Evidence-Based Treatment of Post-Traumatic Stress Disorder

Evidence-Based Treatment of Post-Traumatic Stress Disorder

  

Luke Fullagar 

RMIT University

 

 

This paper outlines the evidence base for the treatment of post-traumatic stress disorder (PTSD) in adults. Due to its Australian-context, this paper primarily relies on the meta-analysis completed by the Australian Centre for Posttraumatic Mental Health (ACPMH ) in 2007 (ACPMH, 2007), which includes and transcends the prior seminal systematic meta-analysis undertaken by United Kingdom National Institute for Clinical Excellence (NICE) in 2005 (NICE, 2005). Given word restrictions, for brevity, study references in this paper will generally refer to additional studies included in the expanded evidence-base reviewed by the ACPMH, and should be taken as extending rather than ignoring the NICE evidence base (as is the spirit of the ACPMH report).

Currently, the strongest-evidence base for psychological treatment of adults with PTSD is in respect of two trauma-focussed interventions: trauma-focussed cognitive behavioural therapy (TF-CBT) and eye movement desensitization (EMDR) and reprocessing treatment together with in vivo exposure therapy (ACPMH, 2007).  Over 30 controlled studies support these broad conclusions and demonstrate effectiveness in both PTSD symptoms and with comorbid depression and anxiety (ACPMH, 2007).  The following expands on this evidence, and concludes with a comparison of these treatments, and their recommended application in clinical settings.

Randomised controlled trials comparing TF-CBT in a range of contexts (e.g. earthquake victims, partner abuse), have demonstrated consistent, statistically-significant clinical superiority to waitlist conditions in reducing PTSD symptom severity and post-treatment diagnosis (both self-reported and clinician-rated) (ACPMH, 2007; Ehlers et al., 2005; Kubany et al., 2004; Basoglu et al., 2005; Lindauer et al., 2005; McDonagh et al., 2005; Rothbaum et al., 2005).  Moreover, two studies have demonstrated statistically-significant improvements in functioning in people receiving FT-CBT when compared with waitlist-conditions (ACPMH, 2007; Ehlers et al., 2005; Basoglu et al., 2005).  While the NICE study found significant evidence favouring FT-CBT over waitlist-conditions in reducing anxiety-related symptoms, subsequent studies reviewed by the ACPMH found a variant, and overall lesser standard of evidence (ACPMH, 2007; McDonagh, 2005; Ehlers, 2005). The NICE study found limited evidence for clinical superiority of FT-CBT over waitlist conditions for depression symptoms (NICE, 2005), and while observing a range of studies with very low or no statistically-significant reductions in depressive-symptoms, the ACPMH study noted two studies which demonstrated this relationship in populations which were predominantly woman aged in their late 30s to 40s (ACPMH, 2007; Kubany 2004; Ehlers, 2005).  Currently, evidence is unclear on the efficacy or clinical importance of FT-CBT in increasing self-reported quality of life (ACPMH, 2007; McDonagh, 2005).

Similarly, there is limited, relevant evidence supporting EDMR over waitlist-conditions in reducing PTSD symptom severity and post-treatment diagnosis (both self-reported and clinician-rated), depressive symptoms, anxiety symptoms and in increasing self-reported quality of life (NICE, 2005).

When comparing these treatments, both the NICE and ACPMH meta-analyses revealed inconclusive evidence to determine whether TF-CBT and EDMR differ in clinical importance on reducing PTSD symptom severity, post-treatment diagnosis (both self-reported and clinician-rated), clinician-rated symptom severity at 3 month follow up, anxiety symptoms at treatment conclusion and at 2-5 month follow-up, and in increasing self-reported quality of life (ACPMH, 2007; NICE, 2005).  Evidence also suggests that there is unlikely to be a clinically important difference between these treatments in respect of self-reported PSTD symptoms at 3-month follow-up, self-reported depression symptoms at 2-5 month follow-up, and limited evidence favouring EDMR over TF-CBT in reducing self-reported depression symptoms at treatment cessation (ACPMH, 2007; NICE, 2005). 

However, despite these statistical results in meta-analyses, a close inspection of the cases making up these analyses reveals qualitative differences in follow-up outcomes (ACPMH, 2007). There is support for opposing views: two studies demonstrate exposure's superiority over EDMR (which demonstrated some return to baseline at follow-up) (Devilly & Spence, 1999; Taylor, 2003) and another with regard to depression and end-state functioning at follow-up (Rothbaum, 2005); while in the converse Ironson (2002) and Lee (2002) demonstrate EDMR's superiority at follow-up.  The ACPMH (2007) argue that alterations to contemporary EDMR which include in vivo exposure and CBT techniques such as cognitive interweaving, future templating, create confounds in this comparison, and that there is therefore a case for treating contemporary EDMR as a variant of TF-CBT (ACPMH, 2007).  This view is supported by evidence suggesting that the aforementioned elements of contemporary EDMR potentially contribute more than the eye-movements themselves (Foley & spates, 1995; Renfrey & Spates, 1994), and critically, the cognitive restructuring and exposure components. 

While some evidence exists suggesting that cognitive restructuring and exposure components are efficacious on their own and demonstrate no improved outcomes when combined (Bryant, 2005; Marks, 1998), the lack of independence between these two treatment variables confounds the current evidence, and accordingly, no conclusive position is yet available on this point (ACPMH, 2007).  On this point, it is also important to note that other treatments such as psychoeducation, anxiety management and stress-inoculation training – which have demonstrated better than wait-list effectiveness yet lower than trauma-focussed treatment effectiveness in reducing post-treatment diagnosis, on follow-up and in treating comorbidities – are all included as elements in the more efficacious trauma-focussed treatments described herein (ACPMH, 2007).

No current evidence base exists for recommending a number of treatment sessions, and studies included in meta-analyses have ranged from single sessions to treatment protocols of 4-14 sessions (ACPMH, 2007).

No current evidence exists demonstrating any superiority of pharmacotherapy over trauma-focussed psychotherapeutic interventions on any of the abovementioned measures, and importantly, on dealing with depression comorbidity (NICE, 2005). Accordingly, it is recommended by NICE and ACPMH that pharmacotherapy not form a routine non-selective first-line treatment for traumatised adults in preference to trauma-focussed psychotherapy (ACPMH, 2007). However, on the basis of a Cochrane Review (Stein et al, 2006), which demonstrates that the greatest number of trials demonstrating efficacy were in respect of SSRIs, ACPMH recommends that where medication is prescribed in the treatment of PTSD in traumatised adults, SSRI antidepressants should be the first-choice.

 

References

 

ACPMH (Australian Centre for Posttraumatic Mental Health). (2007). Australian Guidelines for Treatment of Adults with Acute Stress Disorder and Posttraumatic Stress Disorder. Melbourne: Australian Centre for Posttraumatic Mental Health.

Basoglu, M., Salcioglu, E., Livanou, M., Kalender, D., & Acar, G. (2005). Single-session behavioral treatment of earthquake-related posttraumatic stress disorder: A randomized waiting list controlled trial. Journal of Traumatic Stress, 18(1), 1–11.

Bryant, R. A., Moulds, M. L., Guthrie, R. M., & Nixon, R. D. V. (2005). The additive benefit of hypnosis and cognitive-behavioral therapy in treating acute stress disorder. Journal of Consulting and Clinical Psychology, 73(2), 334–340.

Devilly, G. J., & Spence, S. H. (1999). The relative efficacy and treatment distress of EMDR and a cognitive-behavior trauma treatment protocol in the amelioration of posttraumatic stress disorder. Journal of Anxiety Disorders, 13(1–2), 131–157.

Ehlers, A., Clark, D. M., Hackmann, A., McManus, F., & Fennell, M. (2005). Cognitive therapy for post-traumatic stress disorder: development and evaluation. Behaviour Research and Therapy, 43(4), 413–431.

Foley, T., & Spates, C. R. (1995). Eye movement desensitiation of public-speaking anxiety: A partial dismantling. Journal of Behavior Therapy and Experimental Psychiatry, 26, 321–329.

Ironson, G., Freund, B., Strauss, J. L., & Williams, J. (2002). Comparison of two treatments for traumatic stress: A community-based study of EMDR and prolonged exposure. Journal of Clinical Psychology, 58(1), 113–128.

Kubany, E. S., Hill, E. E., Owens, J. A., Iannce-Spencer, C., McCaig, M. A., Tremayne, K. J., & Williams, P. L. (2004). Cognitive Trauma Therapy for Battered Women With PTSD (CTT-BW). Journal of Consulting and Clinical Psychology, 72(1), 3–18.

Lee, C., Gavriel, H., Drummond, P., Richards, J., & Greenwald, R. (2002). Treatment of PTSD: Stress inoculation training with prolonged exposure compared to EMDR. Journal of Clinical Psychology, 58(9), 1071–1089.

Lindauer, R. J. L., Gersons, B. P. R., van Meijel, E. P. M., Blom, K., Carlier, I. V. E., Vrijlandt, I., & Olff, M. (2005). Effects of brief eclectic psychotherapy in patients with posttraumatic stress disorder: Randomized clinical trial. Journal of Traumatic Stress, 18(3), 205–212.

Marks, I., Lovell, K., Noshirvani, H., Livanou, M., & Thrasher, S. (1998). Treatment of posttraumatic stress disorder by exposure and/or cognitive restructuring: A controlled study. Archives of General Psychiatry, 55(4), 317–325.

McDonagh, A., Friedman, M., McHugo, G., Ford, J., Sengupta, A., Mueser, K., Demment, C. C., Fournier, D., Schnurr, P. P., & Descamps, M. (2005). Randomized trial of cognitive-behavioral therapy for chronic posttraumatic stress disorder in adult female survivors of childhood sexual abuse. Journal of Consulting and Clinical Psychology, 73(3), 515–524.

NICE (National Institute for Clinical Excellence) (2005). The Management of PTSD in Adults and Children in Primary and Secondary Care (Vol. 26). Wilshire: Cromwell Press Ltd.

Renfrey, G., & Spates, C. G. (1994). Eye movement desinsitization: A partial dismantling study. Journal of Behavior Therapy and Experimental Psychiatry, 25, 231–239.

Rothbaum, B. O., Astin, M. C., & Marsteller, F. (2005). Prolonged exposure versus eye movement desensitization and reprocessing (EMDR) for PTSD rape victims. Journal of Traumatic Stress, 18(6), 607–616.

Stein, D. J., Ipser, J. C., & Seedat, S. (2006). Pharmacotherapy for post traumatic stress disorder (PTSD). Cochrane Database of Systematic Reviews(1).

Taylor, S., Thordarson, D. S., Maxfield, L., Fedoroff, I. C., Lovell, K., & Ogrodniczuk, J. (2003). Comparative efficacy, speed, and adverse effects of three PTSD treatments: exposure therapy, EMDR, and relaxation training. Journal of Consulting and Clinical Psychology, 71(2), 330–338.

 

35!

35 spins around that shiner,

Happier, luckier, never wiser,

35 more to make it finer,

'til I will my days from a Jason Recliner.

- Enmore, 23 September 2012.

Reflections on the Aetiology, Pathogenesis and Diagnostic Reassignment of Gambling Dysfunctions in the DSM-V

Reflections on the Etiology, Pathogenesis and Diagnostic Reassignment of Gambling Dysfunctions in the DSM-V

Luke Fullagar

RMIT University

Academic debate has not reached a universally accepted conclusion on the etiology and pathology of dysfunctionalgambling. Current theory and empirical research remains uncertain on whether dysfunctional gambling should most parsimoniously be considered a behavioral addiction, an obsessive-compulsive or a disorder of impulse control (APA, 2010).  This poses difficulties for both treatment development and diagnosis.  Moreover, contemporary research has demonstrated that dysfunctional gambling may not form one disorder arising in a homogenous population, but may instead be more accurately explained as a heterogenous group of populations differentiated in etiology, pathogenesis and severity, despite the display of similar phenomenological features (Blaszczynski & Nower, 2002). 

The history of the Diagnostic and Statistical Manual's (DSM) treatment of dysfunctional gambling highlights both the uncertiainty which has pervaded classification, and the development over time in understanding its complex of contributory factors. Based on significantly limited research (Blaszcynski, 2005; Rodda, Lubman & Latage, 2012), a diagnosis of Pathological Gambling was originally included in the DSM-III as a disorder of impulse control. Remodeling of criteria in the DSM-III-R was similarly undertaken with minimal recourse to empirical research (Blaszcynski, 2005) and based on substance abuse characterisations which included items of preoccupation, tolerance, withdrawal and efforts to minimise or eliminate gambling (APS, 2010; Rodda, Lubman & Latage, 2012). This model largely endured in the DSM-IV and is currently the dominant theoretical paradigm (Blaszczynski & Nower, 2002; National Research Council, 1999). However, a line of developing research on gambling uses for mood regulation (e.g. dissociation) and not impulse control (Anderson & Brown, 1984; Jacobs, 1986) was recognised by the addition of a new item 'gambling as a means of escape'.  Important also was Rosenthal's (1989) suggestion in the DSM-IV review process that criteria should account for the progressive nature of dysfunctional gambling, and distinguish between pathological and non-pathological variants. 

Indeed, in the 30 years since the first inclusion of gambling in the DSM, myriad course identifiers and predictive risk factors associated with dysfunctional gambling have been demonstrated, including: access, impulsivity, biological vulnerabilities, behavioural conditioning, emotional-regulation issues, family history, peer group influences and pre-existing psychopathology (Blaszczynski & Nower, 2007; Brewer, Grant, & Potenza, 2008; Toneatto & Nguyen, 2007).   In recent times, a number of multifactorial integrated biopsychosocial models have been advanced in an attempt to coherently assimilate these research findings (APS, 2010). Chief among these is the Pathways Model (Blaszczynski & Nower, 2007) which advances three subtypes differentiated on pathogenesis and increasing severity: (1) behaviourally-conditioned gamblers affected primarily by access, conditioning and cognitive processes; (2) emotionally-vulnerable gamblers for whom behavioral conditioning and erroneous cognitions are intensified by extant psychopatholgy including prior emotional and family disturbances, poor coping skills, low-self esteem, and social isolation, and for whom gambling is also a strategy for mood regulation (e.g. dissociation) and induction (e.g. arousal); and  (3) impulsive anti-social problem gamblers for whom preexisting psychopatholgy, genetic and neurochemical factors interact to intensify impulsivity and need for stimulation (Blaszczynski & Nower, 2002; APA, 2010; Blaszczynski & Nower, 2007). 

However, despite this growing evidence of a complex heterogeneous set of circumstances, it is proposed that the DSM Pathological Gambling diagnosis be reclassified as a one-dimensional behavioral addiction labeled DisorderedGambling in the DSM-V.  Some support exists for an addiction model. Clinical and epidemiological studies demonstrate high comorbidity with substance abuse (Petry, 2005). Problem gamblers also present with excessive preoccupation and urges to gamble despite negative consequences, difficulty with reduction and cessation (cf. Blaszczynski & Nower, 2002), and symptoms of withdrawal and tolerance (XXX; APA, 2010). 

However, this model has also drawn significant critique.  Substances, unlike gambling, directly reinforce cognitive and neurological processes that adapt and develop dependence. Studies observing boredom in participants engaging in moneyless simulated gambling are used as evidence that the arousal to gamble is associated with anticipated wins not the consequence of the direct act itself (Blaszczynski, 2005).  Moreover, it is argued that the chasing behaviour witnessed in dysfunctional gamblers is wrongly paralleled with dose tolerance in substance abuse, and better understood as at attempt to recoup lost money (Blaszczynski & Nower, 2002).  Furthermore, evidence that dysfunctional gambling is often motivated by a range of persistent erroneous and irrational beliefs which disregard logical probability and mutual independence of chance events despite direct and experiential evidence to the contrary (APA, 2010), is used to mount the argument that symptoms of dependence in dysfunctional gambling are of a cognitive rather than addictive nature (Blaszczynski, 2005).

In light of the above, it appears that a one-dimensional behavioral addiction model suggested for the DSM-V is unreflective of the evidence for a heterogenous condition of varying etiology, pathogenesis and severity, and accordingly a premature conclusion on the matter of dysfunctional gambling. While some arguments have been leveled that an addictions model may result in a practical increase in treatment within a professional and lay culture acquainted with the structure of addictions-modelling for other disorders (e.g. Petry, 2006; Potenza, 2006), the potential risks of unwarranted and incorrect stigmatization, slippery-slope arguments for restriction of other social freedoms, and the evidence for variant forms of gambling dysfunction lead to a conclusion that these positives are not outweighed by their disadvantages.

References

Anderson, G., & Brown, R. I. F. (1984). Real and laboratory gambling: Sensation-seeking and arousal. British Journal of Psychology, 75, 401-410.

APS Australian Psychological Society - Gambling Working Group. (2010). Special Report: The Psychology of Gambling. InPsych, 6, 1-15.

Blaszczynski, A. (2005). To formulate gambling policies on the premise that problem gambling is an addiction may be premature. Addiction, 100(9), 1230-1232.

Blaszczynski, A., & Nower, L. (2002). A pathways model of problem and pathological gambling. Addiction, 97, 487-499.

Blaszczynski, A., & Nower, L. (2007). Etiological processes. In G. Smith, D. Hodgins, & R. Williams (Eds.), Research and measurement issues in gambling studies. Elsevier: Toronto. pp.317-338.

Brewer, J. A., Grant, J. E., & Potenza, M.N. (2008). The treatment of pathological gambling. Addictive Disorders Treatment, 7, 1-13.

Jacobs, D. F. (1986). A general theory of addictions: A new theoretical model. Journal of Gambling Behavior, 2, 15-31.

National Research Council (1999). Pathological gambling: A critical review. Washington D.C.: National Academy Press.

Rodda, S. N., Lubman, D. I., & Latage, K. (2012) Problem gambling; aetiology, identification and management. Australian Family Practice, in press.

Petry, N. M. (2005). Pathological gambling: Etiology, comorbidity and treatment. Washington D.C.: American Psychological Association.

Petry, N. (2006). Should the scope of addictive behaviors be broadened to include pathological gambling? Addiction, 101, 152-160.

Potenza, M. (2007). Should addictive disorders include non-substance-related conditions? Addiction, 101,142-151

Rosenthal, R. J. (1989). Pathological gambling and problem gambling. Problems of definition and

diagnosis. In H.J. Shaffer, S. Stein, B. Gambino, and T.N. Cummings, (Eds.), Compulsive gambling: theory, research, and practice. MA, England. Lexington. pp.101-125.

Toneatto, T., & Nguyen, L. (2007). Individual Characteristics and Problem Gambling Behavior. In G.

Smith, D. Hodgins & R. Williams (Eds). Research and measurement issues in gambling studies, Sydney: Elsevier. pp. 92-103. Toneatto, T. & Gunaratne, C. (2009). Does the treatment of cognitive distortions improve clinical outcomes for problem gambling? Journal of contemporary psychotherapy, 39, 221-229.

O'Brien, C. (2011). Addiction and dependence in DSM-V. Addiction. 106(5), 866-867.

The Evolving Role of Psychologists Diagnosis and Management of Alzheimer's Disease in light of Promising Developments in Research on Biomarkers for Brain Amyloid Deposition.

The Evolving Role of Psychologists Diagnosis and Management of Alzheimer's Disease in light of Promising Developments in Research on Biomarkers for Brain Amyloid Deposition.

Luke Fullagar

RMIT University

As biomarker research into Alzheimer's Disease (AD) develops, psychologists will play a critical role in evolving psychological research, assessment tools and interventions to better understand, diagnose, prevent and treat cognitive and behavioral factors at all stages of the disease (in particular, early and presymptomatic stages). Psychologists will also provide essential diagnostic and management services as part of interdisciplinary healthcare teams in allied health settings.

The success of neuropsychological, biomarker and neuroimaging research, and their correlations, demonstrates that AD is a complex disease expressed in both biological and psychological dimensions. Longitudinal findings demonstrate that AD risk factors are genetic, biological and behavioural (Schaie, 2005; Brooks & Loewenstein, 2010), and that there is significant heterogeneity in each factor's pathogenesis and in how each factor relates to the disease at its varying stages (Schaie, 2005; Brooks & Loewenstein, 2010). While significant advances have been made in the prediction of AD using biomarker and neuroimaging techniques, it is neuropsychological and cognitive assessments that will continue to enable these biological results to be linked to clinical symptoms (Rockwood, 2010; APA 2012) – a point highlighted by their almost ubiquitous use as an outcome measure in studies assessing the utility of biological measures (Blacker, et al., 2007; Gomar, et al., 2011; APA 2012).  It is impossible to provide diagnostic, prognostic and disease progression indications specifically related to the cognitive and behavioral aspects of the clinical syndrome with biomarkers alone (Rockwood, 2010).  Accordingly, efficacious developments involving biomarkers will concurrently demand enhancements in the sensitivity of neuropsychological testing and assessment techniques – particularly in early and presymptomatic stages of AD (APA, 2012).  Indeed, as biomarker research progresses, neuropsychological assessment and evaluation will be required in corroborating evidence of AD onset, functional expression, rate of decline, functional capacity and success in response to biomarker therapies (APA, 2012).

Biomarker research has demonstrated particularly successful results in predicting development to mild cognitive impairment and AD from healthy populations (Graff-Radford et al., 2007; Stomrud et al., 2010; Lo et al., 2011; Jack, Knopman & Jagust, 2010), and the possibility of using biomarkers in early detection, and in identifying at-risk people at a presymptomatic stage, holds considerable promise (Brooks & Loewenstein, 2010).  However, while biomarker research is impressively sensitive, specificity results are mixed – making uncertain whether biomarkers can yet accurately distinguish between etiologically distinct dementias (Rockwood, 2010). This is of particular importance given AD pathology often arises without manifest cognitive symptoms during life, and also given many MCI cases do not include AD pathology (Rowe et al., 2010; Brooks & Loewenstein, 2010). In contrast, neuropsychological testing has demonstrated better sensitivity in predicting conversion to AD than most biomarkers (Gomar et al., 2011; Heister et al., 2011; APA, 2012), and when coupled with serial functional assessment remains the 'gold standard' for differential diagnosis in discriminating between AD from age-related cognitive decline, cognitive difficulties related to psychiatric or medical morbidities, and other related disorders (APA, 2012; Brooks & Loewenstein, 2010).  As biomarker research develops, it is hoped that interdisciplinary assessments will evolve to fill the specificity gap and enhance diagnosis and prognosis. Indeed, given biological testing and psychological evaluation and assessment each provide unique information and variance, it is no surprise that recent studies have demonstrated that their combination across serial assessments predicts progression from MCI to AD better than either technique in isolation (Landau, 2010).

As interdisciplinary approaches evolve, there will be increased demand for psychologists to provide, exchange and integrate diagnostic, prognostic and disease progression information alongside other allied health providers, and specifically, the medical profession (APA, 2012).  Psychologists will not only be essential service providers in this model, but are also well poised to contribute to research on enhancing communication between health providers, patients and caregivers, and tailoring 'best-practice' interactions for these parties (APA, 2012).

Early detection on the basis of amyloid deposition raises the concern that people may suffer needless stress before any cognitive, behavioral or neurodegenerative symptoms are identified (APA, 2012). Psychologists will be required to develop counseling and support approaches for these patients and educational approaches which counter risks of avoidance and denial, and enhance proactive engagement with diagnosis (APA, 2012). Moreover, biomarker research will also not replace cognitive and behavioral prevention strategies, which will continue to be successfully administered to at-risk and early-diagnosed people by psychologists. Psychologists are well-poised to provide educational interventions to alert those at potential risk to empirically-validated modifiable risk factors for AD (midlife obesity, smoking, depression, cognitive and physical inactivity, low-educational attainment) (Barnes & Yaffe, 2011), as well as behavioral therapies to reduce the incidence of these risk factors (APA, 2012).  Lifestyle behavior research has shown promising results for prevention, both in linking cognition and exercise (Colcombe et al, 2003), and also in respect of cognitive training programs (Smith et al., 2009; Basak, Boot, Voss & Kramer, 2008) (APA, 2012). 

Where the disease does progress, psychologists are also essential in assisting patients, family and carers develop advanced care planning, and in administering psychotherapeutic interventions designed to manage patient and caregiver stress, adjustment and acceptance, and coping with difficult behavioral alterations (APA, 2012). Research has shown that multiple psychologist-led face-to-face educational sessions are the most effective way to develop advanced care plans (Bravo, Dubois & Wagneur, 2008; APA, 2012). This is no small concern given 40% do not pursue advance care planning even when medical practitioners and social workers are involved (Garand, Dew, Lingler & DeKosky, 2011; APA, 2012). 

At later stages of AD, behavioral interventions are also effective in addressing negative emotional and social outcomes (Teri, McCurry, Logsdon & Gibbons, 2005), and are of critical importance given the limited efficacy of medication treatment in these populations (Sink, Holden & Yaffe, 2005; AGS, 2011). Psychologists also assist in the provision of optimal stimulation and positive engagement for late-stage AD patients for whom apathy is a central behavioral and emotional challenge (Lin et al, 2009; APA 2012). 

Evidence-based interventions for the health and wellbeing of carers and family have also been successful addressing caregiver burdens (predominantly depression), and are an example of interdisciplinary programs which combine remote access medical treatment with integrated allied health teams to provide acute psychological and social supports (Eisdoerfer et al., 2003; Finkel et al., 2007; APA, 2012).  Across the spectrum of AD management services, psychologists will remain critical service providers, and will continue to develop and administer essential neuropsychological and cognitive tests and functional assessment protocols, assess decision making capacity, develop evidence-based interventions to address differentiated forms of age-related cognitive decline, and educate patients and families on the nature and progression of AD (APA, 2012).

AD is a multifaceted disorder which has expression and effects which are biological, psychological and social. Psychologists will be required to adapt and integrate with biomarker and neuroimaging evidence in an interdisciplinary future which reflects in this complexity.

 

References

 

AGS, American Geriatrics Society (2011). Guide to the Management of Psychotic Disorders and Neuropsychiatric symptoms of dementia in older adults. Retrieved September 3, 2012 from http://dementia.americangeriatrics.org/GeriPsych_index.php#1

APA, American Psychological Association. (2012). APA Comments on the Draft Framework for the National Plan to Address Alzheimer's Disease. Submission to the consultation on the National Plan to Address Alzheimer's Disease. Washington, DC, USA. Retreived September 3, 2012 from http://www.apa.org/pi/aging/resources/alzheimer-comments.pdf

Barnes, D.E. & Yaffe, K. (2011). The projected effect of risk factor reduction on Alzheimer's Disease prevalence. Lancet Neurology, 10, 819-828.

Basak, C., Boot, W.R., Voss, M., & Kramer, A.F. (2008). Can training in a real-time strategy videogame attenuate cognitive decline in older adults? Psychology and Aging, 23, 765-777.

Blacker, D., Lee, H., Muzikansky, A., Martin E., Tanzi, R., McArdle, J., Moss, M., & Albert, M. (2007). Neuropsychological measures in normal individuals that predict subsequent cognitive decline. Archives of Neurology, 64, 862-871.

Bravo, G. A., Dubois, M.-F., & Wagneur, S. (2008) Assessing the effectiveness of interventions to promote advance directives among older adults: A systematic review and multi-level analysis. Social Science & Medicine, 67, 1122–1132

Brooks, L.G. & Lowenstein, D.A. (2010). Assessing the progression of mild cognitive impairment to Alzheimer's disease: current trends and future directions. Alzheimer's Research and Therapy, 2(28), 1-9.

Colcombe, S. J., Erickson, K. I., Raz, N., Webb, A. G., Cohen, N. J., McAuley, E., & Kramer, A. F.  (2003). Aerobic fitness reduces brain tissue loss in aging humans. The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences, 58, 176-180.

Garand, L. , Dew, M. A., Lingler, J. H.,  & DeKosky, S. T. (2011) Incidence and predictors of advance care planning among persons with cognitive impairment. American Journal of Geriatric Psychiatry, 19(8), 23-30.

Gomar J. J., Bobes-Bascaran, M. T., Conejero-Goldberg, C., Davies, P., & Goldberg, T. E. & Alzheimer's Disease Neuroimaging Initiative (2011). Utility of combinations of biomarkers, cognitive markers, and risk factors to predict conversion from mild cognitive impairment to Alzheimer disease in patients in the Alzheimer's Disease neuroimaging initiative. Archives of General Psychiatry, 68, 961-969.

Eisdorfer, C. E., Czaja, S. J., Loewenstein, D. L., Rubert, M. P., Arguelles, S., Mitrani, V., & Szapocznik, J. (2003). The effect of a family therapy and technology-based intervention on caregiver depression. The Gerontologist, 43, 521-531.

Finkel, S.I., Czaja, S.J., Schulz, R., Martinovich, Z., Harris, C., & Pezzuto, D. (2007). E-Care: A Telecommunications technology intervention for family caregivers of dementia patients. American Journal of Geriatric Psychiatry, 15, 443-448

Graff –Radford, N.R., Crook, J.E., Lucas, J., Boeve, B.F., Knopman, D.S., Ivnik, R.J., Smith, G.E., Younkin, L.H., Petersen, R.C., Younkin, S.G. (2007). Association of low plasma Aβ42/Aβ40 ratios with increased imminent risk for mild cognitive impairment and Alzheimer disease. Archives of Neurology, 64, 354-362.

Heister, D., Brewer, J., Magda, S., Blennow, K., McEvoy, L., & for the Alzheimer's Disease Neuroimaging Initiative. (2011). Predicting MCI outcome with clinically available MRI and CSF biomarkers. Neurology, 77, 1619-1628.

Jack, C.R., Knopman, D.S. & Jagust, W.J. (2010). Hypothetical Model of dynamic biomarkers of the Alzheimer's pathological cascade. Lancet Neurology, 9(1), 119-128.

Landau, S.M., Harvey, D., Madison, C.M., Reiman, E.M., Foster, N.L., Aisen, P.S., Petersen, R.C., Shaw L.M., Trojanowski, J.Q., et al. (2010) Comparing predictors of conversion and decline in mild cognitive impairment. Neurology, 75, 230-238.

Lin, L., Wu, S., Kao, C., Tzeng, Y., Watson, R., & Tang, S. (2009). Single ability among activities of daily living as a predictor of agitation. Journal of Clinical Nursing, 18, 117-123.

Lo, R.Y., Hubbard, A.E., Shaw, L.M. Trojanwski, M.D., Petersen, M.D., Aisen, P.S., Weiner, M, W, Jagust, W. J. (2011). Longitudinal change of biomarkers in cognitive decline. Archives of Neurology, 68(10), 1257-1266.

Rockwood, K. (2010). Con: Can biomarkers be gold standards in Alzheimer's disease? Alzheimer's Research and Theory, 2, 16-24.

Rowe, C.C., Ellis, K.A., Rimajova, M., Bourgeat, P., Pike, K.E., Jones, G., Fripp, J., Tochon-Danguy, H., Morandeau, L.,et al. (2010) Amyloid imaging results from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging. Neurobiology of Aging, 31.1275-1283.

Sink K. M., Holden, K. F., & Yaffe, K. (2005). Pharmacological treatment of neuropsychiatric symptoms of dementia: A review of the evidence. Journal of the American Medical Association, 293, 596-608.

Smith, G. E., Housen, P., Yaffe, K., Ruff, R., Kennison, R. F., Mahncke, H. W., & Zelinski, E. A. (2009). A cognitive training program based on principles of brain plasticity: Results from the improvement in memory with plasticity-based adaptive cognitive training (IMPACT) study. Journal of the American Geriatrics Society, 57, 594-603.

Schaie, K. W. (2005). Developmental influences on adult intelligence: The Seattle Longitudinal Study. New York, NY: Oxford University Press.

Stomrud, E., Hansson, O., Zetterberg, H., Blennow, K., Minthon, L., Londos, E. (2010). Correlation of longitudinal cerebrospinal fluid biomarkers with cognitive decline in healthy older adults. Archives of Neurology, 67, 217-223.

Teri, L., McCurry, S. M., Logsdon, R., & Gibbons, L. E. (2005). Training community consultants to help family members improve dementia care: a randomized controlled trial. The Gerontologist, 45, 802–811.

 

 

 

 

Rogers Sings Rogerstein

http://www.thepresentparticiple.blogspot.com