Accreditation News!

WKPIC is elated to announce that we discovered this on APA’s website today, thanks to former intern David Wright:

 

Western Kentucky Psychology Internship Consortium – Hopkinsville, KY – Effective December 9, 2014
Next site visit 2021

At its meeting on March 19-22, 2015, the APA Commission on Accreditation reviewed the psychology internship program at theWestern Kentucky Psychology Internship Consortium and voted to approve initial accreditation, with the next site visit scheduled 7 years from the date of the program’s last site visit. The 7 year decision is based on CoA’s professional judgment of compliance or substantial compliance with all domains of the Guidelines and Principles for Accreditation (G&P). No serious deficiencies.

 

Reaching for Success

 

 

Article Review: Group CBT for Psychosis

 

 

Cognitive Behavior Therapy for Psychosis (CBTp) is considered an effective intervention that is recommended for the treatment of schizophrenia (American Psychological Association, 2004). With that said, offering treatment during an acute episode, while in an inpatient facility proves challenging. Even still, group intervention for psychosis has shown to increase outreach and streamline treatment (Owen et al., 2015).

 

Though there is support for group CBTp, evidence is not definitive.  More specifically, the literature indicates mixed results in the effectiveness of group CBTp as compared to other interventions (i.e., social skills training, psychoeducation). Consequently, due to no clear heterogeneity within CBTp models or use of outcome measures, it is difficult to compare results across studies.  Furthermore, other limitations emerge when attempting a controlled trial in an inpatient setting.  For example, the timing of interventions (individuals are typically in a crisis), uncertainty of the length of stay, and typical medication changes upon admission are noteworthy concerns (Owen et al., 2015).

 

While considering the limitations, research shows positive findings for group CBTp through improvement in one’s wellbeing and reduced readmission rates (Svensson, Hansson, & Nyman, 2000; as cited in Owen et al., 2015).  Furthermore, these positive result are aligned with a recovery model, in that gains are not signified through the reduction of psychotic symptoms, but are more so related to the functional gains made by the individual (e.g., increased confidence, understanding, and improved quality of life; Owen et al., 2014). As noted by Owen et al. (2015), improvements related to recovery are influential in determining discharge; in other words, the ability to cope effectively may be more important than a reduction in symptoms (Owen et al., 2015).

 

Consistent with a recovery model, Owen et al. (2015) created a quasi-experimental design to assess the effects of CBTp within an inpatient setting. The program attempted to balance the reduction of symptoms and the empowerment of individuals by increasing control and understanding of experiences.  Thus, they hypothesized that participants receiving group CBTp would show reductions in distress, improvements in confidence about their mental health, and a reduction in positive symptoms of psychosis compared to Treatment as Usual (TAU).

 

Briefly, Owen et al. (2015) compared two groups of participants from acute inpatient units, one group received a four-week group on CBTp and the other group received TAU.  There were 113 participants (80 men, 33 women) between the ages of 19 and 66, with the majority classified as “White British,” and from an impoverished geographic area.  Participants included individuals experiencing psychotic symptoms (e.g., hallucinations, delusions, paranoia). Groups were conducted for 1.5 hours, over four consecutive weeks.  CBTp groups were co-facilitated by a clinical psychologist, a “service user,” a person with personal experience of psychosis and recovery, and unit staff.  Groups consisted of no more than eight participants and were closed.  They collected data over three periods:  at baseline, post-intervention, and a one-month follow-up.  Individuals discharged during the group were invited back to attend, and if discharged before the one-month follow-up, they were sent the measures for data collection.

 

The group intervention was based on Clarke and Pragnell’s (2008) inpatient group CBTp program.  The program consisted of four sessions with different topics, handouts, and homework (Owen et al., 2015).  Session one focused on group rules, psychoeducation of psychotic experiences, normalization, and monitoring skills.  Session two addressed the understanding of experiences within a CBT model. Specifically, session two introduced the use of a continuum for shared and personal experiences as related to symptom monitoring, worked on the identification of triggers, and discussed how the interpretation of events influence emotions and behaviors.   Session three focused on coping skills, differences in distractions and focusing, and introduced mindfulness and breathing.  Finally, session four explored how to make sense of experiences, introduced the stress-vulnerability model, and understanding psychosis.

 

Findings indicated encouraging results regarding the effects of group CBTp.  First, participants in the CBTp group showed greater reductions in distress at follow-up.  Though this finding was not consistent overall, the results remain consistent with a recovery model.  For individuals in the CBTp group, confidence improved from baseline to post-intervention, and at follow-up.  The author’s noted that insufficient data were collected to measure reduction in positive symptoms, but data indicated a trend, in that individuals in the CBTp group showed a decrease in symptoms overtime (Owen et al., 2015).

Qualitative analyses conducted by Owen et al. (2015) further indicated positive gains from the CBTp group.  Many participants reported feeling more positive, confident, and hopeful about the future.  They reported increased coping strategies and acknowledgment that the group helped some understand their experiences differently.  Again, such results are consistent with a recovery model for psychosis, in that the CBTp group demonstrated an increase in confidence more so than a mere reduction in symptoms (Owen et al., 2015).  In essence, the group members were learning how to “cope with, and accept, difficult and frightening experiences, rather than attempting to reduce their occurrence” (Owen et al., 2015, p. 83).

 

Further analyses indicate a positive correlation for this sample between distress and type of admission, noting that individuals first admitted voluntarily, and later adjusted to involuntary status showed the most distress (Owen et al., 2015).  Though distress can decrease over time, regardless of intervention, the findings indicate that group intervention during the crisis period helped some maintain improvement in distress after the crisis subsided and possibly during discharge (Owen et al., 2015).

 

Limitations of a high drop-out rate (62.8%), inability to randomize participants into groups, and unit staff noted to be more interested in helping with the CBTp group than TAU may have mitigated the results of the study (Owen et al., 2015).  Furthermore, the authors acknowledged that due to the limitations in design and high attrition rates, the findings should be considered interesting and not definitive (Owen et al., 2015).  Overall, Owen et al.’s (2015) results indicate that CBTp may decrease distress and enhance confidence for individuals suffering from psychosis.  They note that the intervention used was feasible, acceptable, as well as, valued by the participating staff.

 

Though limited by design due to constraints of an inpatient facility (e.g., discharge, acute/crisis presentation, medication changes) the results indicate group CBTp to be consistent with a recovery model and particularly focused on hope, normalization, and overall improvement in quality of life.

 

References
American Psychological Association. (2004). Practice Guidelines for the Treatment of Patients with Schizophrenia (2nd ed.). Retrieved from http://psychiatryonline.org/guidelines

 

Clarke, I., & Pragnell, K. (2008). The Woodhaven ‘What is real and what is not?’ group programme: A psychosis group in four sessions for an impatient unit.  Retrieved from http://www.isabelclarke.org/psychology/index.htm#CBT

 

Owen, M., Sellwood, W., Kan, S., Murray, J., & Sarsam, M. (2015). Group CBT for psychosis: A longitudinal controlled trial with inpatients. Behaviour Research and Therapy, 65, 76-85. doi: 10.1016/j.brat.2014.12.008

 

Dannie S. Harris, M.A., M.A., M.A.Ed., Ed.S.
WKPIC Practicum Trainee

Friday Factoid: Can a Computer Know You Better Than Your Spouse?

 

There is no way–NO WAY–that a computer can be a more accurate, better judge of an individual’s personality than other people, right? RIGHT??

 

Well, results yielded from a new research study conducted by Cambridge University is implicating just that. But whoa, how can this be? I mean computers are great with statistics and numbers, you know, hard data. But how can a computer effectively assess something as utterly intangible and ludicrously abstract as personality? Impossible, yeah?

 

Well, according to this research, it is quite possible. In this specific case, computers used one specific metric to assess an individual’s personality: Facebook Likes. Results from this study demonstrated that by assessing a person’s Facebook Likes, a computer model was able to predict an individual’s personality more accurately than most of that person’s own family and friends. If the computer was given a sufficient amount of Likes to analyze, only an individual’s spouse could parallel the computer’s accuracy of personality (as measured by broad psychological traits).

 

Let’s examine some of the results, shall we? Given a mere 10 likes, computers could assess an individual’s personality better than a colleague. Given 70 likes, the computer was more accurate than a friend or roommate. Given 150 Likes to analyze, the computer was more accurate than a parent or sibling. And given 300 Likes, a computer could more accurately predict an individual’s personality than a spouse. Since the average Facebook user has approximately 227 Likes, the computers have no shortage of data to analyze.

 

In this study, researchers used a sample of 86,220 individuals on Facebook that completed a 100 item personality questionnaire (from a myPersonality app) and provided access to their Facebook Likes. From the self-reported personality test, scores were generated based on the “Big Five” personality traits (also called the OCEAN model): openness, conscientiousness, extraversion, agreeableness, and neuroticism. The researchers were able to establish which Likes equated with higher levels of specific traits; for example, a Like of “meditation” showed a higher degree of openness. The aforementioned myPersonality app then gave users the option of inviting others (such as friends and family) to assess the psychological traits of the user via a shorter version of the personality test. The results from people the individual knew and the computer were assessed.

 

Shockingly, the computer came closer to the results from an individual’s self-reported personality than close friends and family members.  It seems that the artificial intelligence depicted in the science fiction genre isn’t as far off in the future as we may have believed…

 

Nauert, R. (2015). Computers Better Than Humans for Assessment of Personality?. Psych Central. Retrieved on January 19, 2015.

 

Faisal Roberts, MA
WKPIC Doctoral Intern

 

Friday Factoid: Origin of New Year’s Resolutions

We are now a little past one week into the new year of 2015. Did you make a New Year’s Resolution? If so, how well have you done with keeping it? I have never personally made one, for reasons that I’m unsure of. I didn’t decide to never make them; I just haven’t for whatever reason. Thinking about all of this made me wonder about the origin of making resolutions. Where did this custom start? When beginning my search, I expected a myriad of contradicting answers with the specific origin being evasive and somewhat ambiguous. However, from the little research that I’ve conducted, the answer appears generally consistent amongst a few different sources.

 

Before New Year’s was celebrated in January, it was celebrated in what we now know as the month of March by the Babylonians nearly 4,000 years ago. This time period was chosen as the start of the New Year as it was the beginning of spring time when the leaves come back and the crops grow, hence why it was a logical choice for them (Blaire, 2006). The Babylonians made promises to their gods at the beginning of the year, with promises to repay their debts and return borrowed objects. The Romans changed New Year’s to January in 153 B.C. (Blaire, 2006), named after one of their gods, Janus, the two faced god that could look backward at the old year while simultaneously looking forward at the new year (Petro, 2015). As opposed to returning objects and repaying debts, their resolutions generally regarding treating each other better.  Today, New Year’s Resolutions can encompass a wide variety of areas, but with personal improvement being the center (Blaire, 2006; Petro, 2015). Common resolutions include those pertaining to fitness, finances, altruism, kindness, charity, volunteer work, career goals, reading habits, learning new skills, giving up vices, etc. 

 

What do you think of New Year’s Resolutions? Is it a great way to kick off the new year with a positive mentality? A pointless endeavor that leads people to feel bad when they invariably fail on their goals? Or somewhere in the middle? Either way, belated happy new years from all of us at WKPIC!

 

Blaire, Gary, R. (2006). The History of New Year’s Resolutions. As retrieved from: http://ezinearticles.com/?The-History-of-New-Years-Resolutions&id=245213

 

Petro, Bill. (2015). History of New Year’s Resolutions: Where Did They Begin?
As retrieved from: http://billpetro.com/history-of-new-years-resolutions

 

Faisal Roberts, MA
WKPIC Doctoral Intern