scholarly journals Development and Case Study Application of a Proxy-Generated Outcome Measure of Suffering for use with Clients with Illusory Mental Health

2020 ◽  
Vol 11 (1) ◽  
pp. 32-57
Author(s):  
Giulia Guglielmetti ◽  
Enrico Benelli
Keyword(s):  
Mental Health ◽  
Outcome Measure ◽  
Self Report ◽  
Idiographic Approach ◽  
Illusory Mental Health ◽  
Nomothetic Approach ◽  
Study Application

The concept of illusory mental health is described as the rationale for needing an approach for working with individuals who are unaware of their suffering and are therefore unable to describe their problems through self-report instruments. The use of a nomothetic approach using self-report or clinician-generated standardised instruments is compared with an idiographic approach for working with such individuals. A case study is used to illustrate the development and first application of a Proxy-Generated Outcome Measure  (PGOM) that allows clinicians, observers and researchers to trace an individualised understanding of a client’s core sufferings and changes occurring during the process of psychotherapy. A comparison with a nomothetic outcome measure is also presented.

scholarly journals Recovering Quality of Life (ReQoL): a new generic self-reported outcome measure for use with people experiencing mental health difficulties

2018 ◽  
Vol 212 (1) ◽  
pp. 42-49 ◽  
Author(s):  
Anju Devianee Keetharuth ◽  
John Brazier ◽  
Janice Connell ◽  
Jakob Bue Bjorner ◽  
Jill Carlton ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Mental Health ◽  
Outcome Measures ◽  
Service User ◽  
Quantitative Methods ◽  
Outcome Measure ◽  
Well Being ◽  
Self Report ◽  
Better Than

BackgroundOutcome measures for mental health services need to adopt a service-user recovery focus.AimsTo develop and validate a 10- and 20-item self-report recovery-focused quality of life outcome measure named Recovering Quality of Life (ReQoL).MethodQualitative methods for item development and initial testing, and quantitative methods for item reduction and scale construction were used. Data from >6500 service users were factor analysed and item response theory models employed to inform item selection. The measures were tested for reliability, validity and responsiveness.ResultsReQoL-10 and ReQoL-20 contain positively and negatively worded items covering seven themes: activity, hope, belonging and relationships, self-perception, well-being, autonomy, and physical health. Both versions achieved acceptable internal consistency, test–retest reliability (>0.85), known-group differences, convergence with related measures, and were responsive over time (standardised response mean (SRM) > 0.4). They performed marginally better than the Short Warwick-Edinburgh Mental Well-being Scale and markedly better than the EQ-5D.ConclusionsBoth versions are appropriate for measuring service-user recovery-focused quality of life outcomes.Declaration of interestM.B. and J.Co. were members of the research group that developed the Clinical Outcomes in Routine Evaluation (CORE) outcome measures.

scholarly journals Use of a routine, self-report outcome measure (HoNOSCA–SR) in two adolescent mental health services

2002 ◽  
Vol 180 (3) ◽  
pp. 266-269 ◽  
Author(s):  
Simon Gowers ◽  
Warren Levine ◽  
Sarah Bailey-Rogers ◽  
Alison Shore ◽  
Emma Burhouse
Keyword(s):  
Mental Health ◽  
Outcome Measure ◽  
Outcome Measurement ◽  
Reliability And Validity ◽  
Adolescent Mental Health ◽  
Self Report ◽  
Routine Outcome Measurement ◽  
Health Measures ◽  
Length Of Treatment ◽  
Report Outcome Measure

BackgroundThe Health of the Nation Outcome Scale for Children and Adolescents (HoNOSCA) is an established outcome measure for child and adolescent mental health. Little is known of adolescent views on outcome.AimsTo develop and test the properties of an adolescent, self-rated version of the scale (HoNOSCA–SR) against the established clinician-rated version.MethodA comparison was made of 6-weekly clinician-rated and self-rated assessments of adolescents attending two services, using HoNOSCA and other mental health measures.ResultsAdolescents found HoNOSCA–SR acceptable and easy to rate. They rated fewer difficulties than the clinicians and these difficulties were felt to improve less during treatment, although this varied with diagnosis and length of treatment. Although HoNOSCA–SR showed satisfactory reliability and validity, agreement between clinicians and users in individual cases was poor.ConclusionsRoutine outcome measurement can include adolescent self-rating with modest additional resources. The discrepancy between staff and adolescent views requires further evaluation.

Understanding the Relationship between Mood Symptoms and Mobile App Engagement Among Breast Cancer Patients: A Machine Learning Process (Preprint)

2021 ◽  
Author(s):  
Anna N Baglione ◽  
Lihua Cai ◽  
Aram Bahrini ◽  
Isabella Posey ◽  
Mehdi Boukhechba ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Mental Health ◽  
Random Forest ◽  
Cancer Patients ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Self Report ◽  
Breast Cancer Patients ◽  
The Relationship

BACKGROUND Health interventions delivered via smart devices are increasingly being used to address mental health challenges associated with cancer treatment. Engagement with mobile interventions has been associated with treatment success, yet the relationship between mood and engagement among cancer patients remains poorly understood. One reason is the lack of a data-driven process for analyzing mood and app engagement data for cancer patients. OBJECTIVE The purpose of this study is to provide a step-by-step process for using app engagement metrics to predict continuously assessed mood outcomes in breast cancer patients. We describe the steps of data preprocessing, feature extraction, and data modeling and prediction. We then apply this process as a case study to data collected from breast cancer patients who engaged with a mobile mental health app intervention (IntelliCare) over 7-weeks. We compare engagement patterns over time (e.g., frequency, days of use) between high- and low-anxious and high- and low-depressed participants. We then use a Linear Mixed Model to identify significant effects and evaluate the performance of Random Forest and XGBoost classifiers in predicting weekly state mood from baseline affect and engagement features. METHODS We describe the steps of data preprocessing, feature extraction, and data modeling and prediction. We then apply this process as a case study to data collected from breast cancer patients who engaged with a mobile mental health app intervention (IntelliCare) over 7-weeks. We compare engagement patterns over time (e.g., frequency, days of use) between high- and low-anxious and high- and low-depressed participants. We then use a Linear Mixed Model to identify significant effects and evaluate the performance of Random Forest and XGBoost classifiers in predicting weekly state mood from baseline affect and engagement features. RESULTS We observed differences in engagement patterns between high- and low-anxious and depressed participants. Linear Mixed Model results varied by the featureset; these results revealed weak effects for several features of engagement, including duration-based metrics and frequency. Accuracy of predicting state mood varied according to classifier and featureset. The XGBoost classifier achieved the highest accuracy for state anxiety prediction when self-report scores and engagement features were used for only the most highly-used apps. The Random Forest classifier achieved the highest accuracy for state depression prediction when self-report scores and engagement features were used from all apps. CONCLUSIONS The results from the case study support the feasibility and potential of our analytic process for understanding the relationship between app engagement and mood outcomes in breast cancer patients. The ability to leverage both self-report and engagement features to predict state mood during an intervention could be used to enhance decision-making for researchers and clinicians, as well as assist in developing more personalized interventions for breast cancer patients.

Prevalence of Self-Reported Depression Symptoms and Perceived Anxiety Among Community-Dwelling U.S. Adults Reporting Tinnitus

2020 ◽  
Vol 5 (4) ◽  
pp. 959-970
Author(s):  
Kelly M. Reavis ◽  
James A. Henry ◽  
Lynn M. Marshall ◽  
Kathleen F. Carlson
Keyword(s):  
Mental Health ◽  
Fold Increase ◽  
Community Dwelling ◽  
Self Report ◽  
Depression Symptoms ◽  
Community Based Interventions ◽  
Data Set ◽  
Health Distress ◽  
Validated Questionnaire ◽  
Mental Health Distress

Purpose The aim of this study was to examine the relationship between tinnitus and self-reported mental health distress, namely, depression symptoms and perceived anxiety, in adults who participated in the National Health and Nutrition Examinations Survey between 2009 and 2012. A secondary aim was to determine if a history of serving in the military modified the associations between tinnitus and mental health distress. Method This was a cross-sectional study design of a national data set that included 5,550 U.S. community-dwelling adults ages 20 years and older, 12.7% of whom were military Veterans. Bivariable and multivariable logistic regression was used to estimate the association between tinnitus and mental health distress. All measures were based on self-report. Tinnitus and perceived anxiety were each assessed using a single question. Depression symptoms were assessed using the Patient Health Questionnaire, a validated questionnaire. Multivariable regression models were adjusted for key demographic and health factors, including self-reported hearing ability. Results Prevalence of tinnitus was 15%. Compared to adults without tinnitus, adults with tinnitus had a 1.8-fold increase in depression symptoms and a 1.5-fold increase in perceived anxiety after adjusting for potential confounders. Military Veteran status did not modify these observed associations. Conclusions Findings revealed an association between tinnitus and both depression symptoms and perceived anxiety, independent of potential confounders, among both Veterans and non-Veterans. These results suggest, on a population level, that individuals with tinnitus have a greater burden of perceived mental health distress and may benefit from interdisciplinary health care, self-help, and community-based interventions. Supplemental Material https://doi.org/10.23641/asha.12568475

Integrated Care Case Study: A Community Mental Health Center and a Federally Qualified Health Center

2012 ◽  
Author(s):  
Jennifer E. Cato-Degroff ◽  
Brian Desantis ◽  
Fred Michel ◽  
Michael D. Welch ◽  
Kelly Phillips-Henry ◽  
...  
Keyword(s):  
Mental Health ◽  
Community Mental Health ◽  
Health Center ◽  
Integrated Care ◽  
Community Mental Health Center ◽  
Mental Health Center ◽  
Federally Qualified Health Center

ANALISIS KINERJA KEUANGAN IAIN PONTIANAK TAHUN 2014-2018 BERDASARKAN PENDEKATAN BALANCE SCORECARD

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
JATRIANA B2041142013
Keyword(s):  
Higher Education ◽  
Balanced Scorecard ◽  
Six Sigma ◽  
Balance Scorecard ◽  
The Balanced Scorecard ◽  
College And University ◽  
University Planning ◽  
Education Journal ◽  
Study Application

Penelitian ini bertujuan untuk mengukur kinerja keuangan kampus IAIN Pontianak menggunakan pendekatan Balance Scorecard. Metode penelitian ini adalah kuantitatif dengan menggunakan statistika untuk menganalisis sampel yang digunakan sebanyak 664 orang mahasiswa dan 193 orang dosen dan pegawai. Hasil penelitian menyatakan bahwa variabel perspektif pelanggan, perpektif bisnis internal dan variabel perspektif pertumbuhan dan pembelajaran, masing-masing berpengaruh positif dan signifikan terhadap peningkatan kinerja keuangan IAIN Pontianak.Kata Kunci : Balance Scorecard, IAIN Pontianak, Kinerja KeuanganDAFTAR PUSTAKA Andriyanto, R. W., & Metalia, M. (2010). Efektivitas Balanced Scorecard Dalam Maningkatkan Kinerja Manajerial Badan Usaha Milik Negara (Bumn). Jurnal Akuntansi dan Investasi, 11(2), 97-114.Arikunto, S. 1992. Prosedur penelitian: Suatu pendekatan praktik. Rineka Cipta.Bastian, Indra. 2006. Akutansi Sektor Publik, Suatu Pengantar. Jakarta: Airlangga.Brown, Cindy. 2012. Application of the Balanced Scorecard in Higher Education: Opportunities and Challenges - An Evaluation of Balanced Scorecard Implementation at the College of St. Scolastica. SCUP; Society for College and University Planning. www.scup.org/phe.html.Effendi, R. (2012). Pengukuran Kinerja Sektor Publik Dengan Menggunakan Balanced Scorecard (Studi Kasus Kanwil DJP Sumsel dan Kep. Babel). Jurnal Ilmiah Stie Mdp, 1(2), 67-73.Gaspersz, Vicent. 2002. Sistem Manajemen Kinerja Terintegrasi: Balanced Scorecard dengan Six Sigma untuk Organisasi Bisnis dan Pemerintah. Cet ke-3, Jakarta: Gramedia Pustaka UtamaHandayani, S. (2017). Analisis Balanced Scorecard Sebagai Tolok Ukur Kinerja Perusahaan Pada Pt Pos Indonesia ( Persero ) Lamongan. Jurnal Penelitian Ekonomi dan Akuntansi, II(3), 589-601.IAIN Pontianak. 2019. “Sistem Informasi Akademik Institut Agama Islam Negeri Pontianak.” Mahasiswa IAIN Pontianak. www.sia.iainptk.ac.id.Kaplan, S. Robert, and David P. Norton. 2000. Balanced Scorecard, Menerapkan Strategi Menjadi Aksi. Jakarta: Penerbit Erlangga.Karathanos, Dementrius, and Patricia Karathanos. 2005. “Appliying the Balanced Scoredard to Education.” Journal of Education for Business: 222–30.Kemenristek Dikti RI. 2019. “Pangkalan Data Pendidikan Tinggi:  Kementrian Riset , Teknologi, Dan Pendidikan Tinggi.” Tenaga Pendidik  IAIN Pontianak. www/forlap.ristekdikti.go.id.Kementrian Agama RI. 2019. “Seleksi Prestasi Akademik Nasional APerguruan Tinggi Keagamaan Islam Negeri.” SPAN PTKIN 2019. https://span-ptkin.ac.id.Mahsun, Muhammad. 2006. Pengukuran Kinerja Sektor Publik. 1st ed. Yogyakarta: BPFE.Mardiasmo. 2004. Akuntansi Sektor Publik. 1st ed. Yogyakarta: BPFE.Mulyadi. 2007. Balanced Scorecard, Alat Manajemen Kontemporer Untuk Pelipatganda Kinerja Keuangan Perusahaan. 1st ed. Jakarta: Penerbit Salemba Empat.Nugrahini, I. A. P., Ratnadi, N. M. D., & Putri, I. G. A. M. A. D. (2016). Penilaian Kinerja Berdasarkan Balanced Scorecard Pada Badan Penanaman Modal Dan Perijinan Daerah Kabupaten Tabanan. E-Jurnal Ekonomi dan Bisnis Universitas Udayana, 5(4), 829-856.Rollins, Andrea Mae. 2011. “A Case Study: Application of Balanced Scorecard in Hingher Education.” PhD Dissertation. San Diego State University.Singarimbun, Masri, and Sofian Effendi. 1989. Metode Penelitian Survey. Jakarta: LP3ES.Sugiono. 2005. Metode Penelitian Bisnis. Bandung: Alfabeta.Suta, I. W. P., & Dwiastuti, G. A. A. S. A. (2016). Pengukuran Kinerja Dengan Pendekatan Balanced Scorecard Pada Kantor Pusat Pt Bank Pembangunan Daerah Bali. Jurnal Bisnis Dan Kewirausahaan, 12(1), 32-41.Syarbaini, Khatib. 1986. “Fakultas Tarbiyah (Ketikan Manual).”Yassin, A., Musadieq, M. A., & Afrianty, T. W. (2016). Pengaruh Balanced Scorecard Dan Knowledge Management Terhadap Kinerja Karyawan Dan Kinerja Perusahaan (Studi Pada Karyawan Pt Semen Indonesia (Persero) Tbk). Jurnal Administrasi Bisnis, 33(2), 125-134.

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