Information

Can General Assessment of Functioning (GAF) be used to measure recovery etc. from all mental health problems?

Can General Assessment of Functioning (GAF) be used to measure recovery etc. from all mental health problems?


We are searching data for your request:

Forums and discussions:
Manuals and reference books:
Data from registers:
Wait the end of the search in all databases.
Upon completion, a link will appear to access the found materials.

Can General Assessment of Functioning (GAF) be used to measure recovery etc. from all mental health problems?

I know it's used with 'schizophrenia', but what about things like personality disorders, Dissociative Identity Disorder, etc.?


Yes, the General Assessment of Functioning (GAF) score can be used for all psychiatric disorders.

The GAF is not commonly used now as the DSM V has opted for the WHODAS 2.0 instead of GAF. There were fundamental problems with GAF including poor reliability with people who were less trained, cross-cultural variations and symptom severity tended to influence symptom scoring instead of functional impairment (Gold, 2014). The DSM V also commented on their concerns -

We do not believe that a single score from a global assessment, such as the GAF, conveys information to adequately assess each of these components, which are likely to vary independently over time. Further, we are concerned about evidence that the GAF requires specific training for proper use, and that good reliability and prediction of outcomes in routine clinical practice may depend on such training (APA, 2013).

References:

American Psychiatric Association. (2013). Insurance Implications of DSM 5. In Diagnostic and statistical manual of mental disorders (5th ed.).

Gold, L. H. (2014). DSM-5 and the Assessment of Functioning: The World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0). Journal of the American Academy of Psychiatry and the Law Online, 42(2), 173-181.


Conclusions

This study showed that the great majority of a large, heterogeneous group of service users with psychosis across several clinical units reported that personal recovery was important for them, regardless of age, ethnicity, symptomatology, functioning, community treatment order status, and time in mental health care. This finding has implications for clinical practice, providing empirical evidence that recovery-oriented treatments are relevant for most service users with psychosis in various mental health services. Recovery-oriented treatments such as IMR, and related themes, such as help for coping with stress and illness and having a plan for early detection and prevention of relapse, appeared to help people with psychosis feel supported by clinicians in their personal recovery process. Specific attention should be given to service users with high levels of general symptoms and depression, because these service users experienced less support for personal recovery, even though personal recovery was equally important for them.

This study was funded by grant 2015106 from the South-Eastern Norway Regional Health Authority (Helse Sør-Øst). Dr. Slade acknowledges support from the Center for Mental Health and Substance Abuse, University of South-Eastern Norway, and the Nottingham Biomedical Research Centre, National Institute for Health Research.

Dr. Slade acknowledges support from the Center for Mental Health and Substance Abuse, University of South-Eastern Norway, and the Nottingham Biomedical Research Centre, National Institute for Health Research.

1 Anthony WA : Recovery from mental illness: the guiding vision of the mental health service system in the 1990s . Psychosoc Rehabil J 1993 16:11–23Crossref , Google Scholar

2 Slade M, Amering M, Oades L : Recovery: an international perspective . Epidemiol Psichiatr Soc 2008 17:128–137Crossref, Medline , Google Scholar

3 Resnick SG, Fontana A, Lehman AF, et al. : An empirical conceptualization of the recovery orientation . Schizophr Res 2005 75:119–128Crossref, Medline , Google Scholar

4 Leamy M, Bird V, Le Boutillier C, et al. : Conceptual framework for personal recovery in mental health: systematic review and narrative synthesis . Br J Psychiatry 2011 199:445–452. Crossref, Medline , Google Scholar

5 Van Eck RM, Burger TJ, Vellinga A, et al. : The relationship between clinical and personal recovery in patients with schizophrenia spectrum disorders: a systematic review and meta-analysis . Schizophr Bull 2018 44:631–642. Crossref, Medline , Google Scholar

6 Chan RCH, Mak WWS, Chio FHN, et al. : Flourishing with psychosis: a prospective examination on the interactions between clinical, functional, and personal recovery processes on well-being among individuals with schizophrenia spectrum disorders . Schizophr Bull 2018 44:778–786. Crossref, Medline , Google Scholar

7 Rosenheck R, Stroup S, Keefe RS, et al. : Measuring outcome priorities and preferences in people with schizophrenia . Br J Psychiatry 2005 187:529–536. Crossref, Medline , Google Scholar

8 Maslow AH : A theory of human motivation . Psychol Rev 1943 50:370–396Crossref , Google Scholar

9 Henwood BF, Derejko KS, Couture J, et al. : Maslow and mental health recovery: a comparative study of homeless programs for adults with serious mental illness . Adm Policy Ment Health Ment Health Serv Res 2015 42:220–228. Crossref, Medline , Google Scholar

10 Clarke S, Oades LG, Crowe TP : Recovery in mental health: a movement towards well-being and meaning in contrast to an avoidance of symptoms . Psychiatr Rehabil J 2012 35:297–304. Crossref, Medline , Google Scholar

11 Lofthus AM, Westerlund H, Bjørgen D, et al. : Recovery concept in a Norwegian setting to be examined by the assertive community treatment model and mixed methods . Int J Ment Health Nurs 2018 27:147–157. Crossref, Medline , Google Scholar

12 van Weeghel J, van Zelst C, Boertien D, et al. : Conceptualizations, assessments, and implications of personal recovery in mental illness: a scoping review of systematic reviews and meta-analyses . Psychiatr Rehabil J 2019 42:169–181. Crossref, Medline , Google Scholar

13 Bird V, Leamy M, Tew J, et al. : Fit for purpose? Validation of a conceptual framework for personal recovery with current mental health consumers . Aust N Z J Psychiatry 2014 48:644–653. Crossref, Medline , Google Scholar

14 Stuart SR, Tansey L, Quayle E : What we talk about when we talk about recovery: a systematic review and best-fit framework synthesis of qualitative literature . J Ment Health 2017 26:291–304. Crossref, Medline , Google Scholar

15 Schrank B, Slade M : Recovery in psychiatry . BJPsych Bull 2007 31:321–325 Google Scholar

16 Slade M, Amering M, Farkas M, et al. : Uses and abuses of recovery: implementing recovery-oriented practices in mental health systems . World Psychiatry 2014 13:12–20. Crossref, Medline , Google Scholar

17 McGuire AB, Kukla M, Green A, et al. : Illness Management and Recovery: a review of the literature . Psychiatr Serv 2014 65:171–179. Link , Google Scholar

18 Egeland KM, Ruud T, Ogden T, et al. : How to implement Illness Management and Recovery (IMR) in mental health service settings: evaluation of the implementation strategy . Int J Ment Health Syst 2017 11:13 Crossref, Medline , Google Scholar

19 Färdig R, Lewander T, Melin L, et al. : A randomized controlled trial of the illness management and recovery program for persons with schizophrenia . Psychiatr Serv 2011 62:606–612. Link , Google Scholar

20 Le Boutillier C, Leamy M, Bird VJ, et al. : What does recovery mean in practice? A qualitative analysis of international recovery-oriented practice guidance . Psychiatr Serv 2011 62:1470–1476. Link , Google Scholar

21 The ICD-10 Classification of Mental and Behavioral Disorders: Clinical Descriptions and Diagnostic Guidelines . Geneva, World Health Organization, 1992 Google Scholar

22 Williams J, Leamy M, Bird V, et al. : Development and evaluation of the INSPIRE Measure of Staff Support for Personal Recovery . Soc Psychiatry Psychiatr Epidemiol 2015 50:777–786. Crossref, Medline , Google Scholar

23 Eisen SV, Normand S-L, Belanger AJ, et al. : The revised Behavior and Symptom Identification Scale (BASIS-R): reliability and validity . Med Care 2004 42:1230–1241. Crossref, Medline , Google Scholar

24 Cameron IM, Cunningham L, Crawford JR, et al. : Psychometric properties of the BASIS-24 (Behaviour and Symptom Identification Scale–Revised) mental health outcome measure . Int J Psychiatry Clin Pract 2007 11:36–43. Crossref, Medline , Google Scholar

25 BASIS-24 Instruction Guide . Belmont, MA, McLean Hospital, 2006 Google Scholar

26 Priebe S, Huxley P, Knight S, et al. : Application and results of the Manchester Short Assessment of Quality of Life (MANSA) . Int J Soc Psychiatry 1999 45:7–12. Crossref, Medline , Google Scholar

27 Guy W : ECDEU Assessment Manual for Psychopharmacology . Rockville, MD, US Department of Health, Education, and Welfare, Public Health Service. Alcohol, Drug Abuse, and Mental Health Administration, 1976 Google Scholar

28 Busner J, Targum SD : The Clinical Global Impressions Scale: applying a research tool in clinical practice . Psychiatry 2007 4:28–37. Medline , Google Scholar

29 Diagnostic and Statistical Manual of Mental Disorders (DSM-5) . Arlington, VA, American Psychiatric Association Publishing, 2013 Google Scholar

30 Pedersen G, Hagtvet KA, Karterud S : Generalizability studies of the Global Assessment of Functioning–split version . Compr Psychiatry 2007 48:88–94. Crossref, Medline , Google Scholar

31 Thomas EC, Despeaux KE, Drapalski AL, et al. : Person-oriented recovery of individuals with serious mental illnesses: a review and meta-analysis of longitudinal findings . Psychiatr Serv 2018 69:259–267. Link , Google Scholar

32 Priebe S, Reininghaus U, McCabe R, et al. : Factors influencing subjective quality of life in patients with schizophrenia and other mental disorders: a pooled analysis . Schizophr Res 2010 121:251–258. Crossref, Medline , Google Scholar

33 Clausen H, Landheim A, Odden S, et al. : Associations between quality of life and functioning in an assertive community treatment population . Psychiatr Serv 2015 66:1249–1252. Link , Google Scholar


Deegan PE. Recovey: the lived experience of rehabilitation. Psychosoc Rehabil J. 198811:11–9.

Onken SJ, Craig CM, Ridgway P, Ralph RO, Cook JA. An analysis of the definitions and elements of recovery: a review of the literature. Psychiatr Rehabil J. 200731(1):9–22.

Anthony WA. Recovery from mental illness: the guiding vision of the mental health service system in the 1990s. Psychosoc Rehabil J. 199316(4):11–23. http://doi.apa.org/getdoi.cfm?doi=10.1037/h0095655.

Deegan P. Recovery as a journey of the heart. Psychiatr Rehabil J. 199619(3):91–7. http://doi.apa.org/getdoi.cfm?doi=10.1037/h0101301.

Roe D, Chopra M, Wagner B, Katz G, Rudnick A. The emerging self in conceptualizing and treating mental illness. J Psychosoc Nurs Ment Health Serv. 200442(2):32–40. http://www.ncbi.nlm.nih.gov/pubmed/14982107.

Harding CM, Zahniser JH. Empirical correction of seven myths about schizophrenia with implications for treatment. Acta Psychiatr Scand. 1994384:140–6. http://www.ncbi.nlm.nih.gov/pubmed/7879636.

Wells EA, Hawkins JD, Catalano RF. Choosing drug use measures for treatment outcome studies. II. Timing baseline and follow-up measurement. Int J Addict. 198823(8):875–85. http://www.ncbi.nlm.nih.gov/pubmed/3066767.

Burgess P, Pirkis J, Coombs T, Rosen A. Review of recovery measures. Aust Ment Heal Outcomes Classif Netw. 20101:1–78.

Giffort D, Schmook A, Woody C, Vollendorf C, Gervain M. Recovery assessment scale. Health ID of M, editor. Chicago 1995.

Cavelti M, Beck E-M, Kvrgic S, Kossowsky J, Vauth R. The role of subjective illness beliefs and attitude toward recovery within the relationship of insight and depressive symptoms among people with schizophrenia spectrum disorders. J Clin Psychol. 201268(4):462–76. http://www.ncbi.nlm.nih.gov/pubmed/22331634.

Law H, Morrison A. Recovery from psychosis: a user informed review of self-report instruments for measuring recovery. J Ment. 201221(2):193–208. http://informahealthcare.com/doi/abs/10.3109/09638237.2012.670885.

Salzer MS, Brusilovskiy E. Advancing recovery science: reliability and validity properties of the recovery assessment scale. Psychiatr Serv. 201465(4):442–53. http://www.ncbi.nlm.nih.gov/pubmed/24487405.

McNaught M, Caputi P, Oades LG, Deane FP. Testing the validity of the Recovery Assessment Scale using an Australian sample. Aust N Z J Psychiatry. 200741(5):450–7.

Chiba R, Miyamoto Y, Kawakami N. Reliability and validity of the Japanese version of the Recovery Assessment Scale (RAS) for people with chronic mental illness: scale development. Int J Nurs Stud. 201047(3):314–22. doi:10.1016/j.ijnurstu.2009.07.006.

Mak WWS, Chan RCH, Yau SSW. Validation of the Recovery Assessment Scale for Chinese in recovery of mental illness in Hong Kong. Qual Life Res. 201625(5):1303–11. http://link.springer.com/10.1007/s11136-015-1157-6.

Young DKW, Ng PYN, Pan J, Fung T, Cheng D. Validity and reliability of Recovery Assessment Scale for cantonese speaking Chinese consumers with mental illness. Int J Ment Health Addict. 201615(1):198–208. http://link.springer.com/10.1007/s11469-016-9657-3.

Cavelti M, Wirtz M, Corrigan P, Vauth R. Recovery assessment scale: examining the factor structure of the German version (RAS-G) in people with schizophrenia spectrum disorders. Eur Psychiatry. 201741:60–7. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85007448269&doi=10.1016/j.eurpsy.2016.10.006&partnerID=40&md5=d4b5eec5ad2c7f90cd55852388320492.

Almeida Berberian A, Silva TR, Gadelha A, Villares CC, Martini LC, Bressan RA. Validação da Recovery Assessment Scale (RAS) no Brasil para avaliar a capacidade de superação das pessoas com esquizofrenia. J Bras Psiquiatr. 201766(1):1–8. http://www.scielo.br/pdf/jbpsiq/v66n1/0047-2085-jbpsiq-66-1-0001.pdf.

Agrest M, Druetta I. The concept of recovery: the importance of users’ perspective and their participation. Vertex. 201122(95):56–64. http://www.ncbi.nlm.nih.gov/pubmed/21505647.

Gabay PM. Recovery: a new paradigm for psychiatry. Vertex. 201122(100):454–61. http://www.ncbi.nlm.nih.gov/pubmed/22799147.

Congreso de la Nación. Ley Nacional de Salud Mental (National Mental Health Law). República Argentina: Boletín oficial 2010.

DSM-IV-TR. Diagnostic and statistical manual of mental disorders: DSM-IV-TR. Lake St. Louis: American Psychiatric Association 2000.

Mundfrom DJ, Shaw DG, Ke TL. Minimum sample size recommendations for conducting factor analyses minimum sample size recommendations for conducting factor analyses. Int J Test. 20095(2):159–68.

Corrigan PW, Giffort D, Rashid F, Leary M, Okeke I. Recovery as a psychological construct. Community Ment Health J. 199935(3):231–9. http://link.springer.com/10.1023/A:1018741302682.

Monteiro MF, Ornelas JH. Recovery Assessment Scale: testing validity with Portuguese community-based mental health organization users. Psychol Assess. 201628(3):e1–11.

IBM CORP. Ibm, SPSS statistics for windows. Armonk: IBM Corp 2013.

Arbuckle JL. Amos. Chicago: IBM SPSS 2014.

Kaiser HF. An index of factorial simplicity. Psychometrika. 197439(1):31–6. http://link.springer.com/10.1007/BF02291575.

Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model A Multidiscip J. 19996(1):1–55. http://www.tandfonline.com/doi/abs/10.1080/10705519909540118.

Browne MW, Cudeck R. Alternative ways of assessing model fit. Sociol Methods Res. 199221(2):230–58. http://journals.sagepub.com/doi/10.1177/0049124192021002005.

Fukui S, Shimizu Y, Rapp CA. A cross-cultural study of recovery for people with psychiatric disabilities between US and Japan. Community Ment Health J. 201248(6):804–12.

Jacobson N, Greenley D. What is recovery? A conceptual model and explication. Psychiatr Serv. 200152(4):482–5. http://www.ncbi.nlm.nih.gov/pubmed/11274493.

Kelly M, Gamble C. Exploring the concept of recovery in schizophrenia. J Psychiatr Ment Health Nurs. 200512(2):245–51. http://www.ncbi.nlm.nih.gov/pubmed/15788044.

Townsend W, Glasser N. Recovery: the heart and soul of treatment. Psychiatr Rehabil J. 200327(1):83–6. http://www.ncbi.nlm.nih.gov/pubmed/12967237.

Fallot RD. Spirituality and religion in psychiatric rehabilitation and recovery from mental illness. Int Rev Psychiatry. 200113(2):110–6. http://informahealthcare.com/doi/abs/10.1080/09540260120037344.

Russinova Z, Cash D. Personal perspectives about the meaning of religion and spirituality among persons with serious mental illnesses. Psychiatr Rehabil J. 200730(4):271–84. http://www.ncbi.nlm.nih.gov/pubmed/17458451.

Hancock N, Bundy A, Honey A, Helich S, Tamsett S. Measuring the later stages of the recovery journey: insights gained from clubhouse members. Community Ment Health J. 201349(3):323–30.

Udagawa K. 2007 Sekai seishin hoken kaigi in Hong kong sanka inshouki—toujisha no bunkakai de hanasareta koto [World Federation for Mental Health 2007 Hong Kong biennial congress participation memory—what was talked in the section meeting for the people with mental]. Psychiatr Ment Health Nurs. 200811(1):79–81.

Garcia-Preto N. Latino families: an overview. In: McGoldrick M, Giordano J, editors. Ethnicity and family therapy. New York: Guilford Press 2005. p. 141–224. http://psycnet.apa.org/psycinfo/2006-00844-011.

Andresen R, Oades L, Caputi P. The experience of recovery from schizophrenia: towards an empirically validated stage model. Aust N Z J Psychiatry. 200337(5):586–94. http://anp.sagepub.com/lookup/doi/10.1046/j.1440-1614.2003.01234.x.

Schauer C, Everett A, del Vecchio P, Anderson L. Promoting the value and practice of shared decision-making in mental health care. Psychiatr Rehabil J. 200731(1):54–61. http://www.ncbi.nlm.nih.gov/pubmed/17694716.

Atkinson M, Zibin S, Chuang H. Characterizing quality of life among patients with chronic mental illness: a critical examination of the self-report methodology. Am J Psychiatry. 1997154(1):99–105.

Fleury MJ, Grenier G, Bamvita JM. Predictive typology of subjective quality of life among participants with severe mental disorders after a five-year follow-up: a longitudinal two-step cluster analysis. Health Qual Life Outcomes. 201513(1):150. doi:10.1186/s12955-015-0346-x.

Brown MA, Velligan DI. Issues and developments related to assessing function in serious mental illness. Dialogues Clin Neurosci. 201618(2):135–44. http://www.ncbi.nlm.nih.gov/pubmed/27489453.

Roe D, Mashiach-Eizenberg M, Lysaker PH. The relation between objective and subjective domains of recovery among persons with schizophrenia-related disorders. Schizophr Res. 2011131(1–3):133–8. http://www.ncbi.nlm.nih.gov/pubmed/21669512.

Giusti L, Ussorio D, Tosone A, Di Venanzio C, Bianchini V, Necozione S, et al. Is personal recovery in schizophrenia predicted by low cognitive insight? Community Ment Health J. 201551(1):30–7. http://www.ncbi.nlm.nih.gov/pubmed/25064088.

Berry JW. Cross-cultural psychology: research and applications. Cambridge: Cambridge University Press 1992.


Medication Free Treatment: Characteristics, Justification and Outcome

In 2015 the Norwegian government, after initiative from user organizations, decided to implement medication free inpatient treatment units. The goal is to secure real options to medication for psychiatric illness, and to gather experiences with medication free options. Freedom of choice is a main concern.

The projects main aim is to study the outcome of medication free treatments of mental illness compared to treatment as usual, as well as characteristics of the treatment and the treatment population and why patients choose this treatment. Hereunder we aim to document who asks for these kinds of services and why, what kind of treatment they get, how they experience it, and how they respond to this kind of treatment. An important part will be to document whether the goal of increased freedom of choice between real treatment options is fulfilled.

  1. Does medication free treatment differ from treatment as usual? Are there any unique characteristics of the patient group who asks for this kind of treatment? What kind of treatment do they receive during their stay? How do they experience this treatment in comparison to treatment as usual? How is this in relation to the goals about increased freedom of choice? Does use of medication change during and/or after medication free treatment?
  2. Why do patients choose medication free treatment? What are their reasons? What experiences lead to this wish?
  3. What is the outcome of medication free treatment compared to treatment as usual?

Condition or disease Intervention/treatment
Mental Illness Behavioral: Medication free treatment Behavioral: Treatment as usual Myrvegen Behavioral: Treatment as usual Åråsen

Background In 2015 the Norwegian government, after initiative from user organizations, decided to implement medication free inpatient treatment units. The goal is to secure real options to medication for psychiatric illness, and to gather experiences with medication free options. Freedom of choice is a main concern. (Aksjon for medisinfrie tilbud) The local unit under study DPS døgn Moenga at Akershus University Hospital has been given the assignment of developing a medication free treatment unit. This is an inpatient treatment unit for voluntary, planned treatment. High suicidal risk, severe acting out, active drug abuse etc. is excluded. The treatment program is 8 weeks long.

Status of knowledge The project has been controversial, especially with reference to the status of knowledge. Critiques have stated that the knowledge base for treating serious psychiatric disorders without medication is lacking (Gundersen, 2016 Røssberg, 2016). Concerns are raised about whether it can be harmful (Røssberg, 2016), whether it is necessary (Røssberg, Andreassen, & Malt, 2016) and whether it creates unfortunate dividing lines within health care (Røssberg et al., 2016). National guidelines recommend considering/offering medication for bipolar disorders, deep depression and psychosis (Helsedirektoratet, 2009, 2012, 2013). On the other hand, the knowledge base for use of psychotropic drugs is also being questioned, especially regarding long term effects (Bentall, 2009 Forand & DeRubeis, 2013 Moncrieff, 2009 Sohler et al., 2016 Whitaker, 2010/2014 (no), 2016). Studies on medication are amongst others criticized for not taking withdrawal effect sufficiently into account (Bentall, 2009 Forand & DeRubeis, 2013 Moncrieff, 2009 Whitaker, 2010/2014 (no), 2016). A randomized controlled study by Wunderink, Nieboer, Wiersma, Sytema, and Nienhuis (2013) indicates a follow up period of at least 3 years is necessary to see the benefits of drug reduction regarding antipsychotics.

Summing up, one can argue that generally, a considerable research base point to psychosocial treatment methods having an important place in the treatment of most psychiatric problems (Lambert, 2013 Wampold, 2001 Wampold & Imel, 2015). The more specific questions regarding pure psychosocial treatment for serious disorders and long term effects of psychotropic drugs are at least disputable, and probably under-researched.

  1. Does medication free treatment differ from treatment as usual? Patient characteristics, treatment received, experience, medication use.
  2. Why do patients choose medication free treatment? What are their reasons? What experiences lead to this wish?
  3. What is the outcome of medication free treatment compared to treatment as usual? Hypotheses The treatment outcome of medication free treatment is not inferior to treatment as usual.

Patients in medication free treatment will use less medication. Medication withdrawal may affect outcome in the short run.

Project methodology The design of the study is a mixed methods, observational design within a naturalistic treatment setting using qualitative and quantitative methods to address the research questions.

Moenga consist of two units, the medication free unit and a regular unit, which will be included for comparison. In addition we include a treatment unit on a different location for comparison DPS Myrvegen. We aim for at least 200 n.

One complication is that this autumn it was decided that the units at Moenga shall move and reorganize sometime during 2018. This entail change of location, possible reorganizing of personnel and that the comparison unit at Moenga is joined with another inpatient unit at the new location. This may cause disruptions that can affect our results. We will study possible effects of this in our data, and may exclude parts of the gathered data and prolong the inclusion period.

We will collect survey data at start of treatment, weekly during treatment, at end of treatment (Work package 1), and at 6 months, 1 year, 2 years and 3 years follow up (work package 3). Register data will be collected 3 years back and 3 years follow up (work package 3). Patient interviews (work package 2) and personnel interviews (work package 4) are performed during spring 2018, the patient interviews near the end of the treatment stay. See measures for details.

Plan for data analyses Quantitative and qualitative analyses will be done according to the research questions. We will seek to compare the medication free unit and treatment as usual. Calculating propensity scores in the observational part of the study will be considered, to balance comparison groups (Austin, 2011).

Statistical power Exact power calculations are only possible in concrete, delimited statistical designs, and must necessarily be based on assumptions not always known before starting the study. In a design with 200 persons the total effect of one-way analysis of variance yield a statistical power of .80 for small to medium effect sizes. That is, the probability of detecting differences between groups will be .80 for effect sizes in the range .40 -.50. For pairwise comparisons between groups (with N=50), the probability of detecting effects in the range of Cohen's d >=. 40 will be about .80. In Cohen's pragmatic system, effect sizes with such magnitudes represent a "small to medium effect size". These estimations will also apply to change-scores between two points in time, given that the correlation between the two repeated measurements are r >= .5.

Work package 1: Inclusion of patients for quantitative measurements starts April 2018 with a 12 months inclusion period. This may be prolonged if necessary.

Work package 2: Patient interviews will be performed during spring 2018. Work package 3: Follow up measures and register data will be collected until spring 2022.

Work package 4: Personnel interviews will be performed during spring 2018. Analysis Qualitative analyses will be performed within end of 2018. Quantitative analyses will start January 2019 Publishing Publishing of the results in scientific papers will take place mainly in 2019-2023.

  1. "Medication free treatment: Does it differ from treatment as usual?" This article will address research question 1 and include qualitative data, Collaborate, BMQ, Inspire, CSQ-8, WAI, treatment received, use of medication and background data.
  2. "Medication free treatment: Why?" This article will address research question 2 (Why do patients choose medication free treatment) and include qualitative data.
  3. "Medication free treatment: Does it work?" This article will address the research questions and will include the outcome measures OQ-45, AII, Quality of life, HoNOs, GAF, CGI, drug use, diagnoses and register data. We will also look for correlations between use of medication and outcome, and therefore include measures of medication use.

Research group PhD Kristin S. Heiervang, head of the research group Quality and implementation in Mental Health Services at Akershus university hospital, is project manager (principal investigator) for the project.

Anders S. Wenneberg, specialist in clinical psychology, is the leader of the inpatient treatment facility. Wenneberg is also the project manager of the "Medication Free Treatment" at Akershus University Hospital, Moenga.

Ole André Solbakken is associate professor of clinical psychology and head of section at the Department of Psychology, University of Oslo.

Odd Arne Tjersland is professor of clinical psychology at the Department of Psychology, University of Oslo.

Jon T. Monsen is professor of clinical psychology at the Department of Psychology, University of Oslo.

Allan Abbass is professor, psychiatrist, and founding Director of the Centre for Emotions and Health at Dalhousie University in Halifax, Canada.

Kari Standal will be the PhD candidate. She is a psychologist at Akershus university hospital, specialized in adult treatment and psychotherapy (group treatment and affect consciousness).

Jill Arild, board member of "Mental Helse" and leader of the action group for medication free treatment is user represantive in the project.

Astrid Ringen Martinsen is a psychology student who will write her main thesis on the qualitative patient data.

Ingrid Engeseth Brakstad is a psychology student who will write her main thesis on the qualitative personnel data.

Layout table for study information
Study Type : Observational [Patient Registry]
Estimated Enrollment : 200 participants
Observational Model: Other
Time Perspective: Prospective
Target Follow-Up Duration: 3 Years
Official Title: Medication Free Treatment: Characteristics, Justification and Outcome
Actual Study Start Date : May 14, 2018
Estimated Primary Completion Date : May 14, 2020
Estimated Study Completion Date : April 1, 2023

Resource links provided by the National Library of Medicine

Key point #2: There is a Need for Functional Performance Testing (FPT)

Presently used methods of assessing function in clinical practice are incomplete. Much like the difficulty in, and complexity of, measuring function, there is the obstacle of defining function and the definitive assessment process for it.

FPT defined

‘Testing’ is defined as using a set of problems to assess abilities. Therefore, we have previously termed FPT to mean using a set of tests to determine performance abilities or functional limitations. 45 In other words, FPT is not impairment or PPM testing ( Table 1 ). In simplified terms, impairments and PPM are typically more isolated findings while function is a more global concept incorporating the entire extremity, body, or person.

Table 1

Muscle performance (primarily includes manual muscle testing)

ROM (including muscle length)

Joint integrity and mobility

Peripheral nerve integrity

Gait, locomotion, and balance

Aerobic endurance testing in multiple planes of movement

Balance/proprioceptive testing in multiple planes of movement

Softball throw for distance

Speed, agility, and quickness testing

Note: PPMs = physical performance measures ROM = range-of-motion.

Pain perception and movement, both integral elements in assessment of manual therapy interventions, are mediated by contextual elements such as cognitive, emotional, and social factors. 45 Consequently, an expanded conceptual model of patient management and assessment at a functional, rather than impairment or PPM level, is necessary to fully evaluate all the elements associated with functioning. 45 This expanded conceptual model (FPT), ventures to capture the multiple dimensions of function through clustered physical performance movements.

FPT can therefore be more complexly defined as using a variety of physical skills and tests to determine: (1) one’s ability to participate at the desired level in sport, occupation, and recreation or to return to participation in a safe and timely manner without functional limitations and (2) one’s ability to move through up to three planes of movement as determined via non-traditional testing that provides qualitative and quantitative information related to specialized motions involved in sport, exercise, and occupations. 45 The clinician should understand that FPT is an aspect of everyday life, whether for the elite athlete, the industrial worker, or the homemaker. The commonality among all groups is that some aspect of performance is needed for each individual to be successful in performing their respective skills or duties. 45

Compared to clinical assessment with special tests, assessments with FPTs test the ability of the person to put together a series of movements (rather than isolated single joint and planar movements) to safely and efficiently complete a task. In other words, assessment at the functional level assesses function of the person rather than function of the part of the person. 24 For example, the fact that a person has full hip, knee, and ankle ROM does not ensure successful return to basketball. If this same person has normal joint play, full strength, and full neuromuscular control and additionally is able to achieve an excellent score on jumping/hopping and anaerobic endurance tests without adverse symptoms, there should be much more confidence about the prospect of a safe return. Many FPTs closely approximate the activities that people need or wish to do.

We recommend the expansion of these recommendations to state that measurement of an individual’s ability to properly function should be along a continuum, and should include multiple measures ( Figs. 1 and ​ and2 2 and Table 2 ). To achieve this objective, the measurement of function demands careful individual consideration and investigations of the interactions among various examination methods.

Conceptual model of comprehensive assessment of function.

Proposed examination continuum. FPT =𠂯unctional performance testing.

Table 2

Self-report measures most indicative of dysfunction

Bio-psycho-social measures relevant to dysfunction

Self-report of activity rating scales (patient interpretation on specific requirements of their necessary activity level to return to previous level of function) 61

Clinician analysis of specific sport/occupation/activities of daily living with respect to requirements (specific type of movements, energy system involvement, etc.)

Anthropometric measurements (body mass index, girth and height measurements, etc.)

Static balance (bilateral and single-leg balance static assessment)

Dynamic posture (posture of individual as they perform movements required)

General movement patterns (walking, transfer movements, etc.)

Dynamic balance predominantly in one plane of movement without quality assessment (functional reach test, tandem walking, etc.)

Assessment of movement patterns the individual performs with their primary tasks (specific sport, occupational, etc. tasks)

Functional movement screen

Movement Impairment syndrome assessment

Single-leg inclined squat on total gym

Multiple joint involvement

Multiple muscle group involvement

Aerobic endurance testing

Star excursion balance test

Knee bending in 30 seconds

Single jump and hop testing in one plane of movement

Jump and hop testing in multiple planes of movement or requiring multiple jumps or hops

Single-leg crossover hop for distance

Hop testing after fatigue

Running-based anaerobic sprint test

Lower extremity functional test

Speed and agility testing

Sidearm medicine ball throw

Underkoffler softball throw for distance

Balance error scoring system

Functional throwing performance index

Multiple single-leg hop stabilization

Functional capacity evaluation

Firefighting �ility test’

Functional abilities test

Assessment forward and backward along the functional continuum ( Fig. 2 ) utilizing each parameter of function (impairment, performance measures, and self-report measures) as necessary

Note: ROM = range-of-motion PPM = physical performance measure 1RM = one repetition maximum BEAST90 =�ll-sport endurance and sprint test FPT =𠂯unctional performance testing.

Traditional thought regarding the examination process might suggest that the normal assessment ‘procedures’ progress from self-report measures to examination (including observation) followed by special testing (with use of clinical measures or other tests). FPT, if employed, would then be implemented at the very end stage of the rehabilitation process. It is our contention that the measurement of function requires assessment of combinations of these measures ( Fig. 1 ) throughout the rehabilitation process. Examination of a patient’s function requires assessment of the entire disablement model.

The conceptual model illustrated in Fig. 1 suggests this comprehensive approach to measuring function. It should also be pointed out that this conceptual model advocates multi-directional flow along the assessment continuum. There are levels of function assessment ( Table 2 ). Lower levels of function assessment can be implemented earlier in the examination process when warranted. In the above example, the use of functional movement and Rockport walk test could be utilized even prior to jumping/hopping and/or isokinetic testing in some dysfunctions. Functional movement could be utilized to screen for normal joint mobility in many early stage rehabilitation programs assuming safety. Additionally, the use of the deep squat assessment component of the Functional Movement Screen™ (Functional Movement Systems, Danville, VI, USA) 43 could be used to determine restricted mobility of the hip joint (impairment). Lack of sufficient hip mobility would not allow the patient to perform a proper deep squat. Performing this assessment early in the examination process would allow the clinician to complete the necessary impairment assessments in order to ascertain the reason(s) for improper deep squatting. Another example of multi-directional flow examination may have a patient perform the firefighting �ility test’ 52 (as long as not contraindicated), allowing the clinician to assess for potential restricted abilities, whether they exist at the PPM or impairment level. An unsuccessful attempt at a specific component of this test does not specifically uncover the limitation, but it can allow the clinician to converge on identifiable areas of interest (impaired joint mobility, decreased muscle performance, etc.). Use of higher levels of testing in this fashion can prove beneficial in determining the limiting factors of function in these patients. The following articles in this series plan to use an algorithmic approach to demonstrate such examples of the integration of the multiple types of testing that we suggest in the comprehensive examination conceptual model. The combination of all of these testing approaches measures the concept of function.


Discrepancy between experience and importance of recovery components in the symptomatic and recovery perceptions of people with severe mental disorders

Personal recovery has become an increasingly important approach in the care of people with severe mental disorders and consequently in the orientation of mental health services. The objective of this study was to assess the personal recovery process in people using mental health services, and to clarify the role of variables such as symptomatology, self-stigma, sociodemographic and treatment.

Methods

Standardised measures of personal recovery process, clinical recovery, and internalized stigma were completed by a sample of 312 participants in a Severe Mental Disorder program.

Results

Users valued most the recovery elements of: improving general health and wellness having professionals who care hope and sense of meaning in life. Significant discrepancies between perceived experience and relative importance assigned to each of the components of the REE were observed. Regression modeling (χ 2 = 6.72, p = .394 GFI = .99, SRMR = .03) identified how positive discrepancies were associated with a higher presence of recovery markers (β = .12, p = .05), which in turn were negatively related to the derived symptomatology index (β = −.33, p < .001). Furthermore, the relationship between clinical and personal recovery was mediated by internalized stigma.

Conclusions

An improvement in psychiatric services should be focused on recovery aspects that have the greatest discrepancy between importance and experience, in particular social roles, basic needs and hope. Personal and clinical recovery are correlated, but the relationship between them is mediated by internalized stigma, indicating the need for clinical interventions to target self-stigma.


Additional information

Competing interests

SB is a psychiatrist and has been Medical Affairs Manager for Janssen-Cilag Portugal since April 2010. AM is a consultant psychiatrist in Oxfordshire affiliated to the Social Psychiatry Group in the Oxford University Department of Psychiatry. VVD is a clinical neuropsychologist affiliated to Santa Maria's University Hospital. He is a consultant for Angelini Pharmaceutical Portugal, and has received educational grants from Lundbeck, Sanofi-Aventis, Janssen-Cilag and AstraZeneca. MLF is a full professor of Psychiatry and Head of the Department of Psychiatry at Santa Maria's University Hospital.

Authors' contributions

SB managed the literature search, and wrote the first draft of the manuscript. The data were analysed by SB, VVD, AM and MLF, who wrote the final draft of the manuscript. All authors contributed to and approved the final version of the manuscript.


Generalizability studies of the Global Assessment of Functioning–Split version

The study aimed to use the Generalizability Theory to investigate the reliability and precision of the split version of the Global Assessment of Functioning (GAF).

Materials

Six case vignettes were assessed by 2 samples one by 19 experienced and independent raters and another by 58 experienced raters from 8 different day-treatment units, evaluating both symptom and function scores of GAF.

Methods

Generalizability studies were conducted to disentangle relevant variance components accounting for error variance in GAF scores. Furthermore, decision studies were conducted to estimate the reliability of different measurement designs, as well as precision in terms of error tolerance ratio.

Results

Both symptom and function scores of GAF were found to be highly generalizable, and a measurement design of 2 raters per subject was found to be most efficient with respect to reliability, precision, and use of resources.

Conclusion

Both symptom and function scores of GAF seem highly consistent across experienced raters.


Methods

Setting

In the UK a veteran is defined as an individual who has completed at least 1 day of military service and is no longer employed by the Armed Forces.15 This was a naturalistic study of individuals who had enrolled on a 6-week inpatient intensive treatment programme (ITP) for PTSD offered by Combat Stress to UK veterans between late 2012 and early 2014. The ITP is a residential programme and consists of a mixture of individual TF-CBT and groups scheduled on weekdays from 9:00 to 17:00 that are standardised and manualised to ensure a homogenous treatment experience for participants. Individuals were assigned to a closed group of eight and are offered a minimum of 15 individual TF-CBT therapy sessions (lasting 90 min) and 55 group sessions each lasting 1 h. Individual TF-CBT was offered by psychologists and CBT therapists and focused on working on trauma memories connected to military service. Group sessions were facilitated by a multidisciplinary team consisting of psychologists, CBT therapists, occupational therapists and art therapists. Group sessions included psychoeducational groups (eg, understanding PTSD, CBT education, understanding medication, exploring the links between PTSD and memory, sleep hygiene and relaxation techniques) and symptom management groups (eg, managing anxiety, managing anger, behavioural activation for depression and mindfulness groups). In addition, occupational therapists facilitated a number of groups aimed at supporting well-being (eg, groups to support resilience, develop goal planning skills and practical groups to encourage individuals to engage in meaningful activities) and six art therapy groups were offered (once a week throughout the ITP). On a typical day participants attended two group sessions that lasted an hour each and were invited to practice newly acquired skills in between sessions. Meal times were fixed throughout the day. Over the course of the week participants attended three 90 min individual TF-CBT sessions.

Participants

When individuals are referred into Combat Stress they receive an initial assessment which includes a range of health measures. Individuals who screen positive for PTSD are then given a referral for an ITP assessment. Prior to admission for the ITP, individuals are assessed separately by a psychiatrist and a psychologist to explore diagnosis, comorbidity and suitability for the programme. Inclusion criteria included having a primary diagnosis of PTSD, exposure to two or more traumatic events connected to an individuals’ military career and being a veteran of the UK military. In addition, where participants were on psychiatric medications, these had to be stable prior to enrolling on the ITP and participants had to remain on the same dose and medication for the duration of the ITP. Exclusion criteria included being actively suicidal, being actively dependent on alcohol, having a diagnosis of a personality disorder, being actively psychotic or whether there was evidence of a brain injury that impacts significantly on cognitive functioning. This did not exclude individuals with mild or moderate brain injuries. When veterans met exclusion criteria, where possible they were given appropriate support and then re-assessed at a later date. For example, this included referrals to substance misuse services or psychiatric support for active symptoms of psychosis. In addition, individuals were required to not drink alcohol or use illicit drugs during the 6-week programme.

A total of 246 participants enrolled on the ITP between 2012 and early 2014. Individuals had to stay for at least 5 weeks of the 6-week programme and attend a minimum of 15 individual TF-CBT sessions to be considered a completer of the programme. Fifteen (6%) participants were classified as non-completers. Of these, five individuals had been asked to leave the ITP because they consumed alcohol during their stay, six individuals were deemed unsuitable for therapy by the clinical team, three individuals had to leave early because of complicated physical health difficulties that arose during their admission, and one individual had to leave early because a family member became unwell.

A total of 231 individuals completed the ITP and 186 (81%) of these were successfully followed up at 6 months. Of the 45 non-responders (19%), 22 were contacted for a non-responder study, one had died (of natural causes), eight had withdrawn their consent to be contacted for follow-up and it was not possible to contact the remaining 14. This means that 49% of our non-responders were contacted for the non-responder study. This increased to 65% when individuals who had died or refused further contact were removed. An overview of the sample is provided in figure 1.

Outcome measures

Outcome measures were collected at admission, discharge, 6 weeks and at 6 months follow-up. At each of these time points the treating clinician completed a ‘clinician’ pack of measures and participants were asked to complete a ‘veterans’ pack of measures. Our primary outcomes for this study were measures of mental health difficulties and our secondary outcomes were measures of functional impairment.

Primary outcome measures

The clinician completed the PTSD Symptom Scale Interview (PSS-I). The PSS-I is a 17-item semistructured interview that assesses the presence and severity of diagnostic symptoms of PTSD using the Diagnostic and Statistical Manual Fourth Edition (DSM-IV).16 , 17 In addition, the participants were asked to complete a number of measures. These included the Revised Impact of Events Scale (IES-R) which measures symptoms of PTSD with 22-items.18 To explore other mental health difficulties participants completed the Patient Health Questionnaire (PHQ-9) which explores symptoms of depression19 , 20 the Generalised Anxiety Disorder Assessment (GAD-7) which explores symptoms of anxiety21 and the Dimensions of Anger Reactions (DAR-5) to measure symptoms of anger.22

Secondary outcome measures

Clinicians completed the Global Assessment of Function (GAF). This is a numeric scale from 1 to 100 that is used to subjectively rate social, occupational and psychological functioning. The GAF is described in the DSM-IV.17 Clinicians also completed the Health of the Nation Outcome Scales (HONOS) this has 12 items and measures behaviours, impairment, symptoms and social functioning.23 Participants completed the Work and Social Adjustment Scale (WSAS). The WSAS is a self-report questionnaire that measures an individuals’ perspective on their level of impaired functioning.24

Demographic characteristics

Demographic details were collected on all participants, with additional information about service (Royal Navy, Army or RAF), last rank (Officer or other rank), year they left, number of deployments they went on and how they left the military.

Non-responder study measures

Those who failed to respond at 6 months were contacted and invited to participate in a non-responder study. Researchers attempted to telephone non-responders three times to ask them to complete a number of health measures. These were the PSS-I to measure symptoms of PTSD and the PHQ-9 and GAD-7 to measure comorbid symptoms of depression and anxiety respectively.

Analysis

The first stage was to conduct exploratory analyses to assess whether potential biases were presented. To do this we used Mann-Whitney U tests to explore whether differences in baseline health scores were present between individuals who completed the ITP and individuals who did not. Following this we used χ 2 tests to explore sociodemographic differences between responders and non-responders. As detailed above, a non-responder study was conducted which collected health measures from individuals we were able to contact. Mann-Whitney U tests were used to compare the health scores between responders and non-responders.

The final stage of the analysis was to explore our primary and secondary outcomes following treatment. Random slopes non-linear growth models were fitted to explore the longitudinal health and functional impairment data collected at admission, discharge, 6 weeks and 6 months follow-up.25 These analyses were repeated and adjusted for age group (<35, 35–44 and >45) and employment status. This is because these were found to improve the fit of the models using likelihood ratio tests. The models fitted were non-linear and used a fixed coefficient of time squared. Analyses were conducted using Stata V.13 (StataCorp, College Station, Texas, USA).


Axis V – Global Assessment of Functioning Scale (GAF), further evaluation of the self-report version

The study aimed to examine agreement between patients' and professional staff members' ratings on the Global Assessment of Functioning scale (GAF).

A total of 191 young adult psychiatric outpatients were included in a naturalistic, longitudinal study. Axis I and axis II disorders were assessed by means of the Structured Clinical Interview for DSM-IV. Before and after treatment, patients and trained staff members did a GAF rating. Agreement between GAF ratings was analyzed using the intra-class correlation coefficient (ICC).

The overall intra-class correlation coefficients before and after treatment were 0.65 and 0.86, respectively. Agreement in different axis I diagnostic groups varied, but was generally lower before treatment as compared to after treatment (0.50–0.66 and 0.78–0.90, respectively). Excessive psychiatric co-morbidity was associated with the lowest inter-rater reliability. Agreement, with respect to change in GAF scores during treatment, was good to excellent in all groups.

Overall, agreement between patients' and professionals' ratings on the GAF scale was good before and excellent after treatment. The results support the usefulness of the self-report GAF instrument for measuring outcome in psychiatric care. However, more research is needed about the difficulties in rating severely disordered patients.


Deegan PE. Recovey: the lived experience of rehabilitation. Psychosoc Rehabil J. 198811:11–9.

Onken SJ, Craig CM, Ridgway P, Ralph RO, Cook JA. An analysis of the definitions and elements of recovery: a review of the literature. Psychiatr Rehabil J. 200731(1):9–22.

Anthony WA. Recovery from mental illness: the guiding vision of the mental health service system in the 1990s. Psychosoc Rehabil J. 199316(4):11–23. http://doi.apa.org/getdoi.cfm?doi=10.1037/h0095655.

Deegan P. Recovery as a journey of the heart. Psychiatr Rehabil J. 199619(3):91–7. http://doi.apa.org/getdoi.cfm?doi=10.1037/h0101301.

Roe D, Chopra M, Wagner B, Katz G, Rudnick A. The emerging self in conceptualizing and treating mental illness. J Psychosoc Nurs Ment Health Serv. 200442(2):32–40. http://www.ncbi.nlm.nih.gov/pubmed/14982107.

Harding CM, Zahniser JH. Empirical correction of seven myths about schizophrenia with implications for treatment. Acta Psychiatr Scand. 1994384:140–6. http://www.ncbi.nlm.nih.gov/pubmed/7879636.

Wells EA, Hawkins JD, Catalano RF. Choosing drug use measures for treatment outcome studies. II. Timing baseline and follow-up measurement. Int J Addict. 198823(8):875–85. http://www.ncbi.nlm.nih.gov/pubmed/3066767.

Burgess P, Pirkis J, Coombs T, Rosen A. Review of recovery measures. Aust Ment Heal Outcomes Classif Netw. 20101:1–78.

Giffort D, Schmook A, Woody C, Vollendorf C, Gervain M. Recovery assessment scale. Health ID of M, editor. Chicago 1995.

Cavelti M, Beck E-M, Kvrgic S, Kossowsky J, Vauth R. The role of subjective illness beliefs and attitude toward recovery within the relationship of insight and depressive symptoms among people with schizophrenia spectrum disorders. J Clin Psychol. 201268(4):462–76. http://www.ncbi.nlm.nih.gov/pubmed/22331634.

Law H, Morrison A. Recovery from psychosis: a user informed review of self-report instruments for measuring recovery. J Ment. 201221(2):193–208. http://informahealthcare.com/doi/abs/10.3109/09638237.2012.670885.

Salzer MS, Brusilovskiy E. Advancing recovery science: reliability and validity properties of the recovery assessment scale. Psychiatr Serv. 201465(4):442–53. http://www.ncbi.nlm.nih.gov/pubmed/24487405.

McNaught M, Caputi P, Oades LG, Deane FP. Testing the validity of the Recovery Assessment Scale using an Australian sample. Aust N Z J Psychiatry. 200741(5):450–7.

Chiba R, Miyamoto Y, Kawakami N. Reliability and validity of the Japanese version of the Recovery Assessment Scale (RAS) for people with chronic mental illness: scale development. Int J Nurs Stud. 201047(3):314–22. doi:10.1016/j.ijnurstu.2009.07.006.

Mak WWS, Chan RCH, Yau SSW. Validation of the Recovery Assessment Scale for Chinese in recovery of mental illness in Hong Kong. Qual Life Res. 201625(5):1303–11. http://link.springer.com/10.1007/s11136-015-1157-6.

Young DKW, Ng PYN, Pan J, Fung T, Cheng D. Validity and reliability of Recovery Assessment Scale for cantonese speaking Chinese consumers with mental illness. Int J Ment Health Addict. 201615(1):198–208. http://link.springer.com/10.1007/s11469-016-9657-3.

Cavelti M, Wirtz M, Corrigan P, Vauth R. Recovery assessment scale: examining the factor structure of the German version (RAS-G) in people with schizophrenia spectrum disorders. Eur Psychiatry. 201741:60–7. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85007448269&doi=10.1016/j.eurpsy.2016.10.006&partnerID=40&md5=d4b5eec5ad2c7f90cd55852388320492.

Almeida Berberian A, Silva TR, Gadelha A, Villares CC, Martini LC, Bressan RA. Validação da Recovery Assessment Scale (RAS) no Brasil para avaliar a capacidade de superação das pessoas com esquizofrenia. J Bras Psiquiatr. 201766(1):1–8. http://www.scielo.br/pdf/jbpsiq/v66n1/0047-2085-jbpsiq-66-1-0001.pdf.

Agrest M, Druetta I. The concept of recovery: the importance of users’ perspective and their participation. Vertex. 201122(95):56–64. http://www.ncbi.nlm.nih.gov/pubmed/21505647.

Gabay PM. Recovery: a new paradigm for psychiatry. Vertex. 201122(100):454–61. http://www.ncbi.nlm.nih.gov/pubmed/22799147.

Congreso de la Nación. Ley Nacional de Salud Mental (National Mental Health Law). República Argentina: Boletín oficial 2010.

DSM-IV-TR. Diagnostic and statistical manual of mental disorders: DSM-IV-TR. Lake St. Louis: American Psychiatric Association 2000.

Mundfrom DJ, Shaw DG, Ke TL. Minimum sample size recommendations for conducting factor analyses minimum sample size recommendations for conducting factor analyses. Int J Test. 20095(2):159–68.

Corrigan PW, Giffort D, Rashid F, Leary M, Okeke I. Recovery as a psychological construct. Community Ment Health J. 199935(3):231–9. http://link.springer.com/10.1023/A:1018741302682.

Monteiro MF, Ornelas JH. Recovery Assessment Scale: testing validity with Portuguese community-based mental health organization users. Psychol Assess. 201628(3):e1–11.

IBM CORP. Ibm, SPSS statistics for windows. Armonk: IBM Corp 2013.

Arbuckle JL. Amos. Chicago: IBM SPSS 2014.

Kaiser HF. An index of factorial simplicity. Psychometrika. 197439(1):31–6. http://link.springer.com/10.1007/BF02291575.

Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model A Multidiscip J. 19996(1):1–55. http://www.tandfonline.com/doi/abs/10.1080/10705519909540118.

Browne MW, Cudeck R. Alternative ways of assessing model fit. Sociol Methods Res. 199221(2):230–58. http://journals.sagepub.com/doi/10.1177/0049124192021002005.

Fukui S, Shimizu Y, Rapp CA. A cross-cultural study of recovery for people with psychiatric disabilities between US and Japan. Community Ment Health J. 201248(6):804–12.

Jacobson N, Greenley D. What is recovery? A conceptual model and explication. Psychiatr Serv. 200152(4):482–5. http://www.ncbi.nlm.nih.gov/pubmed/11274493.

Kelly M, Gamble C. Exploring the concept of recovery in schizophrenia. J Psychiatr Ment Health Nurs. 200512(2):245–51. http://www.ncbi.nlm.nih.gov/pubmed/15788044.

Townsend W, Glasser N. Recovery: the heart and soul of treatment. Psychiatr Rehabil J. 200327(1):83–6. http://www.ncbi.nlm.nih.gov/pubmed/12967237.

Fallot RD. Spirituality and religion in psychiatric rehabilitation and recovery from mental illness. Int Rev Psychiatry. 200113(2):110–6. http://informahealthcare.com/doi/abs/10.1080/09540260120037344.

Russinova Z, Cash D. Personal perspectives about the meaning of religion and spirituality among persons with serious mental illnesses. Psychiatr Rehabil J. 200730(4):271–84. http://www.ncbi.nlm.nih.gov/pubmed/17458451.

Hancock N, Bundy A, Honey A, Helich S, Tamsett S. Measuring the later stages of the recovery journey: insights gained from clubhouse members. Community Ment Health J. 201349(3):323–30.

Udagawa K. 2007 Sekai seishin hoken kaigi in Hong kong sanka inshouki—toujisha no bunkakai de hanasareta koto [World Federation for Mental Health 2007 Hong Kong biennial congress participation memory—what was talked in the section meeting for the people with mental]. Psychiatr Ment Health Nurs. 200811(1):79–81.

Garcia-Preto N. Latino families: an overview. In: McGoldrick M, Giordano J, editors. Ethnicity and family therapy. New York: Guilford Press 2005. p. 141–224. http://psycnet.apa.org/psycinfo/2006-00844-011.

Andresen R, Oades L, Caputi P. The experience of recovery from schizophrenia: towards an empirically validated stage model. Aust N Z J Psychiatry. 200337(5):586–94. http://anp.sagepub.com/lookup/doi/10.1046/j.1440-1614.2003.01234.x.

Schauer C, Everett A, del Vecchio P, Anderson L. Promoting the value and practice of shared decision-making in mental health care. Psychiatr Rehabil J. 200731(1):54–61. http://www.ncbi.nlm.nih.gov/pubmed/17694716.

Atkinson M, Zibin S, Chuang H. Characterizing quality of life among patients with chronic mental illness: a critical examination of the self-report methodology. Am J Psychiatry. 1997154(1):99–105.

Fleury MJ, Grenier G, Bamvita JM. Predictive typology of subjective quality of life among participants with severe mental disorders after a five-year follow-up: a longitudinal two-step cluster analysis. Health Qual Life Outcomes. 201513(1):150. doi:10.1186/s12955-015-0346-x.

Brown MA, Velligan DI. Issues and developments related to assessing function in serious mental illness. Dialogues Clin Neurosci. 201618(2):135–44. http://www.ncbi.nlm.nih.gov/pubmed/27489453.

Roe D, Mashiach-Eizenberg M, Lysaker PH. The relation between objective and subjective domains of recovery among persons with schizophrenia-related disorders. Schizophr Res. 2011131(1–3):133–8. http://www.ncbi.nlm.nih.gov/pubmed/21669512.

Giusti L, Ussorio D, Tosone A, Di Venanzio C, Bianchini V, Necozione S, et al. Is personal recovery in schizophrenia predicted by low cognitive insight? Community Ment Health J. 201551(1):30–7. http://www.ncbi.nlm.nih.gov/pubmed/25064088.

Berry JW. Cross-cultural psychology: research and applications. Cambridge: Cambridge University Press 1992.


Conclusions

This study showed that the great majority of a large, heterogeneous group of service users with psychosis across several clinical units reported that personal recovery was important for them, regardless of age, ethnicity, symptomatology, functioning, community treatment order status, and time in mental health care. This finding has implications for clinical practice, providing empirical evidence that recovery-oriented treatments are relevant for most service users with psychosis in various mental health services. Recovery-oriented treatments such as IMR, and related themes, such as help for coping with stress and illness and having a plan for early detection and prevention of relapse, appeared to help people with psychosis feel supported by clinicians in their personal recovery process. Specific attention should be given to service users with high levels of general symptoms and depression, because these service users experienced less support for personal recovery, even though personal recovery was equally important for them.

This study was funded by grant 2015106 from the South-Eastern Norway Regional Health Authority (Helse Sør-Øst). Dr. Slade acknowledges support from the Center for Mental Health and Substance Abuse, University of South-Eastern Norway, and the Nottingham Biomedical Research Centre, National Institute for Health Research.

Dr. Slade acknowledges support from the Center for Mental Health and Substance Abuse, University of South-Eastern Norway, and the Nottingham Biomedical Research Centre, National Institute for Health Research.

1 Anthony WA : Recovery from mental illness: the guiding vision of the mental health service system in the 1990s . Psychosoc Rehabil J 1993 16:11–23Crossref , Google Scholar

2 Slade M, Amering M, Oades L : Recovery: an international perspective . Epidemiol Psichiatr Soc 2008 17:128–137Crossref, Medline , Google Scholar

3 Resnick SG, Fontana A, Lehman AF, et al. : An empirical conceptualization of the recovery orientation . Schizophr Res 2005 75:119–128Crossref, Medline , Google Scholar

4 Leamy M, Bird V, Le Boutillier C, et al. : Conceptual framework for personal recovery in mental health: systematic review and narrative synthesis . Br J Psychiatry 2011 199:445–452. Crossref, Medline , Google Scholar

5 Van Eck RM, Burger TJ, Vellinga A, et al. : The relationship between clinical and personal recovery in patients with schizophrenia spectrum disorders: a systematic review and meta-analysis . Schizophr Bull 2018 44:631–642. Crossref, Medline , Google Scholar

6 Chan RCH, Mak WWS, Chio FHN, et al. : Flourishing with psychosis: a prospective examination on the interactions between clinical, functional, and personal recovery processes on well-being among individuals with schizophrenia spectrum disorders . Schizophr Bull 2018 44:778–786. Crossref, Medline , Google Scholar

7 Rosenheck R, Stroup S, Keefe RS, et al. : Measuring outcome priorities and preferences in people with schizophrenia . Br J Psychiatry 2005 187:529–536. Crossref, Medline , Google Scholar

8 Maslow AH : A theory of human motivation . Psychol Rev 1943 50:370–396Crossref , Google Scholar

9 Henwood BF, Derejko KS, Couture J, et al. : Maslow and mental health recovery: a comparative study of homeless programs for adults with serious mental illness . Adm Policy Ment Health Ment Health Serv Res 2015 42:220–228. Crossref, Medline , Google Scholar

10 Clarke S, Oades LG, Crowe TP : Recovery in mental health: a movement towards well-being and meaning in contrast to an avoidance of symptoms . Psychiatr Rehabil J 2012 35:297–304. Crossref, Medline , Google Scholar

11 Lofthus AM, Westerlund H, Bjørgen D, et al. : Recovery concept in a Norwegian setting to be examined by the assertive community treatment model and mixed methods . Int J Ment Health Nurs 2018 27:147–157. Crossref, Medline , Google Scholar

12 van Weeghel J, van Zelst C, Boertien D, et al. : Conceptualizations, assessments, and implications of personal recovery in mental illness: a scoping review of systematic reviews and meta-analyses . Psychiatr Rehabil J 2019 42:169–181. Crossref, Medline , Google Scholar

13 Bird V, Leamy M, Tew J, et al. : Fit for purpose? Validation of a conceptual framework for personal recovery with current mental health consumers . Aust N Z J Psychiatry 2014 48:644–653. Crossref, Medline , Google Scholar

14 Stuart SR, Tansey L, Quayle E : What we talk about when we talk about recovery: a systematic review and best-fit framework synthesis of qualitative literature . J Ment Health 2017 26:291–304. Crossref, Medline , Google Scholar

15 Schrank B, Slade M : Recovery in psychiatry . BJPsych Bull 2007 31:321–325 Google Scholar

16 Slade M, Amering M, Farkas M, et al. : Uses and abuses of recovery: implementing recovery-oriented practices in mental health systems . World Psychiatry 2014 13:12–20. Crossref, Medline , Google Scholar

17 McGuire AB, Kukla M, Green A, et al. : Illness Management and Recovery: a review of the literature . Psychiatr Serv 2014 65:171–179. Link , Google Scholar

18 Egeland KM, Ruud T, Ogden T, et al. : How to implement Illness Management and Recovery (IMR) in mental health service settings: evaluation of the implementation strategy . Int J Ment Health Syst 2017 11:13 Crossref, Medline , Google Scholar

19 Färdig R, Lewander T, Melin L, et al. : A randomized controlled trial of the illness management and recovery program for persons with schizophrenia . Psychiatr Serv 2011 62:606–612. Link , Google Scholar

20 Le Boutillier C, Leamy M, Bird VJ, et al. : What does recovery mean in practice? A qualitative analysis of international recovery-oriented practice guidance . Psychiatr Serv 2011 62:1470–1476. Link , Google Scholar

21 The ICD-10 Classification of Mental and Behavioral Disorders: Clinical Descriptions and Diagnostic Guidelines . Geneva, World Health Organization, 1992 Google Scholar

22 Williams J, Leamy M, Bird V, et al. : Development and evaluation of the INSPIRE Measure of Staff Support for Personal Recovery . Soc Psychiatry Psychiatr Epidemiol 2015 50:777–786. Crossref, Medline , Google Scholar

23 Eisen SV, Normand S-L, Belanger AJ, et al. : The revised Behavior and Symptom Identification Scale (BASIS-R): reliability and validity . Med Care 2004 42:1230–1241. Crossref, Medline , Google Scholar

24 Cameron IM, Cunningham L, Crawford JR, et al. : Psychometric properties of the BASIS-24 (Behaviour and Symptom Identification Scale–Revised) mental health outcome measure . Int J Psychiatry Clin Pract 2007 11:36–43. Crossref, Medline , Google Scholar

25 BASIS-24 Instruction Guide . Belmont, MA, McLean Hospital, 2006 Google Scholar

26 Priebe S, Huxley P, Knight S, et al. : Application and results of the Manchester Short Assessment of Quality of Life (MANSA) . Int J Soc Psychiatry 1999 45:7–12. Crossref, Medline , Google Scholar

27 Guy W : ECDEU Assessment Manual for Psychopharmacology . Rockville, MD, US Department of Health, Education, and Welfare, Public Health Service. Alcohol, Drug Abuse, and Mental Health Administration, 1976 Google Scholar

28 Busner J, Targum SD : The Clinical Global Impressions Scale: applying a research tool in clinical practice . Psychiatry 2007 4:28–37. Medline , Google Scholar

29 Diagnostic and Statistical Manual of Mental Disorders (DSM-5) . Arlington, VA, American Psychiatric Association Publishing, 2013 Google Scholar

30 Pedersen G, Hagtvet KA, Karterud S : Generalizability studies of the Global Assessment of Functioning–split version . Compr Psychiatry 2007 48:88–94. Crossref, Medline , Google Scholar

31 Thomas EC, Despeaux KE, Drapalski AL, et al. : Person-oriented recovery of individuals with serious mental illnesses: a review and meta-analysis of longitudinal findings . Psychiatr Serv 2018 69:259–267. Link , Google Scholar

32 Priebe S, Reininghaus U, McCabe R, et al. : Factors influencing subjective quality of life in patients with schizophrenia and other mental disorders: a pooled analysis . Schizophr Res 2010 121:251–258. Crossref, Medline , Google Scholar

33 Clausen H, Landheim A, Odden S, et al. : Associations between quality of life and functioning in an assertive community treatment population . Psychiatr Serv 2015 66:1249–1252. Link , Google Scholar


Medication Free Treatment: Characteristics, Justification and Outcome

In 2015 the Norwegian government, after initiative from user organizations, decided to implement medication free inpatient treatment units. The goal is to secure real options to medication for psychiatric illness, and to gather experiences with medication free options. Freedom of choice is a main concern.

The projects main aim is to study the outcome of medication free treatments of mental illness compared to treatment as usual, as well as characteristics of the treatment and the treatment population and why patients choose this treatment. Hereunder we aim to document who asks for these kinds of services and why, what kind of treatment they get, how they experience it, and how they respond to this kind of treatment. An important part will be to document whether the goal of increased freedom of choice between real treatment options is fulfilled.

  1. Does medication free treatment differ from treatment as usual? Are there any unique characteristics of the patient group who asks for this kind of treatment? What kind of treatment do they receive during their stay? How do they experience this treatment in comparison to treatment as usual? How is this in relation to the goals about increased freedom of choice? Does use of medication change during and/or after medication free treatment?
  2. Why do patients choose medication free treatment? What are their reasons? What experiences lead to this wish?
  3. What is the outcome of medication free treatment compared to treatment as usual?

Condition or disease Intervention/treatment
Mental Illness Behavioral: Medication free treatment Behavioral: Treatment as usual Myrvegen Behavioral: Treatment as usual Åråsen

Background In 2015 the Norwegian government, after initiative from user organizations, decided to implement medication free inpatient treatment units. The goal is to secure real options to medication for psychiatric illness, and to gather experiences with medication free options. Freedom of choice is a main concern. (Aksjon for medisinfrie tilbud) The local unit under study DPS døgn Moenga at Akershus University Hospital has been given the assignment of developing a medication free treatment unit. This is an inpatient treatment unit for voluntary, planned treatment. High suicidal risk, severe acting out, active drug abuse etc. is excluded. The treatment program is 8 weeks long.

Status of knowledge The project has been controversial, especially with reference to the status of knowledge. Critiques have stated that the knowledge base for treating serious psychiatric disorders without medication is lacking (Gundersen, 2016 Røssberg, 2016). Concerns are raised about whether it can be harmful (Røssberg, 2016), whether it is necessary (Røssberg, Andreassen, & Malt, 2016) and whether it creates unfortunate dividing lines within health care (Røssberg et al., 2016). National guidelines recommend considering/offering medication for bipolar disorders, deep depression and psychosis (Helsedirektoratet, 2009, 2012, 2013). On the other hand, the knowledge base for use of psychotropic drugs is also being questioned, especially regarding long term effects (Bentall, 2009 Forand & DeRubeis, 2013 Moncrieff, 2009 Sohler et al., 2016 Whitaker, 2010/2014 (no), 2016). Studies on medication are amongst others criticized for not taking withdrawal effect sufficiently into account (Bentall, 2009 Forand & DeRubeis, 2013 Moncrieff, 2009 Whitaker, 2010/2014 (no), 2016). A randomized controlled study by Wunderink, Nieboer, Wiersma, Sytema, and Nienhuis (2013) indicates a follow up period of at least 3 years is necessary to see the benefits of drug reduction regarding antipsychotics.

Summing up, one can argue that generally, a considerable research base point to psychosocial treatment methods having an important place in the treatment of most psychiatric problems (Lambert, 2013 Wampold, 2001 Wampold & Imel, 2015). The more specific questions regarding pure psychosocial treatment for serious disorders and long term effects of psychotropic drugs are at least disputable, and probably under-researched.

  1. Does medication free treatment differ from treatment as usual? Patient characteristics, treatment received, experience, medication use.
  2. Why do patients choose medication free treatment? What are their reasons? What experiences lead to this wish?
  3. What is the outcome of medication free treatment compared to treatment as usual? Hypotheses The treatment outcome of medication free treatment is not inferior to treatment as usual.

Patients in medication free treatment will use less medication. Medication withdrawal may affect outcome in the short run.

Project methodology The design of the study is a mixed methods, observational design within a naturalistic treatment setting using qualitative and quantitative methods to address the research questions.

Moenga consist of two units, the medication free unit and a regular unit, which will be included for comparison. In addition we include a treatment unit on a different location for comparison DPS Myrvegen. We aim for at least 200 n.

One complication is that this autumn it was decided that the units at Moenga shall move and reorganize sometime during 2018. This entail change of location, possible reorganizing of personnel and that the comparison unit at Moenga is joined with another inpatient unit at the new location. This may cause disruptions that can affect our results. We will study possible effects of this in our data, and may exclude parts of the gathered data and prolong the inclusion period.

We will collect survey data at start of treatment, weekly during treatment, at end of treatment (Work package 1), and at 6 months, 1 year, 2 years and 3 years follow up (work package 3). Register data will be collected 3 years back and 3 years follow up (work package 3). Patient interviews (work package 2) and personnel interviews (work package 4) are performed during spring 2018, the patient interviews near the end of the treatment stay. See measures for details.

Plan for data analyses Quantitative and qualitative analyses will be done according to the research questions. We will seek to compare the medication free unit and treatment as usual. Calculating propensity scores in the observational part of the study will be considered, to balance comparison groups (Austin, 2011).

Statistical power Exact power calculations are only possible in concrete, delimited statistical designs, and must necessarily be based on assumptions not always known before starting the study. In a design with 200 persons the total effect of one-way analysis of variance yield a statistical power of .80 for small to medium effect sizes. That is, the probability of detecting differences between groups will be .80 for effect sizes in the range .40 -.50. For pairwise comparisons between groups (with N=50), the probability of detecting effects in the range of Cohen's d >=. 40 will be about .80. In Cohen's pragmatic system, effect sizes with such magnitudes represent a "small to medium effect size". These estimations will also apply to change-scores between two points in time, given that the correlation between the two repeated measurements are r >= .5.

Work package 1: Inclusion of patients for quantitative measurements starts April 2018 with a 12 months inclusion period. This may be prolonged if necessary.

Work package 2: Patient interviews will be performed during spring 2018. Work package 3: Follow up measures and register data will be collected until spring 2022.

Work package 4: Personnel interviews will be performed during spring 2018. Analysis Qualitative analyses will be performed within end of 2018. Quantitative analyses will start January 2019 Publishing Publishing of the results in scientific papers will take place mainly in 2019-2023.

  1. "Medication free treatment: Does it differ from treatment as usual?" This article will address research question 1 and include qualitative data, Collaborate, BMQ, Inspire, CSQ-8, WAI, treatment received, use of medication and background data.
  2. "Medication free treatment: Why?" This article will address research question 2 (Why do patients choose medication free treatment) and include qualitative data.
  3. "Medication free treatment: Does it work?" This article will address the research questions and will include the outcome measures OQ-45, AII, Quality of life, HoNOs, GAF, CGI, drug use, diagnoses and register data. We will also look for correlations between use of medication and outcome, and therefore include measures of medication use.

Research group PhD Kristin S. Heiervang, head of the research group Quality and implementation in Mental Health Services at Akershus university hospital, is project manager (principal investigator) for the project.

Anders S. Wenneberg, specialist in clinical psychology, is the leader of the inpatient treatment facility. Wenneberg is also the project manager of the "Medication Free Treatment" at Akershus University Hospital, Moenga.

Ole André Solbakken is associate professor of clinical psychology and head of section at the Department of Psychology, University of Oslo.

Odd Arne Tjersland is professor of clinical psychology at the Department of Psychology, University of Oslo.

Jon T. Monsen is professor of clinical psychology at the Department of Psychology, University of Oslo.

Allan Abbass is professor, psychiatrist, and founding Director of the Centre for Emotions and Health at Dalhousie University in Halifax, Canada.

Kari Standal will be the PhD candidate. She is a psychologist at Akershus university hospital, specialized in adult treatment and psychotherapy (group treatment and affect consciousness).

Jill Arild, board member of "Mental Helse" and leader of the action group for medication free treatment is user represantive in the project.

Astrid Ringen Martinsen is a psychology student who will write her main thesis on the qualitative patient data.

Ingrid Engeseth Brakstad is a psychology student who will write her main thesis on the qualitative personnel data.

Layout table for study information
Study Type : Observational [Patient Registry]
Estimated Enrollment : 200 participants
Observational Model: Other
Time Perspective: Prospective
Target Follow-Up Duration: 3 Years
Official Title: Medication Free Treatment: Characteristics, Justification and Outcome
Actual Study Start Date : May 14, 2018
Estimated Primary Completion Date : May 14, 2020
Estimated Study Completion Date : April 1, 2023

Resource links provided by the National Library of Medicine

Methods

Setting

In the UK a veteran is defined as an individual who has completed at least 1 day of military service and is no longer employed by the Armed Forces.15 This was a naturalistic study of individuals who had enrolled on a 6-week inpatient intensive treatment programme (ITP) for PTSD offered by Combat Stress to UK veterans between late 2012 and early 2014. The ITP is a residential programme and consists of a mixture of individual TF-CBT and groups scheduled on weekdays from 9:00 to 17:00 that are standardised and manualised to ensure a homogenous treatment experience for participants. Individuals were assigned to a closed group of eight and are offered a minimum of 15 individual TF-CBT therapy sessions (lasting 90 min) and 55 group sessions each lasting 1 h. Individual TF-CBT was offered by psychologists and CBT therapists and focused on working on trauma memories connected to military service. Group sessions were facilitated by a multidisciplinary team consisting of psychologists, CBT therapists, occupational therapists and art therapists. Group sessions included psychoeducational groups (eg, understanding PTSD, CBT education, understanding medication, exploring the links between PTSD and memory, sleep hygiene and relaxation techniques) and symptom management groups (eg, managing anxiety, managing anger, behavioural activation for depression and mindfulness groups). In addition, occupational therapists facilitated a number of groups aimed at supporting well-being (eg, groups to support resilience, develop goal planning skills and practical groups to encourage individuals to engage in meaningful activities) and six art therapy groups were offered (once a week throughout the ITP). On a typical day participants attended two group sessions that lasted an hour each and were invited to practice newly acquired skills in between sessions. Meal times were fixed throughout the day. Over the course of the week participants attended three 90 min individual TF-CBT sessions.

Participants

When individuals are referred into Combat Stress they receive an initial assessment which includes a range of health measures. Individuals who screen positive for PTSD are then given a referral for an ITP assessment. Prior to admission for the ITP, individuals are assessed separately by a psychiatrist and a psychologist to explore diagnosis, comorbidity and suitability for the programme. Inclusion criteria included having a primary diagnosis of PTSD, exposure to two or more traumatic events connected to an individuals’ military career and being a veteran of the UK military. In addition, where participants were on psychiatric medications, these had to be stable prior to enrolling on the ITP and participants had to remain on the same dose and medication for the duration of the ITP. Exclusion criteria included being actively suicidal, being actively dependent on alcohol, having a diagnosis of a personality disorder, being actively psychotic or whether there was evidence of a brain injury that impacts significantly on cognitive functioning. This did not exclude individuals with mild or moderate brain injuries. When veterans met exclusion criteria, where possible they were given appropriate support and then re-assessed at a later date. For example, this included referrals to substance misuse services or psychiatric support for active symptoms of psychosis. In addition, individuals were required to not drink alcohol or use illicit drugs during the 6-week programme.

A total of 246 participants enrolled on the ITP between 2012 and early 2014. Individuals had to stay for at least 5 weeks of the 6-week programme and attend a minimum of 15 individual TF-CBT sessions to be considered a completer of the programme. Fifteen (6%) participants were classified as non-completers. Of these, five individuals had been asked to leave the ITP because they consumed alcohol during their stay, six individuals were deemed unsuitable for therapy by the clinical team, three individuals had to leave early because of complicated physical health difficulties that arose during their admission, and one individual had to leave early because a family member became unwell.

A total of 231 individuals completed the ITP and 186 (81%) of these were successfully followed up at 6 months. Of the 45 non-responders (19%), 22 were contacted for a non-responder study, one had died (of natural causes), eight had withdrawn their consent to be contacted for follow-up and it was not possible to contact the remaining 14. This means that 49% of our non-responders were contacted for the non-responder study. This increased to 65% when individuals who had died or refused further contact were removed. An overview of the sample is provided in figure 1.

Outcome measures

Outcome measures were collected at admission, discharge, 6 weeks and at 6 months follow-up. At each of these time points the treating clinician completed a ‘clinician’ pack of measures and participants were asked to complete a ‘veterans’ pack of measures. Our primary outcomes for this study were measures of mental health difficulties and our secondary outcomes were measures of functional impairment.

Primary outcome measures

The clinician completed the PTSD Symptom Scale Interview (PSS-I). The PSS-I is a 17-item semistructured interview that assesses the presence and severity of diagnostic symptoms of PTSD using the Diagnostic and Statistical Manual Fourth Edition (DSM-IV).16 , 17 In addition, the participants were asked to complete a number of measures. These included the Revised Impact of Events Scale (IES-R) which measures symptoms of PTSD with 22-items.18 To explore other mental health difficulties participants completed the Patient Health Questionnaire (PHQ-9) which explores symptoms of depression19 , 20 the Generalised Anxiety Disorder Assessment (GAD-7) which explores symptoms of anxiety21 and the Dimensions of Anger Reactions (DAR-5) to measure symptoms of anger.22

Secondary outcome measures

Clinicians completed the Global Assessment of Function (GAF). This is a numeric scale from 1 to 100 that is used to subjectively rate social, occupational and psychological functioning. The GAF is described in the DSM-IV.17 Clinicians also completed the Health of the Nation Outcome Scales (HONOS) this has 12 items and measures behaviours, impairment, symptoms and social functioning.23 Participants completed the Work and Social Adjustment Scale (WSAS). The WSAS is a self-report questionnaire that measures an individuals’ perspective on their level of impaired functioning.24

Demographic characteristics

Demographic details were collected on all participants, with additional information about service (Royal Navy, Army or RAF), last rank (Officer or other rank), year they left, number of deployments they went on and how they left the military.

Non-responder study measures

Those who failed to respond at 6 months were contacted and invited to participate in a non-responder study. Researchers attempted to telephone non-responders three times to ask them to complete a number of health measures. These were the PSS-I to measure symptoms of PTSD and the PHQ-9 and GAD-7 to measure comorbid symptoms of depression and anxiety respectively.

Analysis

The first stage was to conduct exploratory analyses to assess whether potential biases were presented. To do this we used Mann-Whitney U tests to explore whether differences in baseline health scores were present between individuals who completed the ITP and individuals who did not. Following this we used χ 2 tests to explore sociodemographic differences between responders and non-responders. As detailed above, a non-responder study was conducted which collected health measures from individuals we were able to contact. Mann-Whitney U tests were used to compare the health scores between responders and non-responders.

The final stage of the analysis was to explore our primary and secondary outcomes following treatment. Random slopes non-linear growth models were fitted to explore the longitudinal health and functional impairment data collected at admission, discharge, 6 weeks and 6 months follow-up.25 These analyses were repeated and adjusted for age group (<35, 35–44 and >45) and employment status. This is because these were found to improve the fit of the models using likelihood ratio tests. The models fitted were non-linear and used a fixed coefficient of time squared. Analyses were conducted using Stata V.13 (StataCorp, College Station, Texas, USA).


Additional information

Competing interests

SB is a psychiatrist and has been Medical Affairs Manager for Janssen-Cilag Portugal since April 2010. AM is a consultant psychiatrist in Oxfordshire affiliated to the Social Psychiatry Group in the Oxford University Department of Psychiatry. VVD is a clinical neuropsychologist affiliated to Santa Maria's University Hospital. He is a consultant for Angelini Pharmaceutical Portugal, and has received educational grants from Lundbeck, Sanofi-Aventis, Janssen-Cilag and AstraZeneca. MLF is a full professor of Psychiatry and Head of the Department of Psychiatry at Santa Maria's University Hospital.

Authors' contributions

SB managed the literature search, and wrote the first draft of the manuscript. The data were analysed by SB, VVD, AM and MLF, who wrote the final draft of the manuscript. All authors contributed to and approved the final version of the manuscript.


Discrepancy between experience and importance of recovery components in the symptomatic and recovery perceptions of people with severe mental disorders

Personal recovery has become an increasingly important approach in the care of people with severe mental disorders and consequently in the orientation of mental health services. The objective of this study was to assess the personal recovery process in people using mental health services, and to clarify the role of variables such as symptomatology, self-stigma, sociodemographic and treatment.

Methods

Standardised measures of personal recovery process, clinical recovery, and internalized stigma were completed by a sample of 312 participants in a Severe Mental Disorder program.

Results

Users valued most the recovery elements of: improving general health and wellness having professionals who care hope and sense of meaning in life. Significant discrepancies between perceived experience and relative importance assigned to each of the components of the REE were observed. Regression modeling (χ 2 = 6.72, p = .394 GFI = .99, SRMR = .03) identified how positive discrepancies were associated with a higher presence of recovery markers (β = .12, p = .05), which in turn were negatively related to the derived symptomatology index (β = −.33, p < .001). Furthermore, the relationship between clinical and personal recovery was mediated by internalized stigma.

Conclusions

An improvement in psychiatric services should be focused on recovery aspects that have the greatest discrepancy between importance and experience, in particular social roles, basic needs and hope. Personal and clinical recovery are correlated, but the relationship between them is mediated by internalized stigma, indicating the need for clinical interventions to target self-stigma.


Generalizability studies of the Global Assessment of Functioning–Split version

The study aimed to use the Generalizability Theory to investigate the reliability and precision of the split version of the Global Assessment of Functioning (GAF).

Materials

Six case vignettes were assessed by 2 samples one by 19 experienced and independent raters and another by 58 experienced raters from 8 different day-treatment units, evaluating both symptom and function scores of GAF.

Methods

Generalizability studies were conducted to disentangle relevant variance components accounting for error variance in GAF scores. Furthermore, decision studies were conducted to estimate the reliability of different measurement designs, as well as precision in terms of error tolerance ratio.

Results

Both symptom and function scores of GAF were found to be highly generalizable, and a measurement design of 2 raters per subject was found to be most efficient with respect to reliability, precision, and use of resources.

Conclusion

Both symptom and function scores of GAF seem highly consistent across experienced raters.


Axis V – Global Assessment of Functioning Scale (GAF), further evaluation of the self-report version

The study aimed to examine agreement between patients' and professional staff members' ratings on the Global Assessment of Functioning scale (GAF).

A total of 191 young adult psychiatric outpatients were included in a naturalistic, longitudinal study. Axis I and axis II disorders were assessed by means of the Structured Clinical Interview for DSM-IV. Before and after treatment, patients and trained staff members did a GAF rating. Agreement between GAF ratings was analyzed using the intra-class correlation coefficient (ICC).

The overall intra-class correlation coefficients before and after treatment were 0.65 and 0.86, respectively. Agreement in different axis I diagnostic groups varied, but was generally lower before treatment as compared to after treatment (0.50–0.66 and 0.78–0.90, respectively). Excessive psychiatric co-morbidity was associated with the lowest inter-rater reliability. Agreement, with respect to change in GAF scores during treatment, was good to excellent in all groups.

Overall, agreement between patients' and professionals' ratings on the GAF scale was good before and excellent after treatment. The results support the usefulness of the self-report GAF instrument for measuring outcome in psychiatric care. However, more research is needed about the difficulties in rating severely disordered patients.


Key point #2: There is a Need for Functional Performance Testing (FPT)

Presently used methods of assessing function in clinical practice are incomplete. Much like the difficulty in, and complexity of, measuring function, there is the obstacle of defining function and the definitive assessment process for it.

FPT defined

‘Testing’ is defined as using a set of problems to assess abilities. Therefore, we have previously termed FPT to mean using a set of tests to determine performance abilities or functional limitations. 45 In other words, FPT is not impairment or PPM testing ( Table 1 ). In simplified terms, impairments and PPM are typically more isolated findings while function is a more global concept incorporating the entire extremity, body, or person.

Table 1

Muscle performance (primarily includes manual muscle testing)

ROM (including muscle length)

Joint integrity and mobility

Peripheral nerve integrity

Gait, locomotion, and balance

Aerobic endurance testing in multiple planes of movement

Balance/proprioceptive testing in multiple planes of movement

Softball throw for distance

Speed, agility, and quickness testing

Note: PPMs = physical performance measures ROM = range-of-motion.

Pain perception and movement, both integral elements in assessment of manual therapy interventions, are mediated by contextual elements such as cognitive, emotional, and social factors. 45 Consequently, an expanded conceptual model of patient management and assessment at a functional, rather than impairment or PPM level, is necessary to fully evaluate all the elements associated with functioning. 45 This expanded conceptual model (FPT), ventures to capture the multiple dimensions of function through clustered physical performance movements.

FPT can therefore be more complexly defined as using a variety of physical skills and tests to determine: (1) one’s ability to participate at the desired level in sport, occupation, and recreation or to return to participation in a safe and timely manner without functional limitations and (2) one’s ability to move through up to three planes of movement as determined via non-traditional testing that provides qualitative and quantitative information related to specialized motions involved in sport, exercise, and occupations. 45 The clinician should understand that FPT is an aspect of everyday life, whether for the elite athlete, the industrial worker, or the homemaker. The commonality among all groups is that some aspect of performance is needed for each individual to be successful in performing their respective skills or duties. 45

Compared to clinical assessment with special tests, assessments with FPTs test the ability of the person to put together a series of movements (rather than isolated single joint and planar movements) to safely and efficiently complete a task. In other words, assessment at the functional level assesses function of the person rather than function of the part of the person. 24 For example, the fact that a person has full hip, knee, and ankle ROM does not ensure successful return to basketball. If this same person has normal joint play, full strength, and full neuromuscular control and additionally is able to achieve an excellent score on jumping/hopping and anaerobic endurance tests without adverse symptoms, there should be much more confidence about the prospect of a safe return. Many FPTs closely approximate the activities that people need or wish to do.

We recommend the expansion of these recommendations to state that measurement of an individual’s ability to properly function should be along a continuum, and should include multiple measures ( Figs. 1 and ​ and2 2 and Table 2 ). To achieve this objective, the measurement of function demands careful individual consideration and investigations of the interactions among various examination methods.

Conceptual model of comprehensive assessment of function.

Proposed examination continuum. FPT =𠂯unctional performance testing.

Table 2

Self-report measures most indicative of dysfunction

Bio-psycho-social measures relevant to dysfunction

Self-report of activity rating scales (patient interpretation on specific requirements of their necessary activity level to return to previous level of function) 61

Clinician analysis of specific sport/occupation/activities of daily living with respect to requirements (specific type of movements, energy system involvement, etc.)

Anthropometric measurements (body mass index, girth and height measurements, etc.)

Static balance (bilateral and single-leg balance static assessment)

Dynamic posture (posture of individual as they perform movements required)

General movement patterns (walking, transfer movements, etc.)

Dynamic balance predominantly in one plane of movement without quality assessment (functional reach test, tandem walking, etc.)

Assessment of movement patterns the individual performs with their primary tasks (specific sport, occupational, etc. tasks)

Functional movement screen

Movement Impairment syndrome assessment

Single-leg inclined squat on total gym

Multiple joint involvement

Multiple muscle group involvement

Aerobic endurance testing

Star excursion balance test

Knee bending in 30 seconds

Single jump and hop testing in one plane of movement

Jump and hop testing in multiple planes of movement or requiring multiple jumps or hops

Single-leg crossover hop for distance

Hop testing after fatigue

Running-based anaerobic sprint test

Lower extremity functional test

Speed and agility testing

Sidearm medicine ball throw

Underkoffler softball throw for distance

Balance error scoring system

Functional throwing performance index

Multiple single-leg hop stabilization

Functional capacity evaluation

Firefighting �ility test’

Functional abilities test

Assessment forward and backward along the functional continuum ( Fig. 2 ) utilizing each parameter of function (impairment, performance measures, and self-report measures) as necessary

Note: ROM = range-of-motion PPM = physical performance measure 1RM = one repetition maximum BEAST90 =�ll-sport endurance and sprint test FPT =𠂯unctional performance testing.

Traditional thought regarding the examination process might suggest that the normal assessment ‘procedures’ progress from self-report measures to examination (including observation) followed by special testing (with use of clinical measures or other tests). FPT, if employed, would then be implemented at the very end stage of the rehabilitation process. It is our contention that the measurement of function requires assessment of combinations of these measures ( Fig. 1 ) throughout the rehabilitation process. Examination of a patient’s function requires assessment of the entire disablement model.

The conceptual model illustrated in Fig. 1 suggests this comprehensive approach to measuring function. It should also be pointed out that this conceptual model advocates multi-directional flow along the assessment continuum. There are levels of function assessment ( Table 2 ). Lower levels of function assessment can be implemented earlier in the examination process when warranted. In the above example, the use of functional movement and Rockport walk test could be utilized even prior to jumping/hopping and/or isokinetic testing in some dysfunctions. Functional movement could be utilized to screen for normal joint mobility in many early stage rehabilitation programs assuming safety. Additionally, the use of the deep squat assessment component of the Functional Movement Screen™ (Functional Movement Systems, Danville, VI, USA) 43 could be used to determine restricted mobility of the hip joint (impairment). Lack of sufficient hip mobility would not allow the patient to perform a proper deep squat. Performing this assessment early in the examination process would allow the clinician to complete the necessary impairment assessments in order to ascertain the reason(s) for improper deep squatting. Another example of multi-directional flow examination may have a patient perform the firefighting �ility test’ 52 (as long as not contraindicated), allowing the clinician to assess for potential restricted abilities, whether they exist at the PPM or impairment level. An unsuccessful attempt at a specific component of this test does not specifically uncover the limitation, but it can allow the clinician to converge on identifiable areas of interest (impaired joint mobility, decreased muscle performance, etc.). Use of higher levels of testing in this fashion can prove beneficial in determining the limiting factors of function in these patients. The following articles in this series plan to use an algorithmic approach to demonstrate such examples of the integration of the multiple types of testing that we suggest in the comprehensive examination conceptual model. The combination of all of these testing approaches measures the concept of function.



Comments:

  1. Grant

    Agreed, your thought is brilliant

  2. Kezilkree

    Yes it is fantastic

  3. Llacheu

    This is true.

  4. Mitchel

    I apologise, I can help nothing. I think, you will find the correct decision. Do not despair.

  5. Thanos

    Of course. And I ran into this. We can communicate on this theme. Here or at PM.



Write a message