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BackgroundAnxiety and depression continue to be prominent experiences of students approaching their university counseling service. These services face unique challenges to ensure that they continue to offer quality support with fewer resources to a growing student population. The convenience and availability of mobile phone apps offer innovative solutions to address therapeutic challenges and expand the reach of traditional support. ObjectiveThe primary aim of this study was to establish the feasibility of a trial in which guided use of a mobile phone well-being app was introduced into a student counseling service and offered as an adjunct to face-to-face counseling. MethodsThe feasibility trial used a two-arm, parallel nonrandomized design comparing counseling alone (treatment as usual, or TAU) versus counseling supplemented with guided use of a mobile phone well-being app (intervention) for 38 university students experiencing moderate anxiety or depression. Students in both conditions received up to 6 sessions of face-to-face counseling within a 3-month period. Students who approached the counseling service and were accepted for counseling were invited to join the trial. Feasibility factors evaluated include recruitment duration, treatment preference, randomization acceptability, and intervention fidelity. Clinical outcomes and clinical change were assessed with routine clinical outcome measures administered every counseling session and follow-up phases at 3 and 6 months after recruitment. ResultsBoth groups demonstrated reduced clinical severity by the end of counseling. This was particularly noticeable for depression, social anxiety, and hostility, whereby clients moved from elevated clinical to low clinical or from low clinical to nonclinical by the end of the intervention. By the 6-month follow-up, TAU clients’ (n=18) anxiety had increased whereas intervention clients’ (n=20) anxiety continued to decrease, and this group difference was significant (Generalized Anxiety Disorder–7: t22=3.46, P=.002). This group difference was not replicated for levels of depression: students in both groups continued to decrease their levels of depression by a similar amount at the 6-month follow-up (Physical Health Questionnaire–9: t22=1.30, P=.21). ConclusionSupplementing face-to-face counseling with guided use of a well-being app is a feasible and acceptable treatment option for university students experiencing moderate anxiety or depression. The feasibility trial was successfully embedded into a university counseling service without denying access to treatment and with minimal disruption to the service. This study provides preliminary evidence for using a well-being app to maintain clinical improvements for anxiety following the completion of counseling. The design of the feasibility trial provides the groundwork for the development of future pilot trials and definitive trials embedded in a student counseling service. Trial registrationISRCTN registry ISRCTN55102899; http://www.isrctn.com/ISRCTN55102899

BackgroundAlcohol consumption in the student population continues to be cause for concern. Building on the established evidence base for traditional brief interventions, interventions using the Internet as a mode of delivery are being developed. Published evidence of replication of initial findings and ongoing development and modification of Web-based personalized feedback interventions for student alcohol use is relatively rare. The current paper reports on the replication of the initial Unitcheck feasibility trial. ObjectiveTo evaluate the effectiveness of Unitcheck, a Web-based intervention that provides instant personalized feedback on alcohol consumption. It was hypothesized that use of Unitcheck would be associated with a reduction in alcohol consumption. MethodsA randomized control trial with two arms (control=assessment only; intervention=fully automated personalized feedback delivered using a Web-based intervention). The intervention was available week 1 through to week 15. Students at a UK university who were completing a university-wide annual student union electronic survey were invited to participate in the current study. Participants (n=1618) were stratified by sex, age group, year of study, self-reported alcohol consumption, then randomly assigned to one of the two arms, and invited to participate in the current trial. Participants were not blind to allocation. In total, n=1478 (n=723 intervention, n=755 control) participants accepted the invitation. Of these, 70% were female, the age ranged from 17-50 years old, and 88% were white/white British. Data were collected electronically via two websites: one for each treatment arm. Participants completed assessments at weeks 1, 16, and 34. Assessment included CAGE, a 7-day retrospective drinking diary, and drinks consumed per drinking occasion. ResultsThe regression model predicted a monitoring effect, with participants who completed assessments reducing alcohol consumption over the final week. Further reductions were predicted for those allocated to receive the intervention, and additional reductions were predicted as the number of visits to the intervention website increased. ConclusionsUnitcheck can reduce the amount of alcohol consumed, and the reduction can be sustained in the medium term (ie, 19 weeks after intervention was withdrawn). The findings suggest self-monitoring is an active ingredient to Web-based personalized feedback.

There remain barriers to securing robust and complete datasets from counselling embedded in Higher Education (HE). This study aimed to provide the first step towards developing a national dataset of student counselling outcomes drawn from differing outcome measures, platforms and reporting on all clients. Data from four counselling services using two clinical outcome measures and two platforms were pooled and analysed. Students presented to counselling with low levels of wellbeing and functioning, and high levels of depression, anxiety, academic distress and trauma. Counselling was particularly effective for improving depression, anxiety, wellbeing, hostility, social anxiety and academic distress. Results demonstrate value in pooling complete data from HE counselling services and we argue for developing a national dataset of university counselling data. [This article was written on behalf of the SCORE Consortium.]

BackgroundUnhealthy alcohol use among university students is cause for concern, yet the level of help seeking behavior for alcohol use is low within the student population. Electronic brief interventions delivered via the Internet present an alternative to traditional treatments and could enable the delivery of interventions on a population basis. Further evidence is needed of the effectiveness of Internet-delivered interventions and of their generalizability across educational institutions. ObjectiveOur objective was to evaluate the effectiveness across 4 UK universities of a Web-based intervention for student alcohol use. MethodsIn total, 1112 participants took part. Participants were stratified by educational institution, gender, age group, year of study, and self-reported weekly consumption of alcohol and randomly assigned to either the control arm or to the immediate or delayed intervention arms. Intervention participants gained access to the intervention between weeks 1 to 7 or weeks 8 to 15, respectively. The intervention provided electronic personalized feedback and social norms information on drinking behavior accessed by logging on to a website. Participants registered interest by completing a brief screening questionnaire and were then asked to complete 4 further assessments across the 24 weeks of the study. Assessments included a retrospective weekly drinking diary, the Alcohol Use Disorders Identification Test (AUDIT), and a readiness-to-change algorithm. The outcome variable was the number of units of alcohol consumed in the last week. The effect of treatment arm and time on units consumed last week and average units consumed per drinking occasion were investigated using repeated measures multivariate analysis of covariance (MANCOVA). In addition, the data were modeled using a longitudinal regression with time points clustered within students. ResultsMANCOVA revealed a main effect of time on units of alcohol consumed over the last week. A longitudinal regression model showed an effect of assessment across time predicting that participants who completed at least 2 assessments reduced their drinking. The model predicted an additional effect of being assigned to an intervention arm, an effect that increased across time. Regression analysis predicted that being male or being assigned to an intervention arm increased the odds of not completing all assessments. The number of units of alcohol consumed over the last week at registration, age, university educational institution, and readiness to change were not predictive of completion. ConclusionsDelivering an electronic personalized feedback intervention to students via the Internet can be effective in reducing weekly alcohol consumption. The effect does not appear to differ by educational institution. Our model suggested that monitoring alone is likely to reduce weekly consumption over 24 weeks but that consumption could be further reduced by providing access to a Web-based intervention. Further research is needed to understand the apparent therapeutic effect of monitoring and how this can be utilized to enhance the effectiveness of brief Web-based interventions.

Objective: To develop two prediction algorithms recommending person-centered experiential therapy (PCET) or cognitive–behavioral therapy (CBT) for patients with depression: (1) a full data model using multiple trial-based and routine variables, and (2) a routine data model using only variables available in the English NHS Talking Therapies program. Method: Data was used from the PRaCTICED trial comparing PCET vs. CBT for 255 patients meeting a diagnosis of moderate or severe depression. Separate full and routine data models were derived and the latter tested in an external data sample. Results: The full data model provided the better prediction, yielding a significant difference in outcome between patients receiving their optimal vs. non-optimal treatment at 6- (Cohen's d =.65 [.40,.91]) and 12 months (d =.85 [.59, 1.10]) post-randomization. The routine data model performed similarly in the training and test samples with non-significant effect sizes, d =.19 [−.05,.44] and d =.21 [−.00,.43], respectively. For patients with the strongest treatment matching (d ≥ 0.3), the resulting effect size was significant, d =.38 [.11, 64]. Conclusion: A treatment selection algorithm might be used to recommend PCET or CBT. Although the overall effects were small, targeted matching yielded somewhat larger effects. [ABSTRACT FROM AUTHOR]

We investigated the experiences of 10 counsellors undergoing training in a form of person-centred experiential therapy (PCET), known in the UK as Counselling for Depression (CfD). Training was delivered at a service level as part of the PRaCTICED [Pragmatic randomised controlled trial assessing the non-inferiority of counselling for depression versus cognitive behavioural therapy for patients in primary care meeting a diagnosis of moderate or severe depression trial]. Counsellors who took part in the study either completed (n = 5), failed to complete (n = 3) or were ongoing (n = 2) in their PCET training. Framework analysis was selected to extract rich data and an in-depth account of counsellors' experiences. Inconsistencies were reported between counsellors' previous theoretical backgrounds and PCET. Difficulties were also reported in resolving person-centred and emotion-focused elements of PCET. Key facilitators and barriers to completing PCET training were identified, including counsellors' intrapersonal factors.

Aim: Routine outcome monitoring (ROM), including the use of feedback, has become a much vaunted method in psychological therapies but is little used in university/college counselling and mental health services, perhaps because its adoption raises questions for many practitioners and service leaders. There is a need for both clinical‐ and research‐based statements to clarify the reasoning and rationale for ROM. This paper aims to present and respond to common challenges of and reservations about using ROM in student counselling and/or mental health services. Method: The article poses 15 questions and issues about the adoption of ROM drawn from the literature on this topic and further refined by practitioner‐ and researcher‐members of a consortium comprising service leads, practitioners, and researchers working in the field of student counselling in the UK. The questions address nine themes: (1) the purpose and yield of ROM; (2) the burden of measurement; (3) the impact on clients and process of therapy; (4) consistency with therapeutic theory; (5) client groups and settings; (6) concern from practitioners; (7) equality, diversity, and inclusion; (8) implementation; and (9) relationship with the paradigm of practice‐based evidence. Findings: Responses to each of the 15 questions are provided from a methodological, evidence‐based, and clinical perspective. Conclusions: The responses provide practitioners with the necessary information to enable them to make informed decisions as to the value, or otherwise, of adopting ROM, including feedback, in the delivery of counselling interventions, and generating evidence created from clinical practice. [ABSTRACT FROM AUTHOR]

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.

Conduct a systematic review and meta-analysis of randomized controlled trials (RCTs) evaluating the efficacy of individual humanistic-experiential therapies (HEPs) for depression. Database searches (Scopus, Medline, and PsycINFO) identified RCTs comparing any HEP intervention with a treatment-as-usual (TAU) control or active alternative intervention for the treatment of depression. Included studies were assessed using the Risk of Bias 2 tool and narratively synthesized. Post-treatment and follow-up effect sizes were aggregated using random-effects meta-analysis and moderators of treatment effect were explored (PROSPERO: CRD42021240485). Seventeen RCTs, synthesized across four meta-analyzes, indicated HEP depression outcomes were significantly better than TAU controls at post-treatment (g = 0.41, 95% CI [0.18, 0.65], n = 735), but not significantly different at follow-up (g = 0.14, 95% CI [−0.30, 0.58], n = 631). HEP depression outcomes were comparable to active treatments at post-treatment (g = −0.09, 95% CI [−0.26, 0.08], n = 2131), but significantly favored non-HEP alternative interventions at follow-up (g = −0.21, 95% CI [−0.35, −0.07], n = 1196). Relative to usual care, HEPs are effective in the short-term and comparable to non-HEP alternative interventions at post-treatment, but not at follow-up. However, imprecision, inconsistency, and risk of bias concerns were identified as limitations of the evidence included. Future large-scale trials of HEPs with equipoise between comparator conditions are required. [ABSTRACT FROM AUTHOR]