Measuring Recovery Related Outcomes
A Psychometric Investigation of the Recovery Markers Inventory
Bibliographic Data
| ID | 8908652 |
|---|---|
| Authors | Kate DeRoche Lusczakoski (corresponding author), P Antonio Olmos‐Gallo (University of Denver), P Antonio Olmos-Gallo, Christopher J McKinney (Mental Health Center of Denver), Roy Starks (Mental Health Center of Denver), Steve Huff (Mental Health Center of Denver) |
| Year | 2014 |
| Volume | 50 |
| Issue | 8 |
| Pages | 896-902 |
| Publication date | 2014-05-17 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Community Mental Health Journal (JOURNAL) |
| Journal identifiers | ISSN: 0010-3853 • E-ISSN: 1573-2789 |
| Publisher | Springer Science+Business Media (PUBLISHER • DE) |
| DOI | 10.1007/s10597-014-9728-5 |
| PMID | 24838373 |
| PMCID | PMC4220018 |
| OpenAlex | W2009136271 |
| Language | EN |
| Citations received | 1 |
| References cited | 25 |
The concept of recovery can be operationalized from either the point of view of the consumer or from the perspective of the provider of services. The Recovery Markers Inventory (RMI) was created to assess recovery-related factors (i.e., actions/events associated with consumer's recovery) from the provider's perspective. Evidence, which established the psychometric properties of the RMI, was obtained through the use of: (a) construct validity (i.e., confirmatory factor analysis and Rasch principal components analysis of residuals); (b) concurrent validity (i.e., the calculation of Pearson correlations between the RMI and other recovery-oriented instruments); and (c) reliability (i.e., Rasch Partial Credit models). Evidence presented in this article shows that the RMI scale is unidimensional, has an adequate level of correlation, and acceptable reliability. The current analysis provides evidence to support the RMI as a valid, reliable measure of recovery-related factors, which can complement consumer based instruments in the assessment of changes in recovery
Concurrent validity · Confirmatory factor analysis · Construct validity · Developmental psychology · Item response theory · Machine learning · Operationalization · Perspective (graphical · Polytomous Rasch model · Psychometrics · Rasch model · Reliability (semiconductor · Scale (ratio · Structural equation modeling · Validity · Applied Psychology · Artificial Intelligence · Clinical Psychology · Computer Science · Geriatric Care and Nursing Homes · Mental Health and Patient Involvement · Patient Satisfaction in Healthcare · Psychology
Applying the Rasch Model
An analysis of the definitions and elements of recovery
A Brief Mental Health Outcome Scale
Recovery from versus recovery in serious mental illness
Cutoff criteria for fit indexes in covariance structure analysis
Hierarchical Linear Models
Power analysis and determination of sample size for covariance structure modeling.
Hierarchical linear models
Structural Equations with Latent Variables
Applying the Rasch Model
Implementing Recovery Oriented Evidence Based Programs
Statewide treatment outcome assessment in Colorado
The Camberwell Assessment of Need and Behaviour and Symptom Identification Scale as Routine Outcome Measures in a Psychiatric Disability Rehabilitation and Support Service
Seven Key Strategies that Work Together to Create Recovery Based Transformation
Psychometric Properties of an Assessment for Mental Health Recovery Programs
Further Validation of the Psycho-Social Well-Being Scale (PSWS) with Community Clients
In search of how people change
Significance tests and goodness of fit in the analysis of covariance structures
Comparative fit indexes in structural models
| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2025 - 2025 (1) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 1 |