Challenges to addressing student mental health in embedded counselling services: a survey of UK higher and further education institutions

ABSTRACT

With reports continually demonstrating increased demand and severity of student mental health needs, it is important to gain a fuller understanding of the impact on embedded student counselling services. The aims of this research were to identify (a) service similarities, (b) factors which impact on services, (c) characteristics of service users, and (d) the use of therapeutic technology (e.g. online self-help). An online survey was completed by 113 heads of UK student counselling services across Higher Education (HE), Further Education (FE), and Sixth Form Colleges (SFCs), to capture service data from the academic year 2013/14. Students predominantly received high-intensity support (e.g. counselling) and referrals increased over 3 years. Challenges to embedded counselling services and their implications for development are discussed.

KEYWORDS:

• Student mental health
• embedded counselling services
• further education
• higher education
• data collection
• routine outcome measures

Introduction

In the UK, student mental health within Higher Education Institutions (HEIs) has been at the forefront of the political agenda with recommendations from the Higher Education Policy Institute (HEPI) to collect institutional data on mental health services (see Brown, 2016). Many reports have highlighted the growth of the student population alongside increased demands for student counselling (e.g. Royal College of Psychiatrists Report, 2011; Storrie, Ahern, & Tuckett, 2010). A longitudinal study at one UK HEI found evidence that the psychological distress of students rose on entering university and did not return to pre-university registration levels for the duration of their course (Bewick, Koutsopoulou, Miles, Slaa, & Barkham, 2010). Similarly, a web-based survey across four UK HEIs found approximately one-third of students reported clinical levels of psychological distress (Bewick, Gill, Mulhern, Barkham, & Hill, 2008). However, this concern has also extended to Further Education Institutions and Sixth Form Colleges (Warwick, Maxwell, Statham, Aggleton, & Simon, 2008). In addition, the concern about student mental health has been made at a global level (Rückert, 2015).

In response to this increasing need, counselling services in the UK have been challenged to respond to and demonstrate the effectiveness of the therapeutic support offered (e.g. Randall & Bewick, 2016). Uniquely, support services within such establishments are required to work within a cycle of semesters and vacations that do not apply to the general population, however the latest HEPI report recommends that students have access to these services even when away from campus (Brown, 2016). Related, and contributing to this challenge, is the fact that there is a great deal of variation in the information collected across services, which hampers benchmarking and the identification of areas of development across different sectors.

In terms of services offered, in FE and SFCs the types of support may include individual or group counselling and may extend to classroom interventions involving teachers or parents. In HE services, in addition to one-to-one support, students may also be encouraged to use guided self-help, peer-to-peer support, or online help (Mair, 2016). Moreover, the use of eTherapies (i.e. therapeutic advice provided via the internet or telephone) have become popular in recent years, but it is unclear which types of eTherapy have been adopted by services nor is it clear which types of eTherapy students may benefit from (Sucala et al., 2012). Offering different modes of support is necessary to suit the diverse needs of students. However, it also creates difficulties for comparing outcomes in different service sizes and educational settings. Making comparisons across services is advantageous because it can inform service development, demonstrate effectiveness, and build evidence to support bids for institutional funding (Murray, McKenzie, Murray, & Richelieu, 2015). The latter is particularly important in the current economic climate since the reduction of government funding has led to closures of student counselling services in FE (Caleb, 2014). In HE, new policies to widen participation and raise tuition fees have created new challenges for students and counselling services. For example, student debt has been linked to poorer psychological functioning as well as considerations for dropping out of education (Cooke, Barkham, Audin, Bradley, & Davy, 2004; Walsemann, Gee, & Gentile, 2015). Furthermore, early reports from the widening participation scheme anticipated increased reports of student mental ill-health in response to more students from disadvantaged backgrounds entering HE (See Department for Business Innovation & Skills report, 2013).

The challenges of student counselling services have been documented widely and continue to be a concern (Kreß, Sperth, Hofmann, & Holm-Hadulla, 2015; Prince, 2015). In fact concerns for meeting higher demands in student counselling services were reported as early as 1969 and yet demand continues to be a prominent issue (Goldberg, 1980; Holm-Hadulla & Koutsoukou-Argyraki, 2015). This ongoing growth of students entering FE and HE has shaped embedded counselling services to offer new ways of providing support. One response to managing demand has been limiting counselling to 6 sessions. However, the introduction of very short-term support has raised concerns as to whether effective support can be delivered within these time restraints (Mair, 2016). Despite these concerns, client feedback suggests that counselling services contribute to students’ ability to cope academically (McKenzie, Murray, Murray, & Richelieu, 2015). However, as the severity and complexity of student mental health increase, there are growing numbers of students approaching embedded counselling services that would otherwise seek help from the National Health Service (NHS; Stallman, 2010). Furthermore despite limiting the number of counselling sessions, the growth of student referrals has lengthened waiting times (Mowbray et al., 2006). In the student counselling context, the length of the waiting list is further challenged by students having limited access to support outside of academic term times or during course placements.

In response to the unique challenges of FE and HE, student counselling services have introduced alternative support in addition to traditional face-to-face counselling and the HEPI further recommends that services sign-post alternative support resources; including self-help and mobile apps such as the Expert Self-Care Student mobile app (Brown, 2016). The use of alternative support has coincided with the availability of therapeutic technology that has the potential to reach more individuals in a shorter period of time and without the need to regularly attend the counselling service. These attributes are particularly relevant in FE and HE as students have been known to seek help outside of traditional office hours, particularly during evenings, nights and weekends (Gatti, Brivio, & Calciano, 2016). Offering alternative support that can be maintained at a distance also shows potential to support students on course placements who would otherwise not have access. One of the most recent advancements has been from mobile phone apps supporting mental well-being. However there are concerns about quality and risk assessment (Grundy, Wang, & Bero, 2016).

In light of the increasing pressure on embedded counselling services, the current study aimed to compare service data across service size (e.g. small, medium, and large) and sector (i.e. Further Education, Sixth Form Colleges, and Higher Education) to establish the following: (1) service similarities (e.g. use of staff); (2) factors which impact on counselling services (e.g. attended counselling sessions); (3) factors which characterise students/service users (e.g. uptake of different types of support); and (4) identify the use and interest in offering therapeutic technology as a means to address service and client factors (e.g. online self-help).

Method

Design

An online survey was devised based on questions reported in annual service reports made publicly available by university and college counselling services¹. The survey was also informed by an executive committee representing Heads of University and College Counselling Services (HUCS) from FE and HE. The final scope of questions covered the following areas: (1) service characteristics (e.g. size of client pool, years of service, Full Time Equivalent of paid and volunteer therapeutic staff); (2) factors affecting services (e.g. attended counselling sessions, waiting times, and use of clinical outcome measures and associated problems); (3) characterising service users (e.g. referrals for different types of support, and 3-year demand); and (4) types of alternative support available through the service and the head of services’ interest in offering therapeutic technology (e.g. self-help, peer-to-peer, online communities, and mobile phone apps). To ensure clarity and consistency across survey answers, definitions were provided within the survey (see Appendix 1). Unless stated otherwise, questions referred to the previous academic year (2013/14) and reminders of this time frame were stated within each question.

Survey functionality and distribution

The survey questions were displayed electronically on a powerful online platform (https://qualtrics.com/) that enabled participants to complete the survey across multiple sittings. This functionality required participants’ email addresses and, although answers were confidential, they were not therefore anonymous. To allow services to contribute anonymously, a second web link to the survey was created, but this version could only be completed in one sitting. Heads of student counselling services were contacted through a professional mailing list by the chair of the HE counselling sector on behalf of the researchers. The aim of the initial contact was to collect online consent to be contacted by researchers with a unique link to the survey, and to provide the link to the anonymous survey for services willing to complete the survey in one sitting. During the initial contact, the following information was provided: (1) electronic copies of survey questions; (2) a web link to an online consent form to receive a unique web link; and (3) a web link to the anonymous survey version. To promote data integrity and to enable clearer comparisons of service data, question responses were multiple choice with options to provide additional comments on each page. An exception was one question capturing therapists' difficulties when using clinical outcome measures, which was an open comment box with unlimited entry.

Participants

A total of 113 heads of service completed the survey comprising 72 who provided emails through the online consent form shared on a professional mailing list (see above) and a further 41 who completed the survey anonymously. Whilst the total number of heads of services whom accessed the professional mailing list is unknown, there are approximately 160 student counselling services in the UK. Moreover, a previous annual survey distributed through the same professional mailing list captured data from 63 services in 2011/12 (see Dailey & Abbott, 2013), highlighting a stronger response rate for the current study.

The 113 counselling services were drawn from the following sectors: SFCs (n = 11, 9.7%), FE (n = 37, 32.7%), and HE (n = 65, 55.6%). The study received ethical approval from the University of Sheffield Research Ethics Committee before expressions of interest were sought from heads of service (Ref:1078).

Analytic overview

As service facilities are determined by the level of support they have, both financially and in terms of staffing, service characteristics are anticipated to vary according to service size. Therefore, survey data has been grouped into small, medium, and large based on tercile cut-points, within each sector, from the total number of students registered at each institution.² Moreover, grouping services according to the number of student registrations is hoped to be informative by enabling heads of service to make comparisons and reflect on their own service. The sizes of the groups were operationalised as follows: (1) small (∼12,000 students; n = 22, 33.8%); (2) medium (12,001–18,673 students; n = 22, 33.8%); and (3) large (18,674 + students; n = 21, 32.4%). FE institutions were grouped into: (1) small (∼8,000 students; n = 14, 37.8%); (2) medium (8,001–15,000 students; n = 13, 35.1%); and (3) large (15,001 + students; n = 10, 27%). SFCs were grouped into: (1) small (∼1,927 students; n = 4, 36.4%); (2) medium (1,928–2,400 students; n = 4, 36.4%); and (3) large (2,401 + students; n = 3, 27.3%).

Analysis of survey data is predominantly descriptive with the goal of providing an initial descriptive account of UK student counselling services, given the limited research on UK services. As data were normally distributed, the mean, standard deviation and range have been provided to characterise services. Service structure was characterised as the number of years the service had been available and the full-time equivalent (FTE) of paid/volunteer therapeutic staff across low and high-intensity support (e.g. Counselling, Cognitive Behaviour Therapy (CBT), psychotherapy). Factors affecting services were identified by the typical and maximum number of attended and unattended counselling sessions; average, minimum and maximum waiting period for initial and ongoing counselling sessions; the administration of routine outcome measures (ROMs); and difficulties experienced while using ROMs and other assessments. Given the qualitative nature of data capturing difficulties experienced using ROMs, thematic analysis (see Braun and Clarke, 2006) was performed by author EB to provide prominent themes across all services. Themes were determined by grouping comments which were similar in nature (e.g. describing inconsistent use of ROM’s across staff). Themes were corroborated by author MB, before weighted percentages were calculated to establish overlapping experiences across heads of service.

Pearson correlations were calculated to establish the relationships between the waiting periods and the number of attended and unattended counselling sessions (defined as: ‘sessions in which the student did not attend or cancelled after referral’). Service users were characterised by the percentage of student referrals out of the total number of students registered at the institution that year; the percentage of referrals for low and high-intensity support; and overall referrals over a 3-year period to identify changes in demand. The final analysis presents the percentage of services that previously, currently, or would like to use a range of alternative support resources including a range of therapeutic technologies.

Results

Service years

Table 1 presents the number of years counselling services had been available across size and sector. Large HE counselling services had been available the longest, followed by medium services, and small services. This pattern is reflected in FE whereas in SFC, large services had been available the longest followed by small and medium services.

Table 1. Duration of existence of embedded counselling service (in years).

Sector & size	Duration of existence of embedded counselling services (years)
	N	Mean	SD	Min-Max
HE	65
Small	22	20.23	11.25	2–50
Medium	22	27.29	9.42	14–48
Large	21	28.43	9.23	8–46
FE	37
Small	14	14.32	6.90	2–25
Medium	13	16.20	3.99	9–23
Large	10	17.44	5.15	12–26
SFC	11
Small	4	13.50	6.02	7–20
Medium	4	11.50	6.58	3–18
Large	3	18.67	7.09	11–25

FTE of therapeutic staff

Irrespective of sector or size, all counselling services had more high-intensity therapeutic staff than any other available role (see Table 2). This difference was less pronounced in the FE sector, while in SFC the only role other than high-intensity was unpaid. Across service size, large services had the most high-intensity counsellors, whereas medium services had the most Mental Health Advisors (MHAs; defined as ‘someone whose specific role is to assess the impact of mental health needs on academic ability and provide information about mental health issues and the services/support available’) and small services had the most unpaid/trainee counsellors.

Table 2. FTE of therapeutic staff across HE, FE and SFC counselling services.

Service size	N	High-intensity	Low-intensity	Groupwork	MHA	Unpaid	Total
HE
Small	18	1.86	0.09	0.08	0.95	1.37	4.35
Medium	19	3.71	0.43	0.01	1.92	0.62	6.69
Large	18	4.38	0.32	0.00	1.86	1.35	7.91
Total	55	9.95	0.84	0.09	4.73	3.34	18.95
FE
Small	11	1.11	0.09	0.12	1.00	0.13	2.45
Medium	10	0.93	0.44	1.11	0.76	0.63	3.87
Large	9	1.08	0.00	0.00	–	0.37	1.45
Total	30	3.12	0.53	1.23	1.76	1.13	7.77
SFC
Small	3	0.75	0.00	0.00	–	0.20	0.95
Medium	4	0.37	0.00	0.00	–	0.69	1.06
Large	3	1.00	0.00	0.00	–	0.22	1.22
Total	10	2.12	0.00	0.00	–	1.09	3.23

MHA = Mental Health Advisor defined as ‘someone whose specific role is to assess the impact of mental health needs on academic ability and provide information about mental health issues and the services/support available’. Missing data (HE: small = 4; medium = 3; large = 3; FE: small = 3; medium = 3; large = 1; SFC: small = 1; medium = 0; large = 0).

Referrals

In HE the majority of students were referred to high-intensity support and this was consistent across service size (see Table 3). A small percentage of students attended for only the first appointment (and did not go on to receive counselling)³, and this was highest in medium services which was more than twice as many than small HE services. Medium HE services also reported the most students being referred for low-intensity support (e.g. one-off workshops, short groupwork, or psychoeducation). This pattern of referrals matched FE and SFC, and overall SFC reported the highest percentage of referrals for high-intensity support, but this was also the only form of support reported. Irrespective of the intensity of support, both FE and HE services experienced increased demand across the 3-years (2011–2014). Inspection of Figure 1 indicates that the rise in demand is most noticeable in FE and HE, particularly in 2012, whereas referrals in SFCs remain stable. Importantly, the number of referrals for counselling in 2011–2014 has increased beyond the anticipated rise in students entering further and higher education. This remains true even when the maximum number of registered students in 2013/14 is used to calculate the percentage of referrals across sectors. In FE for instance, referrals for counselling account for approximately 2% of students registered in 2011/12 which rises to 6% in 2012/13. Equally in HE, referrals for counselling account for approximately 6% of students registered in 2011/12 which rises to 18% in 2012/13. By contrast the percentage of counselling referrals in SFCs remain at approximately 5% between 2011 and 2014.

Figure 1. Three-year trend of student referrals for higher education, further education, and sixth form college counselling services (n = 92). *SD (HE: 2011/12 = 258; 2012/13 = 291; 2013/14 = 613; FE: 2011/12 = 54; 2012/13 = 72; 2013/14 = 98; SFC: 2011/12 = 33; 2012/13 = 38; 2013/14 = 42).

Table 3. Percentage of student referrals for mental health support at HE, FE and SFC counselling services.

	N	Percentage of student referrals
		Assessment only^a	High-intensity	Low-intensity
HE	52
Small	16	6.5	81.7	11.8
Medium	18	15.5	69.6	14.9
Large	18	8.7	82.3	9.0
FE	20
Small	7	10.7	85.9	3.4
Medium	7	13.4	86.6	0.0
Large	6	7.0	93.0	0.0
SFC	7
Small	2	3.7	96.3	0.0
Medium	2	7.3	91.0	1.7
Large	3	0.0	100.0	0.0

^aThe ‘assessment only’ category does not include students who scored below the cut-off to receive counselling (i.e. high-intensity) as those students have been included in the low-intensity group. Moreover, for services that included the assessment in the first counselling session, respondents were instructed to only include students that did not go on to receive counselling. Missing data (HE: small = 6; medium = 4; large = 3; FE: small = 7; medium = 7; large = 6; SFC: small = 2; medium = 2; large = 0).

Attended counselling sessions

Students in HE typically attended 3–4 counselling sessions, but there was large variation in small services compared to medium and large services (see Table 4). Students in medium HE services also attended the most counselling sessions in 2013/14, which was 10 sessions more than small and large HE services. Students in FE typically attended 3–4 counselling sessions. Students in large FE institutions attended the most counselling sessions. Students in small and medium SFCs attended 3–5 counselling sessions and there was little variation in the maximum attendance across SFC size.

Table 4. The typical and maximum number of attended counselling sessions recorded in 2013/14.

Service	Typical attended sessions (n)				Maximum attended sessions (n)
	N	Mean	SD	Min-Max	Mean	SD	Min-Max
HE	60
Small	20	4.40	3.17	1–12	24.50	7.50	12–34
Medium	19	3.15	1.64	1–6	22.92	10.76	6–46
Large	21	3.29	1.64	1–6	23.20	6.74	11–36
FE	31
Small	12	3.62	2.04	1–7	20.29	5.90	16–32
Medium	10	3.40	2.30	1–6	17.21	9.33	8–32
Large	9	4.20	2.17	1–6	28.25	11.50	14–39
SFC	6
Small	3	5.50	6.36	1–12	25.50	7.78	20–31
Medium	2	4.75	2.36	1–7	25.00	10.23	10–32
Large	1	3.00	na	1–6	na	na	na

Missing data (HE: small = 2; medium = 3; large = 0; FE: small = 2; medium = 3; large = 1; SFC: small = 1; medium = 2; large = 2).

Unattended counselling sessions

In HE, the annual number of unattended counselling sessions increased with service size (small: mean = 275.14, SD = 209.71, min = 23, max = 857; medium: mean = 487.01, SD = 239.39, min = 191, max = 868; and large: mean = 682.88, SD = 437.57, min = 151, max = 1368). In FE, medium counselling services reported the highest number of unattended counselling sessions (mean = 265.25, SD = 241.22, min = 108, max = 622), followed by large (mean = 194.67, SD = 61.28, min = 124, max = 233) and small with the fewest (mean = 154.40, SD = 65.01, min = 74, max = 213). In SFC, small services reported the fewest unattended counselling sessions compared to FE and HE (mean = 115.09, SD = 106.13, min = 9, max = 362.14), however, medium and large services did not report on unattended sessions.

Average waiting periods

Inspection of Table 5 demonstrates that the average waiting period for the initial face-to-face appointment was 6 working days in large HE services and 7 working days for small and medium services. After this, students waited approximately 17–18 working days between ongoing counselling sessions across service size and sector. There was a large variation in the potential waiting period across service sizes, which was the longest in small services for the initial appointment and in large services for ongoing sessions.

Table 5. Wait period (in working days) for the initial assessment and between ongoing counselling sessions in higher education, further education, and sixth form colleges.

Service Size	N	Initial waiting period				Ongoing waiting period
		Mean	SD	Min	Max	Mean	SD	Min	Max
HE	57
Small	19	6.83	4.56	2.00	18.00	17.64	10.48	18.00	33.00
Medium	18	6.74	2.78	3.00	12.40	16.57	8.51	12.40	34.00
Large	20	6.14	3.59	0.00	12.50	16.97	13.90	12.50	43.59
FE	29
Small	13	8.05	3.83	4.00	13.20	8.58	3.53	13.20	15.00
Medium	9	9.12	4.80	4.00	13.50	17.50	6.61	13.50	25.00
Large	7	6.36	1.67	4.80	8.00	10.98	9.46	8.00	27.50
SFC	5
Small	3	7.50	3.54	5.00	10.00	20.00	14.14	10.00	30.00
Medium	2	7.63	4.39	3.00	12.50	8.00	2.65	12.50	10.00
Large	0	–	–	–	–	–	–	–	–

Missing data (HE: small = 3; medium = 4; large = 1; FE: small = 1; medium = 4; large = 3; SFC: small = 1; medium = 2; large = 3).

There were no significant associations between the waiting periods and the number of unattended sessions (Initial: r = .28, p = .16; ongoing: r = .28, p = .20), suggesting that factors aside from the waiting list affect students’ ability to attend counselling sessions. There were also no significant associations between the waiting periods and the number of counselling sessions students attended (Initial: r = .06, p = .74; ongoing r = .03, p = .88). This was also true for the maximum waiting periods and the number of counselling sessions attended (Initial: r = .06, p = .74; ongoing: r = .09, p = .88). However, there was a significant negative association between the number of counselling sessions attended and the number of unattended sessions (r = .48, p = .01), suggesting that students were less likely to cancel sessions the further into counselling they were.

Compared to HE, FE services reported longer waiting periods for both the initial appointment and ongoing counselling sessions, with the longest initial wait found in medium sized services (Table 5). For ongoing counselling sessions, students waited the least in small services, which was also less than the waiting period for ongoing sessions in all HE services. This was also true for the maximum waiting period for ongoing sessions in FE which was typically 10 days fewer than HE. However, few FE services provided data on the waiting period as follows: 4 small services (40%), 3 medium services (30%), and 4 large services (40%). SFCs also had missing data, with only 5 services (36%) contributing data on the waiting periods. Of the data provided, SFCs showed a similar waiting period to FE services for the initial assessment with students waiting approximately 8 working days to be seen. The longest waiting period in SFCs, for both the initial and ongoing counselling sessions, was found in small services, whereas medium services reported the shortest waiting period overall.

Measuring outcomes

Of the various outcome measures available, 39% (total n = 61) of HE services used the Clinical Outcomes in Routine Evaluation-Outcome Measure (CORE-OM; see Barkham et al., 2010), 5% used the Patient Health Questionnaire (PHQ-9; Spitzer, Kroenke, & Williams, 1999), and 3% used the Counseling Center Assessment of Psychological Symptoms (CCAPS; Locke et al., 2011). A further 47% did not use a validated clinical measure although 15% used their own assessment or feedback form. The final 6% did not report on their use of clinical outcome measures. A total of 20% of services used more than one clinical measure. In FE services, only 6 services (42%) used a validated clinical measure, which was predominantly the CORE-OM, and the remaining 48% used their own service evaluation form or questions concerning the impact of counselling services on students’ ability to cope academically. In SFCs, only one service (9%) used a validated clinical measure (PHQ-9) but also reported that 2013/14 was the first year of administration.

In HE, 92% of medium and large services and 79% of small services administered measures at initial screening (i.e. pre-treatment). Only 25% of medium and 62% of large services administered measures at the end of therapy (post-treatment). However, 82% of small services collected post-data. Few HE services administered measures every session representing only 8% of small, 23% of medium and 11% of large HE services. Services in FE and SFCs were less likely to use clinical outcome measures compared to HE with only 36–50% collecting pre-data and 43–50% collecting post-data. However, SFCs were most likely to collect data at every counselling sessions compared to FE and HE (75–100%).

Problems experienced with clinical outcome measures

Of the 65 HE institutions, 37 (57%) reported problems experienced when using (or deciding not to use) a ROM. Ten key issues were raised: (1) low return rate for follow-up data (n = 30, 81%); (2) missing data from students with unplanned endings (n = 28, 76%); (3) inconsistency across staff using/not using measures (n = 25, 68%); (4) time consuming to use measures or to interpret/discuss/input/analyse results (n = 24, 65%); (5) difficulties analysing or reporting data/not having a dedicated member of staff (n = 23, 62%); (6) inconsistency in data across services and unable to benchmark (n = 15, 41%); (7) concerns over differences between different clinical measures (n = 13, 35%); 8) concerns over students not wanting to complete forms (n = 4, 11%); (9) no UK normative sample for students (n = 2, 5%); and (10) concerns over students exaggerating distress to be seen quicker (n = 1, 3%).

Offering alternative support

To explore the types of alternative support available from student counselling services and how the types of support vary according to time and interest, services were asked to report on whether they offered a range of alternative support options in 2013, 2014, and whether they would like to offer any of the types of support listed including: email counselling, phone counselling, self-help books, online self-help, peer-to-peer, groupwork, eTherapy, online communities, and mobile phone apps. Responses were provided by HE services only, and of the 65 HE services in the survey, 46 services (71%) reported on the use and interest in offering alternative support. Percentages were calculated for the number of HE services which have used or would like to use each type of alternative support, with the most prominent including: email counselling, eTherapy, online communities, and mobile phone apps (see Figure 2). HE services differed greatly according the types of alternative support they offered and the types of alternative support they would like to offer. In small services, the use of email counselling, online communities and eTherapy reduced over time with little interest in keeping these services. By contrast, medium services showed increased popularity for email counselling and eTherapy, with declining interest in online communities. Large services also showed reduced interest in eTherapy, email counselling, but unlike small and medium services, large services showed slightly more interest in offering online communities in the future. The only form of alternative support that increased in popularity across all services was mobile phone apps to support mental health and wellbeing. FE and SFCs did not report on their use or interest in alternative therapeutic support.

Figure 2. Use of alternative support in higher education counselling services. A = Small services (n = 18); B = Medium services (n = 20); C = Large services (n = 20).

Discussion

The aim of this study was to characterise UK embedded counselling services in HE, FE, and SFCs to determine their capacity to address the increasing number and severity of student referrals. As expected, the overall level of demand on services increased over a 3-year period and this trend was reflected in referrals, predominantly for high-intensity support. However, this only applied to HE and FE sectors and was particularly acute for HE in 2013. This is noteworthy because it coincides with the first student cohort affected by the rise in tuition fees, introduced in September 2012 (Bolton, 2014). Research has linked student debt with poorer psychological functioning and this relationship has been corroborated by literature even before the fee rise (Cooke et al., 2004). The increased demands for student counselling services may also be attributed to widening participation schemes as more students from more disadvantaged backgrounds are able to access HE and early reports anticipated an increase in the reporting of student mental ill-health (Kemp, 2002).

Despite subtle differences across the sectors, there was an overwhelming trend to utilise high-intensity therapeutic staff. The finding that services predominantly refer for high-intensity support suggests that students approach services when their mental well-being is already affecting their ability to cope. This severity also indicates that students are no longer a privileged group in society and demonstrate a higher prevalence of mental ill-health compared to the general population (Stallman, 2010). Together, these findings substantiate the need for preventative programmes across educational institutions to equip students with the skills (e.g. emotional resilience; see Brown, 2016) to manage their mental health. Such programmes would benefit from promoting help-seeking behaviour to encourage students to seek help before their mental needs are severe.

While not surprising that that the largest therapeutic role was for high-intensity support, the finding that a second prominent role was for MHAs may not have been foreseen. The growth of MHAs in student counselling services has been reported in previous literature and demonstrates a promising response to recommendations from the Royal College of Psychiatrists report (2011). The recent availability of MHAs also reflects changes in service structure as educational institutions introduce dedicated roles to assess the impact of mental health needs on academic ability (see Blakely & Bragg, 2010). By offering specific types of support via such roles, student counselling services highlight the importance of supplying a therapeutic team that is trained and experienced in the student context.

Whilst student counselling services have traditionally offered short-term support, the number of counselling sessions offered has typically varied. This variation has also often changed in response to increasing demands by means of managing longer waiting lists (Mair, 2016). Our findings suggest that two groups of students are likely approaching services: those who are adjusting to a new experience or task, and those in need of on-going therapy. Although the majority of students received short-term support, there have been concerns over the length of time students wait to be seen, particularly as higher demands have led to longer waiting lists (Mowbray et al., 2006). The waiting period has been a particular concern because there is mixed evidence to suggest that the mental health needs of individuals may worsen whilst waiting to be seen. However, they may also improve or show no change (Posternak & Miller, 2001). Despite prior concerns, our findings suggest that being on a waiting list does not lead to students needing more counselling sessions and they are not necessarily at risk of disengaging from therapy. This finding is likely due to the reasonable length of the waiting lists in FE/HE compared to the lengthy waiting lists reported in external counselling services (Dendridge, 2015).

In line with previous literature, the current study found that the CORE-OM was the most commonly used instrument in HE and FE sectors. However, almost half of services did not use a validated clinical measure and 15 per cent used their own feedback measures. It is difficult to see how some services will be able to survive in the absence of evidenced-based outcomes that can be benchmarked against relevant population norms. Collecting client feedback is advantageous as it contributes to the service evidence reported to governing bodies and is recommended to ensure that services are responsive to students’ needs (Mental Wellbeing in Higher Education Working Group, 2015).

The current study aimed to distinguish problems experienced when using validated clinical measures to inform service development. Our findings identified several issues that concerned either students’ use of clinical forms or their use across different therapists and services. The overarching themes centred on an absence of a culture of evaluation and a lack of strategic implementation that would enable collected data to be best used. The constant message of needing additional support in order to implement measures was evident. However, there are now brief measures that are under Creative Commons License and can be mounted free into electronic management systems: for example, CORE-10 and GP-CORE (Barkham et al., 2010). It is to be hoped that services not using a bona fide outcome measure change their practice as soon as possible. There were also concerns about using clinical assessments that do not capture student distress (e.g. academic, family, social anxiety, or substance misuse) or the absence of UK norms for student counselling. Interestingly a small percentage of services used CCAPS (Locke et al., 2011), which is a student specific clinical tool used widely in America and has been validated recently for use in the UK (Broglia, Millings, & Barkham, 2017).

In terms of offering alternative support, this appears particularly important in student counselling services because students often seek help during evenings and at weekends or in more accessible formats such as online or self-help support (Mair, 2016). The current study found particular interest in email counselling, eTherapy, online communities, and mobile phone apps. The finding that small and large services have reduced interest in email counselling and eTherapy, having used them previously, reflects a shift in interest as newer forms of therapeutic technology become available. The cost of new therapeutic technologies and devices are also important considerations for offering alternative support. For instance, it is not surprising that email counselling and video conferencing were used heavily in 2012/13 as they create little expense on a service budget that is already stretched. In similar light, the introduction of well-being apps offers alternative support which is substantially cheaper than the online self-help platforms currently available.

The recent surge of apps for mental well-being has sparked new research exploring the efficacy, effectiveness, and potential implications of using apps to support mental health (Powell, Chen, & Thammachart, 2017). One growing concern is the abundance of apps that are readily accessible by the public without the means to quality assess or determine the appropriateness for individuals to use apps. For example, a recent review of mental and physical health apps found that only 14 per cent had been designed with input from a healthcare professional (Sedrati, Nejjari, Chaqsare, & Ghazal, 2016). Interestingly, the review also found that although the majority of apps for physical health had been designed for medical professionals rather than patients, the majority of apps for mental health had been designed for patients. Together these results highlight that mental health apps should be used with caution and that users could benefit from having professional guidance on the appropriate use of apps.

Cautions and future considerations

Caution should be taken when interpreting results and when drawing conclusions in comparison to individual service data. As there was limited information on embedded counselling services in HE, FE and SFCs, the basic task of the survey was to collect comparative service data that would profile services in order to provide a platform for future research. Moreover, whilst data have been collected on a large number of counselling services across the educational sectors, there was inevitably missing data; most noticeable in FE and SFC. This missing data raises awareness of the types of data currently being collected by embedded counselling services. This finding also highlights the need for guidelines (and encouragement) for collecting data which is informative for future service development.

Conclusion

In conclusion, the current study highlighted the marked severity of student mental health needs and the growing demand that is accelerating in the HE sector, with raised tuition fees and widening participation schemes a likely contributing factor. We found evidence of progress made with new roles (i.e. MHAs) but still a shortfall in the collection of routine outcome data. Finally, our findings demonstrate an overlapping interest in offering mobile apps to support student mental health, which show potential to address the challenges outlined in the current study.

Acknowledgements

We would like to thank Andy Hill as past Head of Research at BACP, Jeremy Christey as chair of University and college Counselling Services (UCS), and Patti Wallace as past lead advisor for UCC for supporting the survey development and distribution. We would also like to thank members of the Heads of UCS (HUCS) for contributing to question development, in particular: Louise Knowles (University of Sheffield); Kate Tindle (Bangor University); Kirstie Adamson as deputy head of service (UWE Bristol); Helen Bently (Loughborough University); Trevor Butlin (DeMonfort University); Geraldine Dufour (University of Cambridge); Charlotte Joseph (University of Wolverhampton); and Eamonn O’Mahony as a counsellor (University of East Anglia). Finally we would like to thank the heads of service and administrative staff that completed the survey.

Disclosure statement

MB was instrumental in conceptualising the Clinical Outcomes in Routine Evaluation-Outcome Measures (CORE-OM & CORE-10) and is a trustee of the CORE System Trust (CST), an organisation that holds and protects the copyright on the CORE instruments that are under Creative Commons License. CORE-OM was developed via research grants from the Mental Health Foundation. MB receives no personal financial benefit from the CORE outcome measures. See www.coresystemtrust for more information.

Notes on contributors

Emma Broglia is currently a post-doctoral researcher in the University Secretary's Office at the University of Sheffield. Her research interests include student mental health, embedded counselling services, help-seeking behaviour, and attainment in higher education.

Abigail Millings is a lecturer in Psychology at the University of Sheffield. Her research interests include attachment styles and the implementation of assistive technologies.

Michael Barkham is a Professor of Clinical Psychology and Director of the Centre for Psychological Services Research at the University of Sheffield. He has a long-term research interest in outcome measurement and the provision of psychological services and support to students.

ORCID

Emma Broglia http://orcid.org/0000-0003-2137-8187

Abigail Millings http://orcid.org/0000-0002-7849-6048

Michael Barkham http://orcid.org/0000-0003-1687-6376

Additional information

Funding

MB reports funding from the British Association for Counselling and Psychotherapy (BACP; see www.bacp.co.uk) for a PhD scholarship, awarded to EB, for the conduct of this study.

Notes

1 See http://www.counselling.cam.ac.uk/general/reports for example reports.

2 The decision to split services for analysis was supported by the HUCS professional group as it was considered more informative than analysing the sample as a whole, as presented in a previous report (see Dailey & Abbott, 2013).

3 The reasons are unknown as to why this sub-group of students only attended the first assessment (i.e. whether they decided not to receive support), however it is unlikely due to students not meeting the criteria to receive counselling as such students would have been recorded in the low-intensity group.

Appendix 1

Table of definitions used in online survey for counselling services in further and higher education.

Table

Term	Definition and additional information provided
1. Counselling	The questions in this survey refer to the academic year 2013-2014, unless otherwise stated. For any questions which refer to “counselling” such as “counselling staff” or “access to counselling services”, please include information on psychotherapy unless it has been explicitly stated to be separate. Thank you for your time and cooperation for completing this survey.
2. High intensity	Counselling, psychotherapy, CBT, therapeutic group work
3. Low intensity	Psychological Wellbeing Practitioner, wellbeing workers
4. Groupwork	Psychoeducation, healthy campus, education, low intensity groups
5. Full-time equivalent of therapeutic staff	Therapeutic contact including supervision is assumed to be 25 hours per FTE staff member. To calculate the contribution of volunteers (including their supervision) is; 3 hours = 0.12; 3.5 hours = 0.14; 4 hours = 0.16; 4.5 hours = 0.18; 5 hours = 0.20; 5.5 hours = 0.22; 25 hour week = 1 FTE
6. Mental Health Advisor (MHA)	For example someone whose specific role is to assess the impact of mental health needs on academic ability and provide information about mental health issues and the services/support available
7. Number of referrals to counselling; How many students used your service and attended at least one counselling session?	Including drop-in, self-referral, and excluding partner institutions
8. Unattended counselling sessions	Sessions in which the student did not attend or cancelled after referral
9. Waiting period for assessment after first contact	Not including emergency/crisis counselling