Are perceived barriers to accessing mental healthcare associated with socioeconomic position among individuals with symptoms of depression? Questionnaire-results from the Lolland-Falster Health Study, a rural Danish population study

Abstract

Objective

To evaluate if perceived barriers to accessing mental healthcare (MHC) among individuals with symptoms of depression are associated with their socio-economic position (SEP).

Design

Cross-sectional questionnaire-based population survey from the Lolland-Falster Health Study (LOFUS) 2016–17 of 5076 participants.

Participants

The study included 372 individuals, with positive scores for depression according to the Major Depression Inventory (MDI), participating in LOFUS.

Interventions

A set of five questions on perceived barriers to accessing professional care for mental health problem was posed to individuals with symptoms of depression (MDI score >20).

Outcomes

The association between SEP (as measured by educational attainment, employment status and financial strain) and five different types of barriers to accessing MHC were analysed in separate multivariable logistic regression models adjusted for gender and age.

Results

A total of 314 out of 372 (84%) completed the survey questions and reported experiencing barriers to MHC access. Worry about expenses related to seeking or continuing MHC was a considerable barrier for 30% of the individuals responding and, as such, the greatest problem among the five types of barriers. 22% perceived Stigma as a barrier to accessing MHC, but there was no association between perceived Stigma and SEP. Transportation was not only the barrier of least concern for individuals in general but also the issue with the greatest and most consistent socio-economic disparity (OR 2.99, 95% CI 1.19 to 7.52) for the lowest vs highest educational groups and, likewise, concerning Expenses (OR 2.77, 95% CI 1.34 to 5.76) for the same groups.

Conclusion

Issues associated with Expenses and Transport were more frequently perceived as barriers to accessing MHC for people in low SEP compared with people in high SEP. Stigma showed no association with SEP.

Informed written consent was obtained. Region Zealand’s Ethical Committee on Health Research (SJ-421) and the Danish Data Protection Agency (REG-24–2015) approved the study.

Strengths and limitations of this study.

• A strength of this study is that it is a population study in a socio-economically-deprived area.

• It combines data on present depression scores and socio-economic position (SEP) with proportions of perceived barriers to accessing mental healthcare (MHC) services.

• The study was done with patient participation.

• A limitation of this study is that the questions used to assess barriers to accessing MHC are not standardised.

• There was a potential overlap in the questions between transportation barriers and expense barriers related to seeking or continuing MHC services.

Introduction

Major depressive disorders (MDD) rank third among leading causes of years lived with disability in high-income countries as MDD is common and has an early onset.¹ Mental health problems in early age can have a profound impact on educational achievements,² on income³ and on later unemployment.⁴ Additionally, a diagnosis of depression is associated with a substantially shorter life expectancy.⁵

In spite of this, not all people suffering from depression are treated. In a Norwegian survey study, only 12% of respondents with symptoms of depression had ever sought help,⁶ and a Canadian study found that 40% with symptoms of depression or anxiety perceived an unmet need for care.⁷ Generally, treatment of patients suffering from depression is insufficient even in high-income countries, as only one in five receives adequate treatment.⁸

Depressive disorders are closely associated with socio-economic position (SEP). A dose–response relationship has been found between income, as well as education, and incidence, prevalence and persistence of depression.⁹ Likewise, studies have found that negative socio-economic changes increase the risk of incidence of mental disorders, particularly mood disorders,¹⁰ and financial strain in itself is associated with depressive disorder.^{11 12}

Thus, people in low SEP may have a higher need for mental healthcare (MHC) due to increased incidence and prevalence of depression. A recent study found predictors of need for highly-specialised MDD care to be depression severity, younger age at onset, prior poor treatment response, psychiatric comorbidity, somatic comorbidity, childhood trauma, psychosocial impairment, older age and a socio-economically disadvantaged status.¹³ Although people in low SEP have an increased need for MHC, it is not evident that they use more specialised care. Some studies have found access to specialist care to be based on clinical need with little inequity in SEP,^14–16 whereas others report disparity in specialised MHC as psychologists or psychiatrists are not provided equally to persons in low SEP according to need^{7 17–19} or that higher SEP is associated with more usage of specialised MHC.^{20 21}

The background for initiating the present study was that healthcare statistics (unpublished) in 2013 revealed a significant disparity, as 20% fewer individuals in the most socio-economically deprived municipality in Denmark (Lolland) had been in contact with outpatient MHC (psychologist, private or public psychiatry) than was expected for the population size (unpublished). Several reasons may account for this discrepancy between the expected higher need in a deprived area and the actual use of MHC services, one of them being perceptions of barriers that affect the patients’ choices or preferences, which we aimed to address in this study.

The study objective was to evaluate if perceived barriers to accessing MHC differ across individuals with symptoms of depression according to SEP. We, thereby, expected to gain valuable knowledge for addressing inequality in the use of MHC services.

Method

Study design

The study was conducted as a cross-sectional questionnaire-based population survey.

Setting

The Danish healthcare system is tax-funded and free at delivery for both primary and secondary care; for adults, dental care and psychotherapy are only partly subsidised.²² The general practitioner (GP) fulfils a gatekeeper function, as specialised care is free only after GP referral. Psychotherapy by a psychologist is partly subsidised only for patients referred by a GP for specific conditions: reaction to specific traumatic events, moderate depression and, specifically for citizens between 18 and 38 years, moderate anxiety disorders. In 2014, the out-of-pocket cost to individuals partly subsidised at the time of service was equivalent to 52€ for the first consultation and 44€ for the following sessions.²³

Study population and data sources

The Lolland-Falster Health Study (LOFUS) is a publicly funded population survey conducted in the two remote municipalities of Lolland and Guldborgsund, located in a socio-economically deprived area of Denmark that is a 1½−2-hour drive south from the capital Copenhagen. In the 2017 national ranking of all 98 municipalities, these two were ranked the most deprived and the eighth most deprived municipalities.²⁴ Together, the municipalities comprised 103 000 citizens, 50% being 50 years of age or older²⁵ in 2017. The study aims to enrol 25 000 participants of all ages and is conducted from 2016 to 2020. Participants are randomly selected by civil registration number,²⁶ invited by mail and re-invited by phone. The study covers several health areas: mental health, health literacy, social issues, genetics, kidney, ear nose & throat problems and more. Beyond questionnaire responses, LOFUS data contains blood samples and biometrics. The study is described in detail elsewhere.²⁷ The present study relies on responses to the questionnaire from adults, with data drawn from LOFUS at the end of 2017, while data collection was still ongoing.

The subjects included in this study are respondents with symptoms of depression. All respondents who scored >20 on the Major Depression Inventory (MDI) were posed the specific questions on perceived barriers to seeking help for mental health problems, which are described below.

Independent variables

Major Depression Inventory

As part of the LOFUS questionnaire, the respondents filled out the MDI. The MDI is based on the 12-item Likert Scale and has been found to have an adequate internal and external validity for defining different stages of depression.²⁸ The MDI is based on the ICD-10 diagnostic criteria for depressive disorder,²⁹ with scores ranging from 0 to 50. We used the sum score after excluding the lowest score on question 8 or 9 and, likewise, the lowest score on item 11 or 12, which measured increased/decreased restlessness and increased/decreased appetite, respectively.³⁰ Mild depression is indicated by scores from 21 to 25, moderate depression from 26 to 30 and severe depression by scores from 31 to 50.³¹ If more than two items were missing in the MDI, the score was categorised as missing.³²

Socio-economic position

SEP was measured by employment status, educational attainment and financial strain. Usually income status is included as measure of SEP but information on income was not an item in the questionnaire. Financial strain is not the optimal measurement of SEP; however, it has been found to be associated with depressive and/or anxiety disorder, above the effect of income and to be negatively, but not strongly, correlated with income (r = −0.41, p<0.001).¹¹

Employment status was gathered using 14 different items in the questionnaire. Respondents over the age of 67 were categorised as retired, unless they were employed. The categories of employment were reduced to four in the analyses: Working (employee; self-employed; combined employee and self-employed; military; secondary school pupil; post-secondary student; apprentice; house-wife/husband); Temporary not working (unemployed; rehabilitation; sickness leave 3 months or more); Retired (retired due to age; disability benefit; early retirement); and Other (other).

Educational attainment was measured and classified as follows: No post-secondary education (if the respondent did not complete any post-secondary education); 1–3 years post-secondary education (for vocational or academy/professional graduates of 1–3 years); 3+ post-secondary education (for baccalaureate matriculants who completed 3–4 years); and Academic (for those who completed graduate study of ≥5 years).

The questionnaire gathered responses concerning financial strain with the following question: How often within the last 12 months have you had problems paying your bills? With possible answers: Never; Few months; Approximately half the months in the year; Every month. In the analysis, the categories were reduced to three to gain power, merging Approximately half the months in the year and Every month into one category.

Extrinsic variables

Socio-demographic variables included were gender, age, marital status and cohabitation.

Questions on self-perceived general health (SRH) were provided to respondents with a five-point Likert Scale from Very good to Very bad. In addition, the presence of a Long-standing health problem was posed as a binary question and General activity limitation was gauged in three grades from Severely limited to Not at all. These questions were adopted from the European Health Status Module.³³

The questionnaire included inquiries regarding past and present medical problems; specifically related to mental health status, the respondents were asked if they presently suffered or had ever suffered from anxiety disorder and/or depression.

Dependent variables

We developed a short list of questions to be included in the LOFUS questionnaire for respondents who scored positive for symptoms of depression. The questions were inspired by the Barriers to Access to Care Evaluation questionnaire by Sara Clement et al.³⁴ Their questionnaire contains 30 items, which was too many to include in the LOFUS study (see online supplementary table 1). The number of questions was reduced and grouped to cover the individual abilities in approaching care as described by Levesque et al³⁵: ability to perceive; ability to seek; ability to reach; ability to pay; and ability to engage (see further description in the online supplementary material, figure 1). A preliminary question on whether considering seeking care had ever been a problem was prompted before the five questions related to the abilities/perceived barriers:

Have any of the reasons listed below prevented, delayed or discouraged you from getting or continuing professional care for a mental health problem?

It has had an impact, that I. .

1. … have been unsure what to do to get professional care. (termed Knowledge in the following).

2. … have been concerned for what others might think, say or do. (termed Stigma).

3. … have had difficulty with transport or travelling for treatment. (termed Transport).

4. … have not been able to afford the expenses that followed. (termed Expense).

5. … have had bad experiences with professional care for mental health problems. (termed Experience).

6. These questions are Not Relevant for me/I do not want to answer.

Answers to question 1–5 were listed in four grades ranging from Not at all to A lot; question six was binary.

In a preliminary form, the questions were evaluated for content validity in a focus-group interview of a group of ten patients and relatives of psychiatric patients (the Panel of Relatives and Patients of Psychiatry Services in Region Zealand) in December 2014. The group found the themes relevant and the questions understandable. They offered some suggestions for rephrasing, which were subsequently followed. The same panel commented on the preliminary results of the study in December 2017.

Statistical analysis

For respondents with symptoms of depression, we estimated the association between SEP and the outcome variables (five types of barriers to MHC: Knowledge; Stigma; Transport; Expense; Experience) in separate multivariable logistic regression models after excluding respondents replying Not relevant. Likewise, we performed the same analyses with the three grades of depression (mild, moderate and severe) and depression score uncategorised (MDI score) as independent variables, which are presented as online supplementary material. The SEP categories were Employment status, Education, and Financial strain. Working, Post-secondary education, and No economic distress were used as reference categories.

The logistic regression models were adjusted for age (18–59 vs 60+) and gender, in addition to the variables studied in the univariate (crude) analysis.

The significance level used was 5% throughout, and all reported CIs were 95%. All statistical analyses were done in Stata 15 (Statacrop, V.1, 2017).

Patient and public involvement

The study objectives were discussed with the members of the Panel of Relatives and Patients of Psychiatry Services in Region Zealand along with the validation of the questions in December 2014. The preliminary results were discussed with the group again in December 2017. The final results were distributed to the group in February 2018 along with an invitation for additional comments. One member of the patient panel responded to the invitation and provided additional comments/discussion. Comments from patients are included in the discussion.

The published article will also be distributed to the patient panel.

Results

Sampling from Lolland-Falster Health Study

By 21 December 2017, a total of 20 680 adults (age 18+) had been invited to the LOFUS study. By 31 December 2017, a total of 5395 adults had replied to the questionnaire. A total of 319 respondents did not reply on the MDI score element or failed to fill in more than two answers in the test, leaving 5076, of whom 372 (7.3%) reported symptoms of depression and, thus, were prompted the questions on perceived barriers to seeking MHC. Fifty eight replied that the questions were not relevant or would not answer them; thus 314 individuals with a n MDI score >20 were included in the analyses of SEP and perceived barriers (figure 1).

Figure 1.

Sampling flowchart. MDI, Major Depressive Inventory.

The total sample consisted of 53% women; 64.5% of the respondents were married, and 80.7% were cohabitating. For the total group, the mean age was 55.7 and the median age was 57.4; for individuals scoring in the depressed range on the MDI, the mean age was 50.2 and the median was 51.4 years.

Compared with the total sample, the respondents reporting symptoms of depression were younger, and more likely to be living alone and unmarried (table 1). They were also more likely to have no post-secondary education, to be temporarily out of work (of whom 33% had symptoms), and to experience more frequent financial strain. Furthermore, their health indicators included: lower self-rated health; more reports of limited physical functioning; more reports of long lasting disease; and former anxiety or depression diagnoses; and more reports to be currently in pharmacological treatment for these disorders.

Table 1.

Characteristics of study sample and respondents with symptoms of depression (Major Depressive Inventory (MDI) >20)

	Total sample				MDI score >20
	Men	Women	Total	%	N	%
Age group
18–29	198	212	410	8.1	55	13.4
30–39	180	250	430	8.5	41	9.5
40–49	357	443	800	15.8	82	10.3
50–59	519	681	1200	23.6	84	7.0
60–69	632	666	1298	25.6	63	4.9
70–79	396	371	767	15.1	41	5.3
80+	95	76	171	3.4	6	3.5
Sum	2377	2699	5076		372	7.3
Marital status
Married	1538	1708	3246	64.5	181	5.6
Partnership	73	108	181	3.6	15	8.3
Separated	12	9	21	0.4	5	23.8
Divorced	169	195	364	7.2	31	8.5
Widower	59	164	223	4.4	11	4.9
Not married	509	487	996	19.8	122	12.2
Cohabitating
Yes	1917	2141	4058	80.7	248	6.1
Secondary schooling
Studying	20	34	54	1.1	5	9.3
<8 years	290	203	493	9.7	35	7.1
8–9 years	610	401	1011	19.9	87	8.6
10–11 years	751	913	1664	32.8	112	6.7
High school	522	896	1418	27.9	89	6.3
Other/foreign	163	215	378	7.4	38	10.1
Post-secondary education
No post-secondary	415	529	944	18.6	112	11.9
1–3 years post-secondary	1307	1238	2545	50.1	172	6.8
3+years post-secondary	495	784	1279	25.2	63	4.9
Other	143	122	265	5.2	21	7.9
Occupational status
Work/study	1417	1526	2943	58.0	167	5.7
Temporarily no work	68	121	189	3.7	63	33.3
Retired	843	966	1809	35.6	115	6.4
Other	47	77	124	2.4	27	21.8
Financial strain
Not at all	2136	2404	4540	89.4	275	6.1
Few months	175	213	388	7.6	60	15.5
Half the months	23	22	45	0.9	13	28.9
Every month	25	32	57	1.1	19	33.3
Self-rated health
Very good	306	328	634	12.5	7	1.1
Good	1348	1524	2872	56.6	83	2.9
Fair	616	697	1313	25.9	181	13.8
Bad	89	137	226	4.5	90	39.8
Very bad	12	6	18	0.4	9	50.0
General activity limitation
Not limited at all	1561	1630	3191	63.2	114	3.6
Limited but not severely	672	906	1578	31.3	166	10.5
Severely limited	132	146	278	5.5	88	31.7
Long-standing illness. Yes	1052	1200	2252	44.7	244	10.8
Anxiety, now or earlier. Yes	110	223	333	6.6	111	33.3
Depression, now or earlier. Yes	145	230	375	7.4	138	36.8
Medication anxiety. Yes	71	119	190	3.8	65	34.2
Medication antidepressants. Yes	85	173	258	5.1	66	25.6

Of those responding to the questions, more than half perceived no problems at all in accessing professional care, least of all Transport.

Among those who did have concerns about accessing or continuing professional MHC, Expense was the most common problem, as 30.1% indicated expenses had prevented, deterred or delayed them either Quite a lot or A lot (both responses aggregated in the ‘Quite a lot + category in figure 2). Likewise, the second most common concern was related to Stigma, phrased in the questionnaire as ‘what others might think, say or do’, which was a serious concern for 22.3%; approximately the same proportion (21.2%) had concerns related to Knowledge, or how to find help for MHC. Transport was not a problem for 78.6%, with only 11.7% reporting that it negatively affected access.

Figure 2.

Responses on perceived barriers to accessing mental health care (MHC), proportions.

Perceived barriers to accessing healthcare by SEP are shown in table 2 (crude numbers are shown in online supplementary table 2). Perceptions of Stigma did not show any significant difference across the socio-economic groups, however measured. Lack of Knowledge was a significant problem for respondents without Post-secondary education compared with those who had completed some Post-secondary education (adjusted OR 2.26 95% CI 1.1 to 4.6) and for respondents with occasional (Few months), but not regular, Financial strain when compared with those with no Financial strain. Low SEP, as measured by educational level and Financial strain, was associated with perceived barriers concerning Transport and Expense; whereas low SEP measured by employment status alone was associated with concerns related to Transport. The retired respondents were more likely to perceive bad Experience with MHC services as a barrier to seeking or continuing MHC compared with respondents who were working. Transport showed the greatest disparity across the socio-economic groups.

Table 2.

Adjusted OR for perceived barriers for accessing mental health care (MHC) by three indicators of Socio-economic position (SEP)

	Employment status			Education				Financial strain
	Adjusted OR	95% CI	n		Adjusted OR	95% CI	n		Adjusted OR	95% CI	n
Stigma
Working	1		291	3+ years	1		290	Not at all			289
Temporarily not working	0.9201	0.4880 to 1.735		1–3 years	1.087	0.5740 to 2.058		Few months	0.8994	0.4841 to 1.671
Retired	0.6808	0.3420 to 1.356		No post-secondary	1.166	0.5833 to 2.332		Half the time+	1.749	0.6933 to 4.410
Other	0.3815	0.1431 to 1.017		Other	0.6699	0.1969 to 2.279
Knowledge
Working	1		292	3+ years	1		291	Not at all	1		290
Temporarily not working	1.204	0.6390 to 2.268		1–3 years	1.597	0.8309 to 3.070		Few months	2.515	1.335 to 4.739
Retired	0.5003	0.2480 to 1.009		No post-secondary	2.263	1.115 to 4.592		Half the time+	2.372	0.9404 to 5.985
Other	0.5004	0.1884 to 1.329		Other	4.752	1.297 to 17.412
Expense
Working	1		289	3+ years	1		288	Not at all			289
Temporarily not working	1.700	0.8911 to 3.323		1–3 years	1.835	0.9324 to 3.612		Few months	4.268	2.172 to 8.385
Retired	1.537	0.7451 to 3.171		No post-secondary	2.773	1.336 to 5.757		Half the time+	9.623	2.708 to 34.194
Other	0.7456	0.2822 to 1.970		Other	2.031	0.5762 to 7.156
Experience
Working	1		287	3+ years	1		286	Not at all	1		286
Temporarily not working	0.9581	0.4820 to 1.905		1–3 years	1.043	0.5392 to 2.019		Few months	1.152	0.5999 to 2.212
Retired	2.143	1.024 to 4.485		No post-secondary	0.6435	0.3073 to 1.347		Half the time+	2.385	0.9685 to 5.874
Other	1.531	0.5932 to 3.952		Other	0.7503	0.2024 to 2.781
Transport
Working	1		290	3+ years	1		289	Not at all			288
Temporarily not working	3.184	1.463 to 6.931		1–3 years	1.603	0.6502 to 3.954		Few months	1.746	0.8392 to 3.634
Retired	4.442	1.900 to 10.384		No post-secondary	2.988	1.187 to 7.518		Half the time+	9.889	3.745 to 26.113
Other	2.169	0.6948 to 6.773		Other	1.019	0.1835 to 5.659

Adjusted for: gender; age ±60; 95% CI, significant results are marked in bold.

SEP showed no association with any of the barriers or with years of schooling (not shown). Using depression as an independent variable, we found that severity of depression (both, measured as a categorical variable and a score) was associated with perceived barriers in relation to Expense and Transport, but not associated with any other perceived barriers (see online supplementary material table 3).

Discussion

Principal findings

In this study of perceived barriers to accessing MHC by respondents with present symptoms of depression, we found that almost 1/3 of the respondents indicated that Expense related to accessing MHC was a considerable barrier; this perception was more prevalent among individuals without Post-secondary education and individuals experiencing Financial strain. Transport presented the least prevalent barrier in general; but on the other hand, transportation also presented the greatest and most consistent socio-economic disparity across all measurements of SEP. Transport and Expenses associated with accessing MHC were a problem for disadvantaged individuals.

Stigma was an issue of concern for 22% of the respondents but did not vary significantly according to SEP, whereas Lack of knowledge about how to get help was a significantly greater problem for individuals without Post-secondary education as compared with individuals with Post-secondary education.

Lack of knowledge about how get to help and bad experience were perceived as a problem for 1/5 of the individuals overall as well.

Strengths and weaknesses of the study

A strength of this study was its use of information from a population study from a deprived area in combination with data on present depression score, information on SEP and perceived barriers to accessing MHC; by this design we were able determine the significance of different barriers to access for potential MHC patients in a deprived area. We are not aware of similar studies.

A limitation in our study was that the items used as dependable variables were not fully validated; validation would be preferred in order to compare to other studies. The Barriers to Access to Care Evaluation - version 3 (BACE-3), at 30 questions, was too extensive to use in the LOFUS study, which already consisted of close to 100 questions; this was also the reasoning behind our focus on five central concepts of barriers to access. The external validity of the questions is supported by the use of generally accepted and validated concepts of abilities and as such is comparable to other studies. The content validity was tested by the panel of patients and patients’ relatives and the questions found to be sound, but in retrospect, might not measure the concept of self-efficacy very well. We used the answer Not relevant/Do not want to reply as an indicator that the individual preferred to handle problems without help. It would have been prudent, however, to ask a more direct question about perceptions of need for care; it is possible that some individuals did not find the question relevant because while they experienced mental health issues, they did not perceive a need for further care. We found no correlation between the answer to the question of relevance and SEP, except for retired respondents, who tended to state Not relevant less frequently, compared with respondents Working (not shown).

Another limitation was that the question about transport was not clearly separated from the question about perceived barriers in relation to Expenses, as it was not specified whether Expenses included transportation-related expenses. Thus, we have no clear determination whether Transport as a barrier is primarily a logistical or an economical barrier, or some combination thereof.

Comparison with other studies

The total sample contained more respondents in the age group 50–69 and fewer in the younger and older age groups compared with the study population; additionally, as compared with the background population, the LOFUS sample is over represented by individuals with +3 years post-secondary education vs No post-secondary education by almost 3:1 according to the general population statistics drawn from Statistics Denmark.²⁵ For the total sample, questions on SRH were rated higher in the sample than the national levels³⁶ even though long-lasting illness was more prevalent in the sample (44.7% compared with a national rate of 35.6%)³⁶; the rate of respondents with severely limited physical functioning was close to the national proportions.³⁷ The group with symptoms of depression had scores well below the national levels in all health-related variables. The total sample may over-represent the middle-aged to older part of the population, an issue seen in national surveys too.³⁸

7.3% had symptoms of depression when the summed MDI score was used, which is a considerably higher rate than found by any other survey in Denmark; however, a recent national survey reported that 7.0% adults suffer from depressed mood, including 7.8% in the region of Zealand.³⁶ Eurostat reported a prevalence of 6.3% adults with depressive symptoms and 3% with major depression symptoms in Denmark.³⁹ In the present study, 225 respondents reported both a core symptom of depression Most of the time or more and a summed MDI score >20, equivalent to an MDD prevalence of 4.4%. A comparable study by Ellervik et al found 2.5% with a summed MDI score >25; we found 3.8%.⁴⁰ The present data is a sub-sample from a population survey in a deprived area, which could explain the high rate of depression symptoms found.

We found perceived Stigma to be of Quite a lot or A lot of concern for 20% of the respondents. This corresponds with findings in a systematic review, where overall 20%–25% respondents in 44 studies reported Stigma as a barrier to accessing MHC services.⁴¹ Stigma showed no association to SEP in our data. We have not been able to verify this in other studies except for one Canadian study, which likewise found no association between years of education and experiencing Stigma in MHC. However, they did find perceived Stigma more prevalent among respondents not working.⁴² In the Panel of Relatives and Patients of Psychiatry Services of Region Zealand, it was said that patients with mental disorders, and their relatives, pull the curtains together when they meet with each other privately, and that patients are indeed concerned with what others might think.

One in five respondents experienced Knowledge as a barrier and had doubts about what to do to get professional help. With free access to a GP in Denmark, and the GP universally understood to be the gatekeeper for referrals, this is puzzling. Among respondents with symptoms of depression, 138 reported former or present depression, and 35 of them (25%) still answered that they experienced Knowledge to be a barrier Quite a lot or A lot of the time. Of those with symptoms of depression and presently taking antidepressant medication, 8 (12%) had doubts about what to do to get help. This could be due to the nature of the disease, but we did not find support for this, as we found no association to Knowledge with the severity of symptoms of depression. However, a Canadian study on perceived unmet need by respondents with symptoms of anxiety or depression found high symptom scores were associated with a higher degree of unmet need,⁷ and not knowing how or where to get help was the most reported reason. The Panel of Relatives and Patients of Psychiatry Services of Region Zealand was not very surprised by this finding: despite free access to a GP, one individual reported that he could not get a family GP, but had to meet changing doctors in a regional clinic (due to lack of GPs in the area). Another mentioned that the waiting time for an appointment with a GP could be weeks (due to lack of GPs).

It could be argued that older people may be more reluctant to use MHC and feel more stigmatised by the need for psychotherapy.^{43 44} We did not find support for this as the Retired group did not differ in perception of Stigma from employed persons. Likewise, older retired persons might be less willing to pay for the expenses associated with treatment, but we did not find support for this either, as Expense was not a significant barrier for the Retired group compared with the Working group.

Use of MHC is sensitive to cost,⁴⁵ and especially so for persons in low SEP.⁴⁶ This corresponds with our findings that Expenses associated with MHC were considered a common barrier for seeking help and the concern of almost 1/3 of our respondents, and by two to five-fold more by respondents without Post-secondary education or in Financial strain. This knowledge is important when research has shown that Financial strain is strongly associated with higher odds for depression¹¹ and for prescription of anti-depressants.⁴⁷ A German study found that even with free access to a psychologist, these services are used less by people in low SEP,¹⁹ which could be explained in part by our findings; people without Post-secondary education may have less knowledge of how to access professional MHC, thus leading to lower usage of available services.

Experience with earlier MHC treatment made retired respondents more reluctant to seek MHC as compared with the working population. This may not necessarily be due to bad experiences with healthcare professionals, though stigmatisation can be a problem in health services too⁴⁸; reports of past experience as a barrier could also indicate bad experience with side-effects from a medication. Our study was not designed to capture or explore this nuance. Retired individuals are more likely to have more experience with healthcare, and this group includes people receiving early retirement pensions, which could indicate a chronic illness leading to early retirement and thus more opportunities for more bad experiences. The patient panel questioned the respondents’ experience with MHC, since the rates of bad past experiences were so low, with one remarking: ‘Those who are really feeling bad have not participated in this survey’. For the panel, bad experience was a common deterrent to MHC, which may indicate an important area of future study.

Transport was perceived to be a greater problem by persons in low SEP compared with individuals in high SEP. This aligns well with our previous findings of the impact of distance and SEP on MHC use by patients in antidepressant treatment.²¹ However, the question was not well distinguished from the question on expenses. Difficulty with transport or travelling includes the time spent to reach services and coordinate with other obligations – taking care of family duties or take time off at work etc. Reliance on infrequent or inadequate public transportation could also be a reason for answering positively to this question, but the study was not designed to capture information regarding public vs private transportation; for example, the patient panel was surprised that transport was a minor issue for the respondents, since it was viewed by them to be both time-consuming and expensive.

Meaning of the study and possible explanations and implication for policy-makers

The study aimed to evaluate if perceived barriers to accessing MHC differ across individuals with symptoms of depression according to their SEP. The answer in this study is quite clear: lack of Post-secondary education was linked to greater perceived barriers to MHC and expenses are considered a barrier to MHC for those with No post-secondary education and in Financial strain. Low mental health literacy, defined as knowledge and beliefs about mental disorders which aid in their recognition, management and prevention,⁴⁹ could be a part of the explanation, since low mental health literacy is also associated with low SEP.⁵⁰ Thus, empowering the community to take action for better mental health literacy⁵¹ can lead to increased help-seeking by individuals in low SEP. In Denmark, two programmes on improving mental health literacy exist: Mental Health First Aid⁵² and the ABC mental health initiative,⁵³ both adopted from Australia. An approach directed more specifically toward deprived areas within such programmes might improve SEP equity in MHC treatment.

Addressing barriers and easing access for the deprived is obviously necessary. Lack of Post-secondary education is associated with greater perception of barriers to MHC, in addition to an increased prevalence of mood disorders. Clearly, our results showed that Expense is a barrier for people in low SEP, but as found in the German study,¹⁹ people in low SEP use psychologists less frequently even with free access. Psychotherapy is associated with the ability to engage, which in itself could be more difficult if an individual struggles with social and economic problems on top of mental ones. In order to address these related barriers, the deprived and depressed probably have additional needs beyond medication and psychotherapy, such as social supports and social/domestic/workplace intervention.

In a future study it could be interesting to investigate the association between depression score, perceived barriers and use of MHC for a period after the score. Future research could also investigate which experiences cause retired respondents with symptoms of depression to hesitate to access MHC. Further improvements and validation of a short-form questionnaire as the present could be beneficial.