100,000 6,296 (38.3%) 5,000 (79.4%) 364 (5.8%) 627 (10.0%) 305 (4.8%)
  Not reported 2,462 (15.0%) 2,046 (83.1%) 146 (5.9%) 196 (8.0%) 74 (3.0%)
 Decrease in income during pandemic <.0001
  Yes 2,756 (16.8%) 1,914 (69.4%) 303 (11.0%) 364 (13.2%) 175 (6.4%)
  No 13,679 (83.2%) 11,306 (82.7%) 732 (5.3%) 1,137 (8.3%) 504 (3.7%)
 Medical or other professional with exposure to patients <.0001
  Yes 1,655 (10.1%) 1,234 (74.6%) 116 (7.0%) 201 (12.1%) 104 (6.3%)
  No 14,780 (89.9%) 11,986 (81.1%) 919 (6.2%) 1,300 (8.8%) 575 (3.9%)
 Essential worker with exposure to public <.0001
  Yes 1,457 (8.9%) 1,086 (74.5%) 124 (8.5%) 163 (11.2%) 84 (5.8%)
  No 14,978 (91.1%) 12,134 (81.0%) 911 (6.1%) 1,338 (8.9%) 595 (4.0%)
 Work change since pandemic
  Yes 5,120 (31.2%) 3,607 (70.4%) 433 (8.5%) 708 (13.8%) 372 (7.3%) <.0001
  No 11,315 (68.8%) 9,613 (85.0%) 602 (5.3%) 793 (7.0%) 307 (2.7%)
 Delay in health care for new health problem <.0001
  Yes 2,278 (13.9%) 1,504 (66.0%) 302 (13.3%) 323 (14.2%) 149 (6.5%)
  No 14,157 (86.1%) 11,716 (82.8%) 733 (5.2%) 1,178 (8.3%) 530 (3.7%)
Need factors
 Presence of MSS of anxiety and/or depression <.0001
  Yes 2,237 (13.6%) 821 (36.7%) 492 (22.0%) 601 (26.9%) 323 (14.4%)
  No 14,198 (86.4%) 12,399 (87.3%) 543 (3.8%) 900 (6.3%) 356 (2.5%)
 The presence of a chronic physical disorder <.0001
  Yes 4,997 (30.4%) 3,860 (77.3%) 333 (6.7%) 516 (10.3%) 288 (5.8%)
  No 11,438 (69.6%) 9,360 (81.8%) 702 (6.2%) 985 (8.6%) 391 (3.4%)
 Suspicion of having had COVID-19 <.0001
  Yes 611 (3.7%) 422 (69.1%) 57 (9.3%) 82 (13.4%) 50 (8.2%)
  No 14,633 (89.0%) 11,920 (81.5%) 863 (5.9%) 1,293 (8.8%) 557 (3.8%)
  Don’t know 1,191 (7.3%) 878 (73.7%) 115 (9.7%) 126 (10.6%) 72 (6.0%)
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Factors associated with MHSU in the overall sample

The multivariate analyses on the association between predisposing, enabling and need factors associated with MHSU in the overall sample are presented in Table 2. The findings show that age, sex, smoking and past-year cannabis use among the predisposing factors; income, reported decrease in income during the pandemic, change in work since the pandemic, being in the health profession, and delay in health care for new health problem among the enabling factors; and the presence of a physical disorder and reporting MSS of depression and/or anxiety among the need factors was associated with MHSU.

Table 2.

Multivariable analyses on the association between need, enabling and predisposing factors associated with mental health service use (MHSU) in overall sample (n = 16,435).

MHSU – using resources already in place vs. initiating new MHSU No MHSU – could not find appointment vs. initiating new MHSU No MHSU – financial barriers vs. initiating new MHSU No MHSU – not comfortable vs. initiating new MHSU No MHSU - no need vs. initiating new MHSU
Predisposing factors Adjusted OR (95% CI) a
 Age group
  ⩽44 years Reference Reference Reference Reference Reference
  45–54 years 1.512 (1.068–2.140) 1.308 (0.685–2.498) 1.954 (0.810–4.711) 1.706 (1.110–2.622) 2.174 (1.581–2.988)
  55–64 years 1.860 (1.313–2.633) 0.910 (0.474–1.750) 1.828 (0.756–4.420) 2.140 (1.397–3.280) 3.679 (2.679–5.054)
  ⩾65 years 2.496 (1.703–3.660) 1.154 (0.579–2.299) 2.148 (0.849–5.437) 2.802 (1.768–4.440) 8.055 (5.689–11.405)
  Sex (female vs. Male) 1.273 (1.013–1.599) 0.658 (0.448–0.967) 0.713 (0.447–1.139) 0.759 (0.591–0.976) 0.712 (0.584–0.868)
 Race/ethnicity: Caucasian vs. non-Caucasian 0.994 (0.695–1.420) 0.751 (0.418–1.349) 0.938 (0.436–2.015) 1.007 (0.667–1.522) 0.871 (0.633–1.199)
  Lives alone (yes vs. no) 1.155 (0.893–1.493) 1.250 (0.814–1.920) 1.081 (0.622–1.881) 1.099 (0.819–1.474) 0.832 (0.657–1.053)
  Current smoking (yes vs. no) 2.336 (1.377–3.962) 1.045 (0.435–2.510) 1.301 (0.460–3.677) 2.206 (1.239–3.927) 2.061 (1.242–3.419)
  Past-year cannabis use (yes vs. no) 0.909 (0.699–1.182) 1.100 (0.702–1.724) 0.934 (0.530–1.648) 0.772 (0.568–1.050) 0.578 (0.454–0.737)
 Past year average weekly alcohol consumption
  Never Reference Reference Reference Reference Reference
  Less than daily (⩽5 times/week) 0.781 (0.603–1.012) 0.871 (0.551–1.375) 0.871 (0.507–1.496) 0.901 (0.668–1.216) 0.948 (0.748–1.203)
  Almost daily (6–7 times a week 0.918 (0.632–1.334) 1.506 (0.801–2.832) 0.657 (0.277–1.555) 1.125 (0.738–1.714) 1.176 (0.837–1.652)
Enabling factors
 Total household income in year prior to pandemic
  < $24,999 0.955 (0.574–1.592) 4.967 (2.308–10.689) 2.054 (0.834–5.057) 0.857 (0.468–1.571) 0.847 (0.530–1.354)
  $25,000–$49,999 1.089 (0.754–1.574) 6.972 (3.921–12.399) 1.837 (0.909–3.713) 1.222 (0.806–1.854) 1.140 (0.816–1.592)
  $50,000–$74,999 0.991 (0.740–1.327) 2.783 (1.605–4.827) 0.940 (0.475–1.857) 1.065 (0.761–1.491) 0.953 (0.733–1.239)
  $75,000–$99,999 0.757 (0.581–0.987) 1.532 (0.873–2.691) 0.950 (0.519–1.742) 0.987 (0.730–1.334) 0.778 (0.617–0.982)
  ⩾ $100,000 Reference Reference Reference Reference Reference
  Not reported 1.048 (0.768–1.429) 2.306 (1.263–4.210) 0.930 (0.447–1.935) 1.345 (0.951–1.903) 1.123 (0.850–1.483)
 Decrease in income during pandemic (yes vs. no) 1.026 (0.824–1.279) 2.511 (1.733–3.639) 1.085 (0.666–1.768) 1.169 (0.910–1.503) 0.817 (0.670–0.998)
 Medical or other professional with exposure to patients (yes vs. no) 0.928 (0.712–1.209) 0.584 (0.325–1.049) 0.372 (0.157–0.880) 0.949 (0.696–1.294) 0.869 (0.685–1.102)
 Essential worker with exposure to public (yes vs. no) 0.960 (0.721–1.280) 0.805 (0.466–1.389) 0.824 (0.418–1.623) 1.143 (0.827–1.580) 0.940 (0.727–1.215)
 Work change since pandemic (yes vs. no) 0.913 (0.740–1.125) 0.666 (0.455–0.974) 0.629 (0.392–1.007) 0.684 (0.538–0.870) 0.559 (0.464–0.673)
 Delay in health care for new health problem (yes vs. no) 1.026 (0.817–1.287) 1.480 (1.000–2.192) 1.616 (1.021–2.556) 1.577 (1.229–2.024) 0.778 (0.632–0.958)
Need factors
 Presence of MSS of anxiety or depression (yes vs. no) 0.761 (0.628–0.921) 0.818 (0.575–1.164) 1.123 (0.735–1.716) 1.095 (0.879–1.364) 0.107 (0.089–0.128)
 The presence of a chronic physical disorder (yes vs. no) 0.687 (0.554–0.852) 0.425 (0.278–0.650) 0.612 (0.377–0.992) 0.502 (0.389–0.648) 0.382 (0.314–0.464)
 Suspicion of having had COVID-19
  Yes 0.820 (0.565–1.190) 1.208 (0.645–2.264) 1.279 (0.599–2.733) 0.652 (0.410–1.035) 0.763 (0.545–1.070)
  No Reference Reference Reference Reference Reference
  Don’t know 0.815 (0.596–1.114) 0.966 (0.549–1.699) 1.669 (0.936–2.976) 1.054 (0.744–1.493) 0.878 (0.665–1.160)
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a

Adjusted for all study variables and regional cohort.

The multivariate analyses on the association between predisposing, enabling and need factors associated with MHSU in the sample restricted to participants reporting the presence of MSS of depression and/or anxiety during the pandemic (n = 2,237) are presented in Table 3.

Table 3.

Multivariable analyses on the association between need, enabling and predisposing factors associated with mental health service use (MHSU) in individuals with moderate or severe symptoms (MSS) of depression and/or anxiety (n = 2,237).

MHSU – using resources already in place vs. initiating new MHSU No MHSU – could not find appointment vs. initiating new MHSU No MHSU – financial barriers vs. initiating new MHSU No MHSU – not comfortable vs. initiating new MHSU No MHSU – no need vs. initiating new MHSU
Predisposing factors Adjusted OR (95% CI) a
 Age group
  ⩽44 years Reference Reference Reference Reference Reference
  45–54 years 1.689 (1.034–2.757) 1.644 (0.655–4.124) 2.026 (0.616–6.668) 1.901 (1.036–3.488) 2.802 (1.621–4.842)
  55–64 years 2.186 (1.330–3.592) 1.315 (0.518–3.336) 1.732 (0.516–5.808) 2.589 (1.411–4.751) 4.421 (2.556–7.648)
  ⩾65 years 3.084 (1.762–5.398) 1.101 (0.387–3.131) 2.786 (0.790–9.828) 3.983 (2.053–7.729) 10.222 (5.619–18.593)
 Sex (female vs. male) 1.263 (0.877–1.820) 0.778 (0.422–1.435) 0.598 (0.305–1.172) 0.751 (0.509–1.107) 0.903 (0.637–1.279)
 Race/ethnicity: Caucasian vs. non-Caucasian 1.045 (0.601–1.817) 0.890 (0.352–2.253) 0.993 (0.317–3.114) 1.111 (0.582–2.122) 0.696 (0.410–1.183)
 Lives alone (yes vs. no) 1.117 (0.759–1.642) 2.122 (1.105–4.076) 0.781 (0.344–1.775) 1.312 (0.855–2.014) 0.888 (0.604–1.305)
 Current smoking (yes vs. no) 2.176 (1.112–4.257) 1.024 (0.333–3.149) 1.015 (0.265–3.897) 2.278 (1.098–4.726) 1.999 (1.015–3.937)
 Past-year cannabis use (yes vs. no) 1.015 (0.705–1.460) 1.257 (0.669–2.360) 0.960 (0.450–2.047) 0.694 (0.451–1.067) 0.547 (0.372–0.804)
 Past year average weekly alcohol consumption
  Never Reference Reference Reference Reference Reference
 Less than daily (⩽5 times/week) 0.837 (0.586–1.197) 0.849 (0.441–1.633) 0.721 (0.358–1.452) 1.074 (0.708–1.630) 1.346 (0.934–1.941)
  Almost daily (Six to seven times a week 1.118 (0.646–1.933) 1.612 (0.636–4.084) 1.068 (0.376–3.030) 1.809 (0.995–3.288) 1.660 (0.964–2.858)
Enabling factors
 Total household income in year prior to pandemic
  <$24,999 1.024 (0.512–2.046) 2.168 (0.713–6.597) 2.738 (0.828–9.054) 0.607 (0.260–1.417) 0.907 (0.452–1.820)
  $25,000–$49,999 1.008 (0.589–1.723) 3.708 (1.610–8.537) 2.630 (0.999–6.922) 1.020 (0.560–1.858) 1.350 (0.805–2.264)
  $50,000–$74,999 0.772 (0.500–1.191) 1.557 (0.704–3.445) 1.215 (0.485–3.045) 0.824 (0.505–1.344) 0.805 (0.527–1.229)
  $75,000–$99,999 0.865 (0.582–1.285) 0.917 (0.389–2.161) 0.943 (0.377–2.362) 1.046 (0.671–1.630) 0.713 (0.478–1.063)
  ⩾$100,000 Reference Reference Reference Reference Reference
  Not reported 0.928 (0.572–1.505) 1.248 (0.492–3.163) 1.016 (0.337–3.064) 1.191 (0.706–2.010) 1.044 (0.656–1.661)
 Decrease in income during pandemic (yes vs. no) 1.025 (0.745–1.411) 3.104 (1.798–5.360) 0.944 (0.469–1.900) 1.102 (0.767–1.582) 0.740 (0.535–1.023)
 Medical or other professional with exposure to patients (yes vs. no) 1.101 (0.733–1.655) 0.785 (0.352–1.750) 0.490 (0.144–1.673) 1.213 (0.764–1.924) 1.016 (0.672–1.536)
 Essential worker with exposure to public (yes vs. no) 1.163 (0.745–1.814) 0.869 (0.374–2.018) 1.707 (0.723–4.030) 1.595 (0.987–2.577) 1.288 (0.830–2.000)
 Work change since pandemic (yes vs. no) 0.872 (0.636–1.196) 0.660 (0.378–1.152) 0.711 (0.359–1.407) 0.580 (0.407–0.827) 0.661 (0.484–0.904)
 Delay in health care for new health problem (yes vs. no) 1.011 (0.740–1.381) 1.347 (0.773–2.348) 1.156 (0.610–2.193) 1.414 (1.003–1.993) 0.986 (0.723–1.345)
Need factors
 The presence of a chronic physical disorder (yes vs. no) 0.665 (0.486–0.911) 0.446 (0.241–0.826) 0.656 (0.338–1.275) 0.341 (0.235–0.496) 0.272 (0.197–0.377)
 Suspicion of having had COVID-19
  Yes 0.820 (0.491–1.368) 0.800 (0.321–1.996) 0.420 (0.095–1.858) 0.885 (0.492–1.591) 0.920 (0.553–1.529)
  No Reference Reference Reference Reference Reference
  Don’t know 0.865 (0.553–1.352) 0.864 (0.372–2.004) 1.222 (0.521–2.867) 1.045 (0.634–1.722) 1.028 (0.663–1.593)
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a

Adjusted for all study variables and regional cohort.

No MHSU due to self-reported no need as compared to initiating new MHSU

Among the predisposing factors studied, smokers were twice more likely and participants in the ⩾65-year, 55- to 64-year, and 45- to 54-year age groups were between 3 and 10 times more likely, as compared to those in the ⩽44-year age group, to report no MHSU due to self-reported no need than initiating new MHSU. Past-year cannabis users were less likely to report no MHSU due to self-reported no need than initiating new MHSU. Among the enabling factors studied, those who reported change in work status were less likely to report no MHSU due to self-reported no need. Among the need factors studied, individuals reporting no MHSU due to self-reported no need than initiating new MHSU, were close to four times less likely to report a physical chronic condition.

No MHSU for reason not comfortable seeking mental health support as compared to initiating new MHSU

Among the predisposing factors studied, smokers were twice more likely and participants in the ⩾65-year, 55- to 64-year and 45- to 54-year age groups were between two four times more likely, as compared to those in the ⩽44-year age group, to report no MHSU due to not being comfortable seeking mental health support than initiating new MHSU. Among the enabling factors studied, those who reported change in work status were less likely whereas those reporting a delay in health care for a new health problem were more likely to report no MHSU due to not being comfortable seeking mental health support than initiating new MHSU. Among the need factors studied, individuals reporting no MHSU due to not being comfortable seeking mental health support than initiating new MHSU, were close to three times less likely to report a physical chronic condition.

No MHSU due to financial barriers as compared to initiating new MHSU

Among participants with MSS of depression or anxiety during the pandemic, none of the predisposing, enabling and need factors studied were significantly associated with MHSU.

No MHSU due to health system barriers as compared to initiating new MHSU

Among the predisposing factors studied participants living alone were twice more likely to report no MHSU due to health system barriers such as not being able to find an appointment than initiating new MHSU. Among the enabling factors, participants reporting a decrease in income from prior to the pandemic were three times more likely and those reporting income between $25,000 and $49,999 were close to four times more likely, as compared to the ⩾ $100,000 income category, to report no MHSU due to not being able to find an appointment than initiating new MHSU. Among the need factors studied, those reporting the presence of chronic physical disorders were twice less likely to report not being able to find an appointment.

MHSU of resources individuals already had in place as compared to initiating new MHSU

Among the predisposing factors studied, smokers were twice more likely and participants in the ⩾65-year, 55- to 64-year and 45- to 54-year age groups were between two and three times more likely, as compared to those in the ⩽44-year age group, to report MHSU of resources already in place than initiating new MHSU. Among the need factors studied, individuals reporting a physical chronic condition were less likely to report MHSU of resources already in place than initiating new MHSU.

Discussion

The current study examined the predisposing, enabling and need factors associated with initiating new MHSU during the first eighteen months of the COVID-19 pandemic in a large Canadian sample of adults. This study extends past literature by identifying correlates of initiating new MHSU as compared to MHSU of resources already in place and the absence of MHSU due to health system, financial and personal barriers, and the self-reported absence of need. Among the factors studied, there were differences in predisposing, enabling and need factors associated with MHSU.

Since the beginning of the pandemic (March 2020), 13.2% of the current study sample reported MHSU, similar to the 12% reported in a Canadian general population poll carried out one year following the start of the pandemic (Canadian Centre on Substance Use and Addiction and the Mental Health Commission of Canada, 2021). Further, when looking at the reasons for not accessing mental health services in the current study, 17.2% could not afford it or had lost health benefits due to being laid off or reduced working hours and 10.6% could not get an appointment. Among the individuals reporting no MHSU despite perceiving a need during the pandemic, 72.2% reported personal reasons such as not comfortable seeking help. This is similar to a Canadian survey late in 2020 showing that 78.5% of Canadians reporting personal reasons as a barrier to mental health care (Statistics Canada, 2021).

In the context of important health service disruptions, shifting from in-person to virtual mental health care, and increased demand and limited access to mental health treatment during the pandemic (Asmundson et al., 2020; Canadian Institute for Health Information, 2022b; Duden et al., 2022; Mental Health Research Canada, 2020), few population studies have focused on the factors associated with initiating MHSU. A Danish study conducted prior to the pandemic showed that primary care patients having screened positive for depression and initiating mental healthcare within the year were more likely females and to report more severe impairment in mental health, while education, occupation and income differences were not observed (Geyti et al., 2020). A Veterans Health Administration study in the USA showed that individuals initiating psychotherapy or antidepressant treatment within 3 months of a positive screen for depression were more likely to be females, to report anxiety or post-traumatic stress disorder, to be married, and to be younger than 44 years as compared to older age groups (Cornwell et al., 2021).

Our findings, in individuals with MSS of depression and/or anxiety add to the present literature by observing that adults living alone, experienced a reduction in income from prior to during the pandemic or had lower income, were more likely to report no MHSU due to health system barriers (i.e. not being able to get an appointment with health professional) as compared to initiating new MHSU. Physical distancing measures and fear of infection leading to changes in work status and social isolation during the pandemic may have increased the perceived need for mental health care in individuals living alone (Spagnolo et al., 2022). Barriers to accessing healthcare among individuals with mental health problems have been previously reported across many countries including Canada (Corscadden et al., 2018). An earlier Canadian population-based study similarly showed that 22% of adults with either depression or an anxiety disorder reported barriers in accessing mental health care (Wang, 2006). The most common barriers reported among individuals perceiving a need but not seeking services include structural barriers such as financial barriers and lack of availability of mental health services (Andrade et al., 2014; Wang, 2006).

In the current study 4.6% of the overall sample and 15.9% of individuals with MSS of depression and/or anxiety reported no MHSU due to not being comfortable to seek mental health care. As compared to initiating new MHSU, these individuals were more likely in older age groups than the younger age group (⩽44 years), smoke and report delay in healthcare for a new health problem. Further, 1.1% in the overall sample and 2.5% of individuals with MSS of depression and/or anxiety reported no MHSU due to financial barriers.

The current study findings also showed that among individuals reporting MSS of depression and/or anxiety during the pandemic, adults aged 44 years and younger as compared to all other older age groups, also reporting cannabis use and a physical chronic condition, and change in work status were more likely to initiate MHSU than report no MHSU due to no need. These findings may reflect increased perceived mental health burden in these individuals. Contrary to earlier studies (Cornwell et al., 2021; Geyti et al., 2020), we did not find sex differences in initiating MHSU in individuals with MSS of depression and/or anxiety. This may in part be due to the fact that the majority (80%) of participants reporting MSS of depression and/or anxiety were female.

The strength of the current study includes available data on socio-demographic, economic, lifestyle factors and symptoms of depression and anxiety from prior to during the pandemic, minimising the risk of information and recall bias, in a large Canadian sample recruited in CanPath’s longitudinal regional cohorts, spanning a number of provinces. Another strength of the current study was that we were able to study in more detail the factors associated with MHSU and specifically be able to distinguish between initiating new MHSU and using resources individual already had in place, as well as distinguishing no MHSU due to no need from no MHSU due to barriers or personal reasons (not being comfortable). A limitation of the current study was that we were not able to distinguish the type of health professionals consulted or sought for services (i.e. family physician or general practitioner, psychiatrist, mental health professional such as psychologist, psychotherapist/counsellor) or whether this was in the public or private sector. Furthermore, the present study did not assess whether the reported MHSU was for in person or virtual mental health care, which may have further clarified whether this modality is a facilitator or barrier of MHSU for different subgroups of the population. Finallly, participants of the regional cohorts were more likely women, white, reported higher level education, and were retired and therefore results may not be generalisable to the general Canadian population. Participants however were similar in their reporting of chronic physical conditions to the Canadian general population (Dummer et al., 2018).

In conclusion, the findings of the present study showed that younger adults were more likely to initiate MHSU via new services during the pandemic than older adults. The decreased odds of initiating new MHSU during the pandemic by older adults may reflect the increased difficulty in finding new mental health resources for older adults or that virtual mental health consultations offered during the pandemic may have seen a limited uptake in older age groups. Further, older adults were up to ten times more likely to report no MHSU due to not feeling the need and not being comfortable to seek care. This finding underscores the importance of informing older adults about the various treatments available for anxiety and depression. Awareness campaigns focusing on older adults underlying the importance of seeking treatment for their anxiety and depression and to explain the process of available effective treatments such as psychotherapy may help in improving acceptability. With a better understanding of the different treatments available, they might be more willing and comfortable to seek help for their mental health problem. Future studies should also aim towards better documenting the use of virtual mental health care and associated perceived barriers in older adults (Harerimana et al., 2019). Furthermore, health system barriers such as not being able to find an appointment were present in individuals living alone and with lower socio-economic status and this in individuals reporting MSS of depression and/or anxiety. Social isolation and lower socio-economic status have been associated with difficulties in navigating the health care system suggesting the importance of informing at risk individuals as to the different available health services in their area and aiding in scheduling appointments if necessary, and ensuring continuity of care and communication between professionals to support patient care (Canadian Institute for Health Information, 2022a). Health policies should go further in improving access to mental health care at the individual level by improving structural and organisational barriers such as removing any financial or insurance reimbursement barriers to mental health service use. General practitioners and health professionals in proximity to the community should also identify individuals with anxiety and depression living alone which may be more at risk of unmet mental health service needs. Future research should focus on better describing the factors associated with the type of mental health professionals consulted in both the public and private health sectors.

Acknowledgments

The data used in this research were made available by CanPath – Canadian Partnership for Tomorrow’s Health (formerly the Canadian Partnership for Tomorrow Project) including 5 regional cohorts of the British Columbia Generations Project, Alberta’s Tomorrow Project, Ontario Health Study, CARTaGENE, and Atlantic Partnership for Tomorrow’s Health – and the COVID-19 Immunity Task Force and Public Health Agency of Canada. CanPath is supported by the Canadian Partnership Against Cancer and Health Canada, BC Cancer, Genome Quebec, Centre Hospitalier Universitaire (CHU) Sainte-Justine, Dalhousie University, Ontario Institute for Cancer Research, Alberta Health, Alberta Cancer Foundation, and Alberta Health Services. The views expressed herein represent the views of the authors and not of CanPath, the regional cohorts or its funders. The authors would like to thank Nolwenn Noisel for her collaboration in obtaining funding for the study and Catherine Lamoureux-Lamarche, MSc, PhD, for preparing the manuscript for submission.

Footnotes

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

Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The current project was funded by a Canadian Institutes of Health Research (CIHR) grant (#02211-000). The funder had no role in the study design, data collection, analysis and interpretation, draft and revision of the paper nor in the decision to submit for publication. J. Spagnolo is currently funded by a CIHR Fellowship (2022-2025) and previously received funding from a FRQ-S Postdoctoral Training Fellowship (2020-2022). S. Grenier is funded by a FRQ-S Senior salary award.

ORCID iD: Helen-Maria Vasiliadis Inline graphic https://orcid.org/0000-0003-0186-6060

Data availability: Data from CanPath participants are available through a data access process. More information can be obtained via https://canpath.ca/.

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