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Record W3092838678 · doi:10.1016/s2589-7500(20)30224-7

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

2020· article· en· W3092838678 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Lancet Digital Health · 2020
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsUniversity of Regina
FundersMacquarie UniversityAustralian Government
KeywordsTelehealthObservational studyAnxietyMedicineMental healthDepression (economics)Patient Health QuestionnaireDistressDemographicsFamily medicineTelemedicinePsychiatryHealth careClinical psychologyDepressive symptomsDemography

Abstract

fetched live from OpenAlex

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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Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.596

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.341
GPT teacher head0.478
Teacher spread0.137 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it