Friday Factoids: Effective Parenting

In a press release for the American Psychological Association, Hamilton (2015) reviewed Larzelere’s presentation on effective parenting.  Larzelere and his research team interviewed 102 mothers who described five times they disciplined their toddlers (ages 17 months to 3 years) for hitting, whining, defiance, negotiating, or not listening.  The findings indicated that regardless of the type of behavior, compromising was the most effective for immediate behavioral improvement.  For mildly annoying behaviors, reasoning was the next most effective.  Punishments (e.g., timeout or taking away something) were more effective than reasoning for defiance or hitting; yet punishments were least effective for negotiating or whining.  Additionally, reasoning was not effective for defiance or hitting.

 

When interviewed two months later, a different pattern emerged.  Children were reportedly acting worse when mothers too frequently used compromising for hitting or defiance.  Reasoning was reportedly the most effective over time, even though it was noted to be the least effective for these behaviors when used immediately.  For defiant children, a moderate use of timeouts and other punishments resulted in improved behavior.

 

Hamilton (2015) also discussed Cipani’s research on punishment.  Capani indicated that often timeouts do not work because they are not used properly.  For example, spur of the moment timeouts are noted to not be effective. Capani indicated that children should know ahead of time what behaviors result in timeout and that consistent use of time out for specified behaviors has shown to significantly reduce problem behaviors.

 

Consequences of parental discipline style has been linked to both internalizing (e.g., withdrawal, anxiety, depression) and externalizing  (e.g., aggression, delinquency, hyperactivity) behaviors in youth (Parent, McKee, & Forehand, 2016).  Harsh discipline (e.g., physical or corporal punishment [hitting or spanking when angry]) often reinforces oppositional behavior (Granic & Patterson, 2006, as cited in Parent et al., 2016) and models hostile interaction patterns (Pettit et al., 1993, as cited in Parent et al., 2016).  With regard to lax discipline (permissiveness and inconsistency), permissiveness often results in both internalizing and externalizing behaviors in children, where as inconsistency is associated with the development of more externalizing behavior than internalizing behavior (Parent et al., 2016).

 

Seesaw discipline, which is considered both harsh and lax, has been linked to high levels of internalizing problems in youth (Parent et al., 2016).   Though parental education often focuses on the consequences of harsh and permissive discipline, it may be beneficial to discuss seesaw discipline as well, and paying close attention to the consequences of youth internalizing behaviors (Parent et al., 2016).

 

Further consideration related to parents suffering from psychopathology may also need to be discussed. Research has indicated that parents with psychopathology tend to create chaotic and unpredictable home environments, which may be aligned with inconsistent parental discipline (Parent et al., 2016); thus, psychoeducation and training for this population may be beneficial.

 

Dannie S. Harris
WKPIC Doctoral Intern

 

References

Hamilton, A. (2015). Punishing a child is effective if done correctly.  Retrieved from http://www.apa.org/news/press/releases/2015/08/punishing-child.aspx

 

Parent, J., McKee, L. G., & Forehand, R. J. (2016). Seesaw discipline: The interactive effect of harsh and lax discipline on youth psychological adjustment. Journal of Child and Family Studies, 25, 396-406.

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Article Review: Cannon, T. D., Yu, C., Addington, J., Bearden, C. E., Cadenhead, K. S., Cornblatt, B. A.,…Kattan, M. W. (2016). An individualized risk calculator for research in prodromal psychosis.

 

Psychosis has been described as a terrifying experience that has been associated with shame, guilt, and humiliation (National Alliance on Mental Illness [NAMI], 2011).  As indicated by NAMI (2011) delay in assessment, identification, diagnosis, and treatment for psychosis is a public health crisis, for which efforts of prevention and early intervention are now being emphasized throughout communities. Therefore, understanding the onset of psychosis is necessary.

 

For the majority of individuals there is a period prior to the onset of psychosis during which individuals begin to exhibit changes in beliefs, thoughts, and perceptions (Cannon et al., 2016). Though not a diagnosis, according to the Center for the Assessment and Prevention of Prodromal States (CAPPS; 2011) this period of time is the prodromal period and could last from a couple of days to years. It is during this time that the subtle changes are said to represent “attenuated forms of delusions, formal thought disorder and hallucinations” (Cannon et al., 2016, p. 1).  Individuals with such an onset or prodromal psychosis are designated high-risk and over a 2-year period, about 20% to 35% of these individuals go on to develop full psychotic symptoms (Cannon et al., 2016, pg. 1). As a result, Cannon et al. (2016) created a risk calculator to calculate the probability of conversion to psychosis among individuals identified with prodromal psychosis.

 

Cannon et al. (2016) emphasized that past research has investigated risk factors for conversion (e.g., demographic factors, symptoms), yielding high predictability and specificity, yet low sensitivity for the identification of conversion.  Their current research focused on the ability to scale risk during initial patient contact by using easily accessible clinical, cognitive, and demographic variables.  The study utilized data from the second phase of the North American Prodrome Longitudinal Study from 2008 to 2013.  Participants in this study participated in the Structured Interview for Prodromal Syndromes (SIPS) and the Structured Clinical Interview (Diagnostic and Statistical Manual- [DSM] IV).  Individuals with substance dependence, neurological disorders, an estimated IQ below 70, or past diagnosis of a psychotic disorder were excluded from the study. Follow-up evaluations were schedule for every 6-months for 2 years. Participants were identified as having high-risk syndromes (attenuated psychotic symptoms syndrome, brief intermittent psychotic symptom syndrome, and familial risk and deterioration syndrome).  The final cohort consisted of 596 participants, who were followed up to the point of conversion to psychosis or up to 2 years.

 

By assessing the importance of each predictor variable, Cannon et al. (2016) created a risk calculator by “using time-to-event proportional hazards regression” (p. 2). The authors identified eight predictor variables apriori:  age; SIPS items P1 and P2; Brief Assessment of Cognition in Schizophrenia (BACS), symbol coding raw score; Hopkins Verbal Learning Test-Revised, scores summed; stressful life events; family history of psychosis; a decline in functioning as shown on the Global Functioning Social Scale; and trauma history.  More specifically, the SIPS items P1 and P2 assess unusual thought content and suspiciousness, which, per Cannon et al. (2016), for high-risk individuals have shown to be strongly predictive of psychosis.  Additionally, the literature has demonstrated that slower processing speed, lower verbal learning, and memory functioning are predictive of conversion (Cannon et al., 2016).  A decline in social functioning prior to conversion, childhood traumas, and stressful life events have also been shown to be predictive of psychosis in high-risk individuals. The Research Interview Life Events Scale and the Childhood Trauma and Abuse Scale were used to assess traumatic experiences. Finally, family history of psychosis was included though the authors indicated the literature does not support this factor as a “robust predictor” of conversion (p. 3). Regardless it was included due to the elevated risk compared to individuals with no familial history.

 

The results indicated that within the 2-year period, 84 individuals in the sample converted to psychosis. The mean time to conversion was 7.3 months. A 16% probability of conversion was reported. The overall model’s C-index was 0.71.  Overall, the authors concluded that high levels of suspiciousness and unusual thought, decline in social functioning, lower verbal learning and memory performance, slower speeds of processing, and a younger age at baseline created a higher risk for conversion to psychosis. The variables of stressful life events, trauma, and family history were not predictive of conversion.

 

Given that this study used an established database, generalizability could be a concern. The authors argue for “predictive inference” (p. 4), due to the community based service centers used in the establishment of the database. Still, for clinical utility, each respective client should be assessed regarding relative fit to the sample.  Additionally, the authors report that the output for the risk calculator is without a confidence interval.  Thus, individuals are provided a percentage for conversion risk, which is taken without consideration of error or a range of values. As such, there is concern of patient distress if the risk calculator yields a relatively high conversion probability. The authors note the benefit of utilizing the risk calculator for identifying research participants (e.g., meeting a particular threshold), utilizing this risk calculator to communicate risk relative to treatment, and to identify the cost-benefit ratio related to treatment options.  The risk-calculator did not include biological factors, and with future research may need to be amended to accommodate other factors that are predictive of conversion.

 

Overall this tool is related to early identification of risk, yet it appears to be more so applicable to research studies.  The authors further note that a decision tree has been installed to ensure that individuals who use the risk calculator are in fact professionals that have conducted a SIPS interview and the client has a diagnosis of a prodromal risk syndrome.  This risk calculator appears to be a practical tool, but clinical utility may be equivocal due to concerns of reporting risk of conversion to clients and not providing a probability of remission.  The risk calculator is aligned with early intervention. Knowing the probability of conversion may help encourage clients to engage in treatment and help clinicians or researchers recommend treatment options best aligned to meet the client’s needs.

 

Dannie S. Harris
WKPIC Doctoral Intern

 

References
Cannon, T. D., Yu, C., Addington, J., Bearden, C. E., Cadenhead, K. S., Cornblatt, B. A.,…Kattan, M. W. (2016). An individualized risk calculator for research in prodromal psychosis. American Journal of Psychiatry. Advance online publication. http://dx.doi.org/10.1176/appi.ajp.2016.15070890

 

Center for the Assessment and Prevention of Prodromal States. (2011). What is the Prodrome? Retrieved from https://www.semel.ucla.edu/capps/what-prodrome

 

National Alliance on Mental Illness. (2011). First episode: Psychosis, results from a 2011 NAMI survey. Retrieved from http://www.nami.org/psychosis/report

 

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Friday Factoids: Diagnosing Early-Onset Schizophrenia

 

 

Early-onset Schizophrenia is defined by an onset prior to adulthood, with an onset prior to 12 years of age being rare (Vyas et al., 2011). The Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American Psychiatric Association, 2013) identifies early onset as being associated with a worse prognosis. The DSM-5 further emphasizes that childhood schizophrenia is more difficult to diagnosis, where as compared to adults, “childhood delusions and hallucinations may be less elaborate” (p. 102), and visual hallucinations should be “distinguished from normal fantasy play” (p. 102).  Furthermore, hallucinations are not uncommon in both healthy children and children with a psychiatric illness, yet often with childhood schizophrenia, hallucinations are multimodal (Driver, Gogtay, & Rapoport, 2013). Diagnostic criteria for schizophrenia are “age independent” (Stentebjerg-Olesen, Pagsberg, Fink-Jensen, Correll, & Jeppesen, 2016), which is supported by diagnostic stability throughout the lifespan.

 

Yet there is still ambiguity with differential diagnosis for early-onset schizophrenia.  As noted by Stentebjerg-Olesen, Pagsberg, Fink-Jensen, Correll, and Jeppesen (2016) there is “considerable overlap in phenomenology between schizophrenia and affective symptomatology in children and adolescents with psychosis” (p. 411).  As cited in Stentebjerg-Olesen et al. (2016), Weary (1992) and Masi et al. (2006) the most common diagnostic mistake is a “misclassification of a mood disorder as schizophrenia” (p. 411).  Other diagnostic considerations extend to pervasive developmental disorders, severe personality disorders or traits, posttraumatic stress disorder (PTSD), generalized anxiety disorder, and obsessive-compulsive disorder (Driver et al., 2013).  As such understanding the “developmentally sensitive descriptions of symptomatology, clinical characteristics, and outcome” may offer a clearer diagnostic picture for early-onset schizophrenia (Stentebjerg-Olesen et al., 2016, p. 411).

 

In a systematic review of studies from 1990 to 2014 of early-onset psychosis, Stentebjerg-Olesen et al. (2016) found that hallucinations were mainly auditory (81.9%) and delusions were mostly persecutory and of reference (77.5%). Formal thought disorder was found in 65% of the patients and 36% had disorganized speech or pressured speech.  Negative symptoms were found in about half of the patients, and half of the group with negative symptoms experienced positive symptoms as well.  Comorbidity was high at 32% for substance abuse and 33.5% for ADHD and disruptive behavioral disorders.  Trauma is also thought to play a significant role in early-onset schizophrenia, with Stentebjerg-Olesen et al. (2016) finding a high level of comorbid PTSD (34%).

 

Stentebjerg-Olesen et al. (2016) found that “severity of positive symptoms at baseline, the severity and the persistence of negative symptoms, longer [duration of untreated psychosis], and poorer premorbid adjustment each predicted a worse outcome of illness” (p. 423).  Longer duration of untreated psychosis and poorer premorbid adjustment were also associated with poorer outcomes. In short, patients with early-onset schizophrenia were found to have substantial impairment from positive and negative symptoms, disorganized behavior, and pre- and comorbid conditions and diagnoses.  The authors note that the “high prevalence of negative and disorganized” symptoms “may mask the emergence of psychosis” and delay identification and treatment (p. 424).

 

Dannie S. Harris
WKPIC Doctoral Intern

 

References
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: Author.

 

Driver, D. I., Gogtay, N., & Rapoport, J. L. (2013). Childhood onset schizophrenia and early onset schizophrenia spectrum disorders.  Child and Adolescent Psychiatric Clinics of North America, 22(4), 539-555.  

Stentebjerg-Olesen, M., Pagsberg, A. K., Fink-Jensen, A., Correll, C. U., & Jeppesen, P. (2016). Clinical characteristics and predictors of outcome of schizophrenia-spectrum psychosis in children and adolescents: A systematic review. Journal of Child and Adolescent Psychopharmacology, 26(5), 410-427.

 

Vyas, N. S., Patel, N. H., & Puri, B. K. (2011). Neurobiology and phenotypic expression in early onset schizophrenia. Early Intervention in Psychiatry, 5, 3-14.

 

 

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Huge Congratulations

You did it!

You did it!

 

WKPIC extends warmest congratulations to Dianne Rapsey-Vanburen, for taking her oath today and finishing the arduous process of becoming a United States Citizen!!

 

We are so happy to have you, and your ceremony flowers are beautiful.

 

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Friday Factoids: Early Intervention for First Episode Psychosis

 

 

 

Interventions specific to first episode psychosis have become a significant focus in community mental health.  However, programs directed at early intervention and identification are unable to impact treatment progress if clients are not engaged. In general, disengagement from mental health services is problematic.  Approximately 30% of individuals with first episode psychosis disengage from treatment, which is consequently associated with poorer outcomes (Casey et al., 2016; Robinson et al., 2002).  Thus, identification of factors related to disengagement becomes necessary to influence treatment outcomes.

 

As cited in Casey et al. (2016), research identifying predictive factors related to disengagement and first episode psychosis has been equivocal.  For instance, Singh and Burns (2006; as cited in Casey et al., 2016) found conflicting evidence for disengagement between minority ethnic groups.  Ouellet-Plamondon et al. (2015; as cited in Casey et al., 2016) found immigrant populations were more likely to disengage from treatment.  Clients with a history of childhood physical abuse, alcohol use, violence, and psychopathic traits were also associated with disengagement (Spidel et al, 2010; as cited in Casey et al., 2016).  Though dated, Baekeland and Lundewall (1975; as cited in Casey et al, 2016) found no consistent relationship between engagement and gender, age, living status, marital status, SES, or educational level.  Additionally, little is known about disengagement and the impact of the emergence or chronology of psychosis, as well as symptom attribution or one’s beliefs about mental illness (Casey et al., 2016).  The literature has found conflicting results regarding levels of engagement and the duration of untreated psychosis (Casey et al., 2016).  More recent studies found the strongest association of disengagement is impacted by symptom severity at baseline, duration of untreated psychosis, insight, comorbid substance use, and family support (Doyle et al., 2014).  Doyle et al. (2014) indicated that individuals entering a first episode psychosis program without family support and those who maintain persistent substance use are at higher risk for disengagement.

 

Casey et al. (2016) found that the level of education predicted levels of engagement; where as higher engagement scores were associated with lower levels of education.  Duration of untreated illness (greater than 1220 days) was also a significant predictor for engagement.  In this study, duration of untreated illness was defined as the time period of prodromal onset to treatment compliance (p. 205).  Beliefs about mental illness were also a significant predictor, in that individuals with the belief that social stress is a cause of mental illness and that odd thoughts are associated with mental illness had higher engagement scores.  Though not a predictor, patients living with others had significant higher engagement scores.

 

Overall, Casey et al. (2016) emphasized interventions specific to understanding patient beliefs about mental illness and discussing such beliefs in a non-judgmental manner regarding symptom attributions. Additionally, initiatives targeted at individuals with higher educational levels were also recommended.  Awareness of these factors will provide clinicians with an understanding of the characteristics likely associated with disengagement.  Thus, outreach may need to reflect more active strategies for engaging individuals with these characteristics. As recommended by Heinssen, Goldstein, and Azrin (2014), for individuals with first episode psychosis “assertive outreach, efficient enrollment, and hopeful messages are critical at the time of intake” (p. 8).  First contacts are critical.  Clinicians should be supportive, reassuring, and focus on learning about the individual’s experience of symptoms, the impact of these symptoms on daily life, and how psychosis has impacted family members (Heinssen, Goldstein, & Azrin, 2014).  In addition, establishing a youth friendly environment, offering ongoing education and support, as well as giving consideration to providing services separate from the larger clinic, (if possible with a separate entrance and waiting room) may help positively impact levels of engagement.  Due to the poorer outcomes associated with disengagement, as well as the progressive course of a psychotic illness, every effort should be considered to increase engagement in services.

 

References
Casey, D., Brown, L., Gajwani, R., Islam, Z., Jasani, R., Parsons, H.,…Singh, S. P. (2016). Predictors of engagement in first-episode psychosis. Schizophrenia Research, 175, 204-208.

Doyle, R., Turner, N., Fanning, F., Brennan, D., Renwick, L., Lawlor, E., & Clarke, M. (2014). First-episode psychosis and disengagement from treatment: A systematic review.  Psychiatric Services, 65(5), 603-611.

 

Heinssen, R. K., Goldstein, A. B., & Azrin, S. T. (2014). Evidence-based treatments for first episode psychosis:  Components of coordinated specialty care. Retrieved from http://www.nimh.nih.gov/health/topics/schizophrenia/raise/nimh-white-paper-csc-for-fep_147096.pdf

 

Robinson, D. G., Woerner, M. G., Alvier, J. M. J., Bilder, R. M., Hinrihsen, G. A., & Lieberman, J. A. (2002). Predictors of medication discontinuations by patients with first-episode schizophrenia and schizoaffective disorder. Schizophrenia Research, 57, 209-219.

 

Dannie S. Harris, MA
WKPIC Doctoral Intern

 

 

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Goodbye . . . And Hello!

It is with great fondness and lots of sadness that we bid farewell to this crop of minions . . . I mean, interns. Jon Torres headed home to Kansas City for a post-doctoral position at an inpatient facility, while Rain Smith started a post-doctoral slot at Pennyroyal Center in Hopkinsville. Crystal Bray is staying on with the crew here at Western State as a post-doc, and we’re glad to have her.

 

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BUT, amidst all the parting sorrow, there is joy, because we have sparkly new arrivals!!!

 

Welcome, Dannie, Dianne, and Jennifer!!

 

 

 

 

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And though she has never read Harry Potter, 50 points to Gryffindor on behalf of Dianne, who has already expertly trolled Dr. Greene with a New York Yankees poster. Come on, Dr. G. Expand those sports horizons.

 

 

 

 

 

 

 

 

 

We look forward to an awesome year–and I am impatiently waiting to see what this year’s group comes up with for intern office decorations…

 

 

Susan R. Vaught, Ph.D.
Director, WKPIC

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Friday Factoids Catch-Up: Schizophrenia Symptoms Reduced Through Exercise

 

Schizophrenia symptoms in the acute phase are often characterized by hallucinations and delusions, which are usually treatable with medication. However, most patients are still troubled with pervasive cognitive deficits, which include poor memory, impaired information processing, and loss of concentration. Antipsychotic medications have little impact on improving cognition, and other pharmacological approaches towards treating cognitive deficits have demonstrated limited efficacy thus far. Non-pharmacological interventions have been developed to specifically target cognitive symptoms, including cognitive remediation therapy (CRT). This therapeutic approach involves completing tasks designed to train various cognitive functions such as memory, attention, and problem-solving skills. However, CRT has only a small effect on psychiatric symptoms, and improvements are lost over time.

 

A number of recent meta-analyses have shown that structured exercise can significantly improve positive symptoms, negative symptoms, and social functioning in this population. A meta-analysis study combined the data from ten independent clinical trials with a total of 385 patients diagnosed with Schizophrenia. According to a new study from University of Manchester researchers, around 12 weeks of aerobic exercise training can significant improve patients’ brain functioning. The research showed that patients who are treated with aerobic exercise programs, such as treadmills and exercise bikes, in combination with their medication, will improve their overall brain functioning more than those treated with medications alone. There was also evidence among the studies that programs, which used greater amounts of exercise and those which were most successful for improving fitness, had the greatest effects on cognitive functioning.

 

Furthermore, by increasing cardiorespiratory fitness and metabolic health, exercise may also reduce the physical health problems associated with Schizophrenia, such as obesity and diabetes, which contribute towards reduced life expectancy and adversely affect cognitive functioning. Exercise has also been found to increase hippocampal volume and white matter integrity in healthy older adults and those with Schizophrenia. Additionally, cross-sectional research has demonstrated that physical activity and fitness are associated with better cognitive performance and higher levels of neurotrophic factors which promote brain plasticity. Results from cognitive outcomes showed that exercise improves global cognition significantly more than control conditions. Analyses suggested that supervision from physical health instructors results in better cognitive outcomes. This may be due to increased exercise engagement among participants or better program delivery resulting in more favorable outcomes.

 

Meta-regression analyses indicated that higher weekly duration of exercise tends to be associated with greater improvement in cognition. The amount that an individual exercises appears to be an important factor for achieving cognitive enhancement. Previous studies have shown that the amount of exercise achieved by participants during an intervention is a significant predictor of cognitive improvements. Additional studies have previously examined the relative influence of exercise duration, frequency, and intensity on cognitive improvements following a 12-week exercise program. The result indicated that exercise intensity was the best predictor variable. This also suggests that aerobic exercise may be more effective for cognition in Schizophrenia than yoga, which previous meta-analyses have found to only be effective for long-term memory.

 

This meta-analysis study indicated that exercise has similar effects on cognition in Schizophrenia to CRT. Individual studies have shown significantly greater improvements from combining CRT with aerobic exercise for various cognitive subdomains, along with significantly greater reductions in negative symptoms of Schizophrenia. There is also some preliminary evidence supporting the role of brain-derived neurotrophic factor (BDNF) as a mediating factor for cognitive improvements from exercise.

 

The two other domains, which showed significant changes in response to exercise, were attention and working memory. Since these factors are strong predictors of functional recovery after a first episode of Schizophrenia, implementing exercise interventions from the early stages of illness may facilitate functional recovery. Indeed, exercise may confer even greater benefits in the early psychosis, as cognitive enhancement interventions are more effective at this time than later in the illness. Consistent with this, three recent studies in young patients with first-episode psychosis (aged 23–26) have observed large cognitive improvements from moderate/vigorous exercise after just 10–12 weeks. With the currently limited evidence, it is unclear whether this high level of responsiveness to exercise among first-episode patients is due to their younger age or their earlier stage of illness.

 

References:
Firth, J., Stubbs, B., Rosenbaum, S., Vancampfort, D., Malchow, B., Schuch, F.,…Yung, A.R. (2016). Aerobic exercise improves cognitive functioning in people with schizophrenia: a systematic review and meta-analysis. Schizophrenia Bulletin. DOI: 10.1093/schbul/sbw115

 

Jonathan Torres, M.S.
WKPIC Doctoral Intern

 

(Director’s Note:  We have come to our final Friday Factoids post from the 2015-2016 intern class. Stay tuned for the first offerings of the 2016-2017 crew!)

 

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Friday Factoids Catch-Up: Effects of Multitasking

 

Many business leaders think of multitasking as a great asset and they envision employees who can get more work accomplished. People also believe that the Millennial generation (ages 18 to 34) is better equipped to juggle multiple tasks. For the most part this is true. Millennials are known for being adept with all forms of technology and moving from one job to another, shifting between priorities with relative ease. Most employers post “The ability to multitask” as a skill on several job openings. Unfortunately, the latest research conducted in psychology and business productivity suggests we have gotten it all wrong.

 

The average Millennial switches their attention among media platforms 27 times per hour. Research shows that performing a mental task while multitasking yields similar results to performing the same task if you got no sleep the previous night. Additionally, prolonged multitasking will actually damage your brain. Regular multitaskers have less brain density in areas controlling cognitive and emotional functions. Alternating between tasks will lower your emotional intelligence. If you are switching your gaze from your laptop to your smartphone to a TV screen and back again, you stand to miss a lot of subtle nonverbal signals from the person you are talking with simultaneously. Researchers revealed that the brain cannot effectively handle more than two complex related activities at once.

 

Multitasking doesn’t always live up to the dream. Instead, it tends to mean a lack of focus and an increase in impulsivity. Experts predicted that the impact of networked living on youth today will increase their desire for instant gratification, cause them to settle for quick choices, and cause them to lack patience. Researchers at Stanford University conducted a famous experiment 50 years ago where children were given the chance to eat a single marshmallow immediately, or wait until someone returned later, at which point they would receive a second marshmallow. The kids were tracked later in life and it turns out those who waited for that second marshmallow fared much better than those who chose instant gratification. The participants who did not wait were more likely to have behavioral problems, be obese, use drugs and spend time in jail.

 

There’s a financial cost, too. Lack of productivity due to multitasking equates to global losses of $450 million per year and Millennial job-hopping costs the U.S. economy more than $30 million per year. Nearly nine out of ten Millennials plan to stay in a job less than three years and 21 percent say they have changed jobs in the past year. While the average job tenure for all workers 25 and older is 5.5 years, it is only three years for Millennials. The cost of job-hopping to employers is not marginal, either. The loss of one Millennial employee runs between $15,000 to $25,000, for most companies.

 

In terms of the turnover issue, employers can discourage Millennials from leaving too soon by offering finite terms of employment from the get-go. Giving Millennials a sense of purpose through meaningful work and projects that require a variety of skills has been shown to deter job-hopping. To help reduce the effects of multitasking, you should schedule blocks of uninterrupted time. There is time management method called the Pomodoro Technique that allows you to work for 25-minute chunks of time and then take a five-minute break. During this time you focus all your attention on a single task and take short breaks as a way to increase focus and productivity. Lastly, you can increase the ability to focus, concentrate, and reduce stress throughout the day by practicing either (or better yet, both) yoga or meditation. However you choose to do it, cutting back on or eliminating multitasking is well worth the effort. You will work more productively and finish tasks more quickly.

 

References:
Clapp, W., Rubens, M., Sabharwal, J., Gazzaley, A. (2011). Deficit in switching between functions underlies the impact of multitasking memory in older adults. Proceedings of the National Academy of Sciences of the United States of America. 108(17), 7212-7217.

 

Sanbonmatsu, D., Strayer, D., Medeiros-Ward, N., Watson, J. (2013). Who multi-tasks and why? Multi-tasking ability, perceived multi-tasking ability, impulsivity, and sensation seeking. PLOSOne. 8(1), e54402.

 

Zetlin, M. (2016, July 30). Constant Multitasking Is Damaging Millennial Brains, Research Shows. Retrieved from: http://www.inc.com/minda-zetlin/constant-multitasking-is-damaging-millennial-brains-research-shows.html

 

Jonathan Torres, M.S.
WKPIC Doctoral Intern

 

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Friday Factoids Catch-Up: What Exactly Does Psychosomatic Mean?

When patients who are presenting to physicians for treatment hear the word “psychosomatic” they usually feel immediately discredited. This term is often followed by a referral to see a psychologist, which patients often do not choose to do.

 

First, the term psychosomatic means something different to physicians and most patients than it does to psychologists and mental health professionals. When physicians resort to telling patients they feel their condition is psychosomatic, it is often after much frustration and perceived treatment failures. Physicians note that these patients report very high levels of symptomatology, but testing and evaluations cannot identify concrete pathology. Physicians may also notice that patients seem to be reporting higher levels of symptoms than what seems to make sense in light of physical findings. The model that many physicians were trained in (Cartesian Model) creates a mindset that all medical conditions can be diagnosed with a methodical and logical approach. If this approach yields no solid support to reported symptoms, the problem is determined to be psychosomatic—or essentially not real. Laypeople (patients) typically identify the term psychosomatic in the same context. It can be a painful word for patients to hear and understand, and they often feel insulted by the resultant referral to see a psychologist.

 

Psychologists do not identify the term psychosomatic the same way as physicians and patients may define it. Many psychologists conceptualize health problems from a multi-faceted approach in which physical and biological conditions interact with their environment. “Somatic” research generally approaches physical conditions as inseparable from the mind. This under no circumstances means that psychologists think “every problem” is in the mind. In fact, it means that all systems in which a person functions interact with each other. Chronic pain is an example of a problem in which many systems interact. Emotions have been identified as one factor in decreasing pain tolerance, and biological changes can result from emotional state. So, feelings can make pain worse, and worsening pain increases emotional issues—and the problems can spiral.

 

Explaining to patients that seeing a psychologist is a part of treatment for medical conditions and not a result of practitioners deciding that patients are “faking” or “just emotional,” may help facilitate following up with recommendations. Patients who experience chronic illnesses often feel very misunderstood and disrespected, and more could be done to help patients understand that psychologists may be an instrumental part of their healthcare. This simple step could result in significant improvements in overall outcome for many conditions.

 

Rain Smith, MS
WKPIC Doctoral Intern

 

Posted in Blog, Continuing Education, Current Interns, Friday Factoids, Mental Health and Wellness, Resources for Interns | Tagged , , | Leave a comment

Article Review: The role of psychological symptoms and social group memberships in the development of post-traumatic stress after traumatic injury [Jones et. al. British Journal of Health Psychology(2012) 17, 798-811]

Jones et. al (2012) points out that traumatic injury can be linked with later development of PTSD. It does not seem surprising that PTSD is common after a major physical trauma resulting in orthopedic injuries (OI)  or acquired brain injury (ABI). Unknown variables included which factors might mitigate or limit the development of PTSD after traumatic injury.

 

Jones et.al. discussed the social identity model. The social identity approach looks at how one’s social group memberships contribute to health outcomes. Jones et. al. evaluated two injury groups (OI and ABI) at 2 weeks and again at three months after discharge. The participants were given The General Health Questionnaire (GHQ) to assess somatic symptoms. The Exeter Identity Transition Scales (EXITS) were utilized to assess sense of belonging, connection and support. Finally the Trauma Screening Questionnaire (TSQ) was given to assess post traumatic symptomatology.

 

The researchers found that group memberships seemed to effect OI and ABI differently. Injuries that caused long term life changes seemed to have reduced trauma symptoms when new group membership after the injury was developed. An example of “new group membership” would be joining an ABI support group. The authors theorized that membership in a group that facilitated the changes involved allowed patients to better adjust to their new life circumstances.

 

Jones et. al suggested that for injuries with higher levels of long term disabilities, trauma symptoms may be reduced by health care personnel making appropriate referrals to community services and groups.

 

References
Jones et. al (2012). The role of psychological symptoms and social group memberships in the development of post-traumatic stress after traumatic injury. British Journal of Health Psychology, 17, 798-811

 

Rain Smith, MS
WKPIC Doctoral Intern

 

Posted in Blog, Continuing Education, Current Interns, Mental Health and Wellness, Resources for Interns | Tagged , | Leave a comment