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      User characteristics and outcomes from a national digital mental health service: an observational study of registrants of the Australian MindSpot Clinic

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          Abstract

          Background

          Interest is growing in digital and telehealth delivery of mental health services, but data are scarce on outcomes in routine care. The federally funded Australian MindSpot Clinic provides online and telephone psychological assessment and treatment services to Australian adults. We aimed to summarise demographic characteristics and treatment outcomes of patients registered with MindSpot over the first 7 years of clinic operation.

          Methods

          We used an observational design to review all patients who registered for assessment with the MindSpot Clinic between Jan 1, 2013, and Dec 31, 2019. We descriptively analysed the demographics, service preferences, and baseline symptoms of patients. Among patients enrolled in a digital treatment course, we evaluated scales of depression (Patient Health Questionnaire-9 [PHQ-9]) and anxiety (Generalized Anxiety Disorder 7-Item Scale [GAD-7]), as primary measures of treatment outcome, from the screening assessment to post-treatment and a 3 month follow-up. The Kessler Psychological Distress 10-Item Plus Scale was also used to assess changes in general distress and disability, and course satisfaction was measured post-treatment.

          Outcomes

          A total of 121 652 screening assessments were started, of which 96 018 (78·9%) were completed. The mean age of patients was 35·7 years (SD 13·8) and 88 702 (72·9%) were women. Based on available assessment data, 36 866 (34·5%) of 106 811 participants had never previously spoken to a health professional about their symptoms, and most people self-reported symptoms of anxiety (88 879 [81·9%] of 108 494) or depression (78 803 [72·6%] of 108 494), either alone or in combination, at baseline. 21 745 patients started treatment in a therapist-guided online course, of whom 14 503 (66·7%) completed treatment (≥four of five lessons). Key trends in service use included an increase in the proportion of people using MindSpot primarily for assessment and information, from 52·6% in 2013 to 66·7% in 2019, while the proportion primarily seeking online treatment decreased, from 42·6% in 2013 to 26·7% in 2019. Effect sizes and percentage changes were large for estimated mean scores on the PHQ-9 and GAD-7 from assessment to post-treatment (PHQ-9, Cohen's d effect size 1·40 [95% CI 1·37–1·43]; and GAD-7, 1·45 [1·42–1·47]) and the 3 month follow-up (PHQ-9, 1·36 [1·34–1·38]; and GAD-7, 1·42 [1·40–1·44]); proportions of patients with reliable symptom deterioration (score increase of ≥6 points [PHQ-9] or ≥5 points [GAD-7]) were low post-treatment (of 13 058 respondents, 184 [1·4%] had symptom deterioration on the PHQ-9 and 282 [2·2%] on the GAD-7); and patient satisfaction rates were high (12 452 [96·6%] of 12 895 respondents would recommend the course and 12 433 [96·7%] of 12 860 reported the course worthwhile). We also observed small improvements in disability following treatment as measured by days out of role.

          Interpretation

          Our findings indicate improvement in psychological symptoms and positive reception among patients receiving online mental health treatment. These results support the addition of digital services such as MindSpot as a component in contemporary national mental health systems.

          Funding

          None.

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          Most cited references 33

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          Advantages and limitations of Internet-based interventions for common mental disorders.

          Several Internet interventions have been developed and tested for common mental disorders, and the evidence to date shows that these treatments often result in similar outcomes as in face-to-face psychotherapy and that they are cost-effective. In this paper, we first review the pros and cons of how participants in Internet treatment trials have been recruited. We then comment on the assessment procedures often involved in Internet interventions and conclude that, while online questionnaires yield robust results, diagnoses cannot be determined without any contact with the patient. We then review the role of the therapist and conclude that, although treatments including guidance seem to lead to better outcomes than unguided treatments, this guidance can be mainly practical and supportive rather than explicitly therapeutic in orientation. Then we briefly describe the advantages and disadvantages of treatments for mood and anxiety disorders and comment on ways to handle comorbidity often associated with these disorders. Finally we discuss challenges when disseminating Internet interventions. In conclusion, there is now a large body of evidence suggesting that Internet interventions work. Several research questions remain open, including how Internet interventions can be blended with traditional forms of care. Copyright © 2014 World Psychiatric Association.
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            To GEE or not to GEE: comparing population average and mixed models for estimating the associations between neighborhood risk factors and health.

            Two modeling approaches are commonly used to estimate the associations between neighborhood characteristics and individual-level health outcomes in multilevel studies (subjects within neighborhoods). Random effects models (or mixed models) use maximum likelihood estimation. Population average models typically use a generalized estimating equation (GEE) approach. These methods are used in place of basic regression approaches because the health of residents in the same neighborhood may be correlated, thus violating independence assumptions made by traditional regression procedures. This violation is particularly relevant to estimates of the variability of estimates. Though the literature appears to favor the mixed-model approach, little theoretical guidance has been offered to justify this choice. In this paper, we review the assumptions behind the estimates and inference provided by these 2 approaches. We propose a perspective that treats regression models for what they are in most circumstances: reasonable approximations of some true underlying relationship. We argue in general that mixed models involve unverifiable assumptions on the data-generating distribution, which lead to potentially misleading estimates and biased inference. We conclude that the estimation-equation approach of population average models provides a more useful approximation of the truth.
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              A brief measure for assessing generalized anxiety disorder: the GAD-7.

              Generalized anxiety disorder (GAD) is one of the most common mental disorders; however, there is no brief clinical measure for assessing GAD. The objective of this study was to develop a brief self-report scale to identify probable cases of GAD and evaluate its reliability and validity. A criterion-standard study was performed in 15 primary care clinics in the United States from November 2004 through June 2005. Of a total of 2740 adult patients completing a study questionnaire, 965 patients had a telephone interview with a mental health professional within 1 week. For criterion and construct validity, GAD self-report scale diagnoses were compared with independent diagnoses made by mental health professionals; functional status measures; disability days; and health care use. A 7-item anxiety scale (GAD-7) had good reliability, as well as criterion, construct, factorial, and procedural validity. A cut point was identified that optimized sensitivity (89%) and specificity (82%). Increasing scores on the scale were strongly associated with multiple domains of functional impairment (all 6 Medical Outcomes Study Short-Form General Health Survey scales and disability days). Although GAD and depression symptoms frequently co-occurred, factor analysis confirmed them as distinct dimensions. Moreover, GAD and depression symptoms had differing but independent effects on functional impairment and disability. There was good agreement between self-report and interviewer-administered versions of the scale. The GAD-7 is a valid and efficient tool for screening for GAD and assessing its severity in clinical practice and research.
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                Author and article information

                Journal
                Lancet Digit Health
                Lancet Digit Health
                The Lancet. Digital Health
                The Author(s). Published by Elsevier Ltd.
                2589-7500
                19 October 2020
                November 2020
                19 October 2020
                : 2
                : 11
                : e582-e593
                Affiliations
                [a ]MindSpot Clinic, Macquarie University, Sydney, NSW, Australia
                [b ]Department of Psychology, Macquarie University, Sydney, NSW, Australia
                [c ]Macquarie University Health Sciences Centre, Macquarie University, Sydney, NSW, Australia
                [d ]Discipline of Clinical Psychology, Graduate School of Health, University of Technology Sydney, Sydney, NSW, Australia
                [e ]University Centre for Rural Health, The University of Sydney, NSW, Australia
                [f ]Department of Behavioural Sciences and Learning, Linköping University, Linköping, Sweden
                [g ]Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
                [h ]Department of Psychology, University of Regina, Regina, SK, Canada
                [i ]Center for Behavioral Intervention Technologies, Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
                [j ]Centre for Children's Health Research and School of Psychology and Counselling, Queensland University of Technology, Brisbane, QLD, Australia
                Author notes
                [* ]Correspondence to: Dr Lauren G Staples, MindSpot Clinic, Macquarie University, Sydney, NSW 2109, Australia
                Article
                S2589-7500(20)30224-7
                10.1016/S2589-7500(20)30224-7
                7571905
                © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

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