scholarly journals The contribution of reliable and clinically significant change methods to evidence-based mental health

1998 ◽  
Vol 1 (3) ◽  
pp. 70-72 ◽  
Author(s):  
C. Evans ◽  
F. Margison ◽  
M. Barkham
Keyword(s):  
Mental Health ◽  
Evidence Based ◽  
Clinically Significant Change ◽  
Significant Change ◽  
Clinically Significant

scholarly journals Heart Rate Variability Analysis: How Much Artifact Can We Remove?

2020 ◽  
Vol 17 (9) ◽  
pp. 960-965
Author(s):  
David C. Sheridan ◽  
Ryan Dehart ◽  
Amber Lin ◽  
Michael Sabbaj ◽  
Steven D. Baker
Keyword(s):  
Mental Health ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Heart Rate Variability Analysis ◽  
Time Interval ◽  
Clinically Significant Change ◽  
Hrv Analysis ◽  
Significant Change ◽  
Clinically Significant ◽  
The Impact

Objective Heart rate variability (HRV) evaluates small beat-to-beat time interval (BBI) differences produced by the heart and suggested as a marker of the autonomic nervous system. Artifact produced by movement with wrist worn devices can significantly impact the validity of HRV analysis. The objective of this study was to determine the impact of small errors in BBI selection on HRV analysis and produce a foundation for future research in mental health wearable technology.Methods This was a sub-analysis from a prospective observational clinical trial registered with clinicaltrials.gov (NCT03030924). A cohort of 10 subject’s HRV tracings from a wearable wrist monitor without any artifact were manipulated by the study team to represent the most common forms of artifact encountered.Results Root mean square of successive differences stayed below a clinically significant change when up to 5 beats were selected at the wrong time interval and up to 36% of BBIs was removed. Standard deviation of next normal intervals stayed below a clinically significant change when up to 3 beats were selected at the wrong time interval and up to 36% of BBIs were removed. High frequency HRV shows significant changes when more than 2 beats were selected at the wrong time interval and any BBIs were removed.Conclusion Time domain HRV metrics appear to be more robust to artifact compared to frequency domains. Investigators examining wearable technology for mental health should be aware of these values for future analysis of HRV studies to improve data quality.

Investigating the experience of individuals with comorbid posttraumatic stress disorder and substance misuse attending a Seeking Safety group

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jac Neirin Airdrie ◽  
Alexandra Lievesley ◽  
Emma Griffith
Keyword(s):  
Mental Health ◽  
Substance Misuse ◽  
Stress Disorder ◽  
Small Sample ◽  
Post Traumatic Stress ◽  
Content Type ◽  
Clinically Significant Change ◽  
Seeking Safety ◽  
Significant Change ◽  
Clinically Significant

Purpose There is no specific recommended treatment for the co-morbid presentation of post-traumatic stress disorder (PTSD) and substance use disorder in the United Kingdom (UK). Seeking Safety (SS), a group-based treatment that targets symptoms of both disorder, has emerging evidence in the USA but lacks evidence from UK-based samples. The purpose of this study was to explore UK service users’ experience of attending SS and evaluate its impact on mental health symptomology and substance misuse. Design/methodology/approach A mixed method approach was used to evaluate the acceptability of SS for a small sample (n = 7) of adult users of a substance misuse service in the UK. Thematic analysis was used to explore their experiences, derived from individual semi-structured interviews. The authors also calculated the number of participants who achieved reliable and/or clinically significant change in mental health symptomology and substance misuse from data routinely collected by the service. Findings Seven overarching themes emerged: strengthening the foundations of the self, the evocation and management of emotions, safety and validation provided relationally, readiness and commitment, content and delivery, Seeking Safety is Not an Island and ending. Most participants with data available both before and after the group made reliable (three out of four) and clinically significant (two out of three) change for depression and anxiety symptomology; however, this was less evident for PTSD symptomology with two out of three making reliable change and one out of three making clinically significant change. Originality/value To the best of the authors’ knowledge, this was the first study exploring the experiences of UK attendees of a SS group as an approach to treating comorbid PTSD and substance misuse.

Assessing Reliable and Clinically Significant Change on Health of the Nation Outcome Scales: Method for Displaying Longitudinal Data

2005 ◽  
Vol 39 (8) ◽  
pp. 719-724 ◽  
Author(s):  
Alberto Parabiaghi ◽  
Angelo Barbato ◽  
Barbara D'avanzo ◽  
Arcadio Erlicher ◽  
Antonio Lora
Keyword(s):  
Clinical Improvement ◽  
Normative Data ◽  
Community Mental Health Services ◽  
Routine Data ◽  
Clinically Significant Change ◽  
Real Change ◽  
Significant Change ◽  
Clinically Significant ◽  
Routine Data Collection

Objective: Many authors recommended that reliable and clinically significant change (RCSC) should be calculated when reporting results of interventions. To test the reliability of the Health of the Nation Outcome Scales (HoNOS) in identifying RCSC, we applied the Jacobson and Truax model to two HoNOS assessments in a large group of people evaluated in 10 community mental health services in Lombardy, Italy, in 2000. Method: The HoNOS was administered to 9817 patients; of these, 4759 (48%) were re-assessed. Reliable change (RC) was calculated using Cronbach's alpha ( α), as a parameter of the reliability of the measure. Clinical significance cut-offs were calculated using a classification of severity based on HoNOS items. Results: In the whole sample, the clinical improvement cut-off was 11 and the remission cut-off was 5. Considering the severe patients, the clinical improvement cut-off was 12. The RC index calculated on the whole group and on the subgroup of severe patients indicated that eight-point and seven-point changes, respectively, were needed to be confident that a real change had occurred. Longitudinal changes were depicted on two-dimensional graphs as examples of reporting RCSC on HoNOS total scores in a routine data collection: 91.6% of the whole sample (4361) was stable, 5.6% (269) improved and 1.8% (129) worsened. Conclusion: Our study proposes a methodological framework for computing RCSC normative data on a widely used outcome scale and for identifying different degrees of clinical change.

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