Peer-reviewed journal articles are an essential tool for students, professionals, and researchers in the human services field. Therefore, as a student in this program, you must be able to locate, utilize, and cite peer-reviewed articles. This makes it important for you to understand what it means to be peer-reviewed, how it influences published research, and how it impacts practitioners. For this Discussion, locate and select a peer-reviewed journal article from the Walden Library databases. Reflect on the importance of using peer-reviewed journal articles as a scholar-practitioner in the helping professions.
By Day 4
Post a brief description of the peer-reviewed journal article you selected. Include the title of the article, the name of the database where you located the article, and a link to the article. Then, explain the criteria you used to evaluate whether the journal article you selected was peer-reviewed. Finally, explain the importance of using peer-reviewed journal articles, such as the one you selected, as a scholar-practitioner in your area of practice.
Reminder: Be sure to support your posting and responses with specific references to the Learning Resources and/or current literature. Use APA formatting to cite references in your posting and responses.
Work 54 (2016) 631–637 DOI:10.3233/WOR-162311 IOS Press 631 Exploring resilience and mindfulness as preventative factors for psychological distress burnout and secondary traumatic stress among human service professionals Rachel Harker a, Aileen M. Pidgeon a,∗ , Frances Klaassen band Steven King c aDepartment of Psychology, Bond University, Robina, QLD, AustraliabMercy Family Services, Toowoomba, QLD, AustraliacMercy Family Services, Brisbane, QLD, Australia Received 23 August 2014 Accepted 7 August 2015 Abstract.
BACKGROUND:Human service professionals are concerned with the intervention and empowerment of vulnerable social populations. The human service industry is laden with employment-related stressors and emotionally demanding interactions, which can lead to deleterious effects, such as burnout and secondary traumatic stress. Little attention has been given to developing knowledge of what might enable human service workers to persist and thrive. Cultivating and sustaining resilience can buffer the impact of occupational stressors on human service professionals. One of the psychological factors associated with cultivating resilience is mindfulness.
OBJECTIVE:The aim of this current research is to improve our understanding of the relationship between resilience, mindfulness, burnout, secondary traumatic stress, and psychological distress among human service professionals.
METHODS:The current study surveyed 133 human service professionals working in the elds of psychology, social work, counseling, youth and foster care work to explore the predictive relationship between resilience, mindfulness, and psychological distress.
RESULTS:The results showed that higher levels of resilience were a signi cant predictor of lower levels of psychological distress, burnout and secondary traumatic stress. In addition, higher levels of mindfulness were a signi cant predictor of lower levels of psychological distress and burnout.
CONCLUSIONS:The ndings suggest that cultivating resilience and mindfulness in human service professionals may assist in preventing psychological distress burnout and secondary traumatic stress. Limitations of this study are discussed together with implications for future research.
Keywords: Work, stress, mental health, healthcare workers ∗Address for correspondence: Dr. Aileen M Pidgeon, Depart- ment of Psychology, Bond University, Robina, QLD, Australia.
Tel.: +61 07 55952510; E-mail: email@example.com. 1. Introduction Human service professionals who work to pro- vide intervention and empower the most vulnerable, distressed, and disadvantaged people are routinely 1051-9815/16/$35.00 © 2016 – IOS Press and the authors. All rights reserved 632R. Harker et al. / Exploring resilience and mindfulness as preventative factors confronted with the psychological distress, emotional pain, and traumatic recollections of the individu- als with whom they work . The level of stress that human service professionals experience from these frequent and emotionally charged interactions can lead to psychological distress, burnout, and sec- ondary traumatic stress .
1.1. Psychological distress, burnout and secondary traumatic stress Psychological distress is largely de ned as a state of emotional suffering, characterised by symptoms of anxiety (i.e., feeling tense, nervousness) and depres- sion (i.e., sadness, hopelessness) . Burnout refers to a multifaceted work-related disorder of three dimensions, which include; emotional exhaustion, depersonalisation, and reduced personal accomplish- ment [4, 5]. These dimensions describe feelings of being over-extended, fatigued, and depleted; atti- tudes of negativity and cynicism towards clients or work; and a reduced sense of ef cacy and accom- plishment [6, 7]. Secondary traumatic stress refers to work-related, secondary exposure to traumatic events (i.e., by listening to a client’s traumatic expe- rience in session) and can produce emotional and physical reactions, such as fear, sleep dif culties, intrusive images, and avoidance of reminders of the client’s traumatic experiences [8, 9]. Human ser- vice professionals working with traumatised clients can experience stress, which can be a costly and signi cant source of mental health problems and psy- chological distress [10, 11].
Human service professionals comprise of diverse professionals including psychologists, social work- ers, counselors, youth, and foster care workers. In recent decades, professional quality of life for human service professionals has been a topic of growing interest . Risk and protective factors ofmental ill healthhave been researched, with potential protec- tive factors including resilience and mindfulness .
Mental ill health is often considered an umbrella term that encompasses a continuum from mild to severe symptomology. The term mental ill health includes psychological distress, burnout, and secondary trau- matic stress and is distinct from mental illness that consists of diagnosable disorders such as depression, bipolar disorder, anxiety, or schizophrenia.
In addition to individual effects on mental health and psychological well-being, the organi- sational consequences of burnout among human service professionals include; increased turnover andabsenteeism, unproductive work behaviours, and reduced job-satisfaction . However, these neg- ative outcomes not only effect the organisation but also affect the human services professional’s ability to effectively care for others . Thus, practitioner- focused research has recognised the importance of building resilience in the promotion of psychological well-being and in the preservation of service stan- dards .
1.2. Resilience Resilience has been viewed as a “buffer” which protects individuals from adverse environmental in uences and forces . Although a universal de nition does not exist, resilience considers an indi- vidual’s capacity to overcome adversities that would otherwise be expected to have negative consequences . Individuals with high levels of resilience exhib- ited faster physiological and emotional recovery from stressful life events (i.e., heavy caseloads and stress- ful work conditions) . In a qualitative study of the phenomenon among Australian mental health clinicians, Edward  aptly described resilience as “the ability to bounce back from adversity, persevere through dif cult times, and return to a state of inter- nal equilibrium” [p. 143]. Thus, much research has been directed towards what factors are most effective in buffering against stress and one factor that seems to be most important on the basis of this research is resilience .
1.3. Mindfulness Of the psychological factors thought to contribute to resilience, mindfulness has increasingly gained attention in recent years [20, 21]. Conceptualised as an intentional state of awareness, mindfulness concerns the process of bringing one’s attention to the present moment, in a non-judgmental and accepting manner . Through the practice of var- ious techniques, individuals are able to cultivate a state of mindfulness and develop a number of skills considered to be of transdiagnostic impor- tance . For example, increased mindfulness has been shown to be correlated positively with several aspects of psychological well-being, and negatively associated with burnout and secondary traumatic stress . Research investigating the bene cial effects of increased levels of mindfulness has reported improvements in distress tolerance , emotion reg- ulation skills , and psychological exibility . R. Harker et al. / Exploring resilience and mindfulness as preventative factors633 Furthermore, Shapiro  argues that mindfulness shows promise as a protective factor against burnout and secondary traumatic stress, as mindfulness is associated with a greater ability and willingness to tolerate and accept negative emotions. This notion is supported with results showing that after attending a brief four-week mindfulness intervention health pro- fessionals reported signi cant reduction in symptoms of burnout and improved life-satisfaction .
1.4. Age and gender The research is unclear on the impact that indi- vidual factors, such as age and gender, have on burnout . For example, Ackerley et al.’s  study showed that while age was associated with burnout among psychologists, with younger psychologists experiencing more emotional exhaustion than older psychologists, relationship status, and gender were not. In contrast, Bearse et al.’s  study involving 260 psychologists found that females reported sig- ni cantly greater levels of vicarious traumatisation and compassion fatigue compared to males. Further- more, Sangganjanavanich and Balkin’s  study of 220 counselor educators indicated that neither age nor gender had a signi cant impact on levels of burnout.
Due to the inconsistent ndings to date, this current study examined the relationship between age, gender, and burnout.
1.5. Aim of study The current study explored the predictive relation- ship between resilience, mindfulness, psychological distress, burnout, and secondary traumatic stress among human service professionals. High levels of mindfulness and resilience were hypothesised to sig- ni cantly predict low levels of burnout, secondary traumatic stress, and psychological distress. In addi- tion, high levels of burnout and secondary traumatic stress were hypothesised to signi cantly predict high levels of psychological distress.
2. Method 2.1. Participants The sample consisted of 133 human service pro- fessionals working in the elds of psychology, social work, counseling, youth and foster care work. The age range of the participants was 20 to 64 years(M age = 39.20,SD= 11.13) with 106 (79.7%) female participants and 27 (20.3%) male participants.
2.2. Materials The psychometrically sound questionnaires participants completed to measure psychologi- cal distress, burnout, secondary traumatic stress, mindfulness, and resilience were as follows. The General Well-Being Schedule (GWBS)  an 18-item questionnaire with two subscales that measure psychological well-being and distress.
The psychological distress subscale assesses emotional suffering in terms of anxiety (i.e., rest- lessness, feeling tense) and depressive (i.e., sadness, hopelessness) symptomology. The Professional Quality of Life Scale – Version 5 (ProQOL-5)  a 30-item scale with two subscales; the burnout subscale which assesses exhaustion, frustration, anger, and depression typical of burnout and the secondary traumatic stress subscale which assesses negative feelings driven by fear and work-related trauma. The Resilience Factor Inventory (RFI) , a 60-item scale measuring an individual’s current level of resilience. The Frieburg Mindfulness Inventory (FMI)  a 14-item scale measuring mindfulness.
3. Results 3.1. Correlational analysis Intercorrelations, uncentred means and standard deviations are shown in Table 1. All variables were signi cantly related, with psychological dis- tress, burnout, and secondary traumatic stress being signi cantly negatively related to resilience and mindfulness. Psychological distress, burnout, and secondary traumatic stress were signi cantly posi- tively related. Likewise, resilience and mindfulness were signi cantly positively related.
3.2. Hierarchical analysis one: Burnout Preliminary analysis revealed age was a signi – cant predictor of resilience (r= 0.26,p= 0.003) and mindfulness (r= 0.26,p= 0.003). However age was not related to burnout (r= –0.09,p= 0.294). Gender, education, and employment status were not related to any of the criterion or predictor variables. As prelim- inary analysis found age covaried with the criterion and predictor variables, it was entered on Step 1 of the hierarchical multiple regression analysis. Resilience 634R. Harker et al. / Exploring resilience and mindfulness as preventative factors Table 1 Means, standard deviations and pearson correlation coef cients between psychological distress, burnout, secondary traumatic stress, resilience, and mindfulness (N= 133) Variable 1 2 3 4 5MSD 1. PsyDis —20.51 8.02 2. BurnT 0.62 ∗∗ — 49.40 9.81 [0.51, 0.72] 3. STS 0.47 ∗∗ 0.67 ∗∗ — 49.30 8.48 [0.32, 0.59] [0.57, 0.76] 4. Res –0.59 ∗∗ –0.61 ∗∗ –0.48 ∗∗ — 68.95 8.89 [–0.69, –0.47] [–0.71, –0.50] [–0.60, –0.33] 5. Mind –0.57 ∗∗ –0.60 ∗∗ –0.41 ∗∗ 0.67 ∗∗ — 39.51 7.24 [–0.67, –0.44] [–0.70, –0.48] [–0.54, –0.26] [0.56, 0.75] Note. PsyDis = Psychological distress; BurnT = Burnout; STS = Secondary traumatic stress; Res = Resilience; Mind = Mindfulness. 95% con dence intervals for intercorrelations are presented in brackets. ∗∗p< 0.01. was entered on Step 2 and mindfulness on Step 3.
After Step 3, when age, resilience, and mindfulness had been entered into the regression equation, a sig- ni cant amount of variance in burnout was accounted for (R 2= 0.45, adjustedR 2= 0.44,F(3, 129) = 35.15, p< 0.001). TheR 2value of 0.45 indicates that the model with all predictors in it accounts for 45% of the variance in burnout.
At Step 1 age was not a signi cant contributor to the model, accounting for 0.8% of the variance in burnout,R 2 change = 0.01,F change = (1, 131) = 1.11, p= 0.294. At Step 2, resilience accounted for a signi cant 37.3% of the variance in burnout, R 2 change = 0.37,F change = (1, 130) = 78.43,p< 0.001.
Higher scores on resilience were af liated with lower levels on burnout. At Step 3, mindfulness accounted for an additional 6.8% of the variance in burnout,R 2 change = 0.07,F change = (1, 129) = 15.99, p< 0.001. Higher scores on mindfulness were also af liated with lower scores on burnout. Examination of the part correlation coef cients revealed age contributed 0.98% unique variance to burnout, resilience contributed 8.88% unique variance and mindfulness contributed 6.81% unique variance.
28% of the variance in burnout was attributable to shared variability amongst the predictor variables.
3.3. Hierarchical analysis two: Secondary traumatic stress Age was entered on Step 1, resilience was entered on Step 2, and mindfulness on Step 3. After Step 3, when age, resilience, and mindfulness had been entered into the regression equation, a signi cant amount of variance in secondary traumatic stress was accounted for (R 2= 0.26, adjustedR 2= 0.24,F(3, 129) = 14.69,p< 0.001). TheR 2value of 0.26 indi- cates that the model with all predictors in it accountsfor 26% of the variance in secondary traumatic stress.
For secondary traumatic stress, age contributed 0.1% of the variance in the model at Step 1, however it was not a signi cant predictor,R 2 change = 0.00, F change = (1, 131) = 0.09,p= 0.771. At Step 2, resilience accounted for a signi cant 23.6% of the variance in secondary traumatic stress, R 2 change = 0.24,F change = (1, 130) = 40.28,p< 0.001.
Higher scores on resilience were af liated with lower levels on secondary traumatic stress. At Step 3, mindfulness accounted for a non-signi cant 1.8% of the variance in secondary traumatic stress, R 2 change = 0.02,F change = (1, 129) = 3.05,p= 0.083.
Examination of the part correlation coef cients revealed age contributed 1.32% unique variance to secondary traumatic stress, resilience contributed 8.18% unique variance and mindfulness contributed 1.77% unique variance. 15% of the variance in secondary traumatic stress was attributable to shared variability amongst the predictor variables.
3.4. Hierarchical analysis three: Psychological distress one Age was entered on Step 1, resilience was entered on Step 2, and mindfulness on Step 3. After Step 3, when age, resilience, and mindfulness had been entered into the regression equation, a signi cant amount of variance in psychological distress was accounted for (R 2= 0.40, adjustedR 2= 0.39,F(3, 129) = 29.05,p< 0.001). TheR 2value of 0.40 indi- cates that the model with all predictors in it accounts for 40% of the variance in psychological distress.
At Step 1, age contributed a signi cant 4.7% of the variance in the model,R 2 change = 0.05,F change = (1, 131) = 6.47,p= 0.012. At Step 2, resilience accounted for a signi cant 30.4% of the variance in psychological distress,R 2 change = 0.30,F change = R. Harker et al. / Exploring resilience and mindfulness as preventative factors635 (1, 130) = 61.04,p< 0.001. Higher scores on resilience were af liated with lower levels on psychological distress. At Step 3, mindfulness accounted for an additional 5.2% of the variance in psychological distress,R 2 change = 0.05,F change = (1, 129) = 11.18,p= 0.001. Higher scores on mind- fulness were also af liated with lower scores on psychological distress. Examination of the part corre- lation coef cients revealed age contributed a 0.23% unique variance to psychological distress, resilience contributed 7.56% unique variance and mindfulness contributed 5.15% unique variance. 27% of the variance in psychological distress was attributable to shared variability amongst the predictor variables.
3.5. Hierarchical analysis four: Psychological distress two Age was entered on Step 1, burnout was entered on Step 2, and secondary traumatic stress on Step 3.
After Step 3, when age, burnout, and secondary trau- matic stress had been entered, a signi cant amount of variance in psychological distress was accounted for (R 2= 0.42, adjustedR 2= 0.40,F(3, 129) = 30.88, p< 0.001). TheR 2value of 0.42 indicates that the model with all predictors in it accounts for 42% of the variance in psychological distress.
Age was a signi cant contributor to the model, accounting for 4.7% of the variance in the model at Step 1,R 2 change = 0.05,F change = (1, 131) = 6.47, p= 0.012. At Step 2, burnout accounted for a sig- ni cant 36.5% of the variance in psychological distress,R 2 change = 0.37,F change = (1, 130) = 80.87, p< 0.001. Higher scores on burnout were af li- ated with higher levels on psychological distress.
At Step 3, secondary traumatic stress accounted for a non-signi cant 0.5% of the variance in psycho- logical distress,R 2 change = 0.01,F change = (1, 129) = 1.21,p= 0.273. Examination of the part correla- tion coef cients revealed age contributed 2.70% unique variance to psychological distress, secondary traumatic stress contributed 0.55%, and burnout con- tributed 15.68% unique variance. 22% of the variance in psychological distress was attributable to shared variability amongst the predictor variables.
4. Discussion The results found that higher levels of resilience and mindfulness signi cantly predicted lower levels of burnout supporting previous research [16, 28]. Theresults indicated that age was not a signi cant predic- tor of burnout consistent with previous research .
Resilience was found to be a signi cant predictor of low levels of secondary traumatic stress consistent with previous research . However, mindfulness was not found to be a signi cant predictor, which was inconsistent with previous studies . Contrary to expectations, age did not signi cantly predict low levels of secondary traumatic stress indicating that regardless of age, human service professionals can experience secondary traumatic stress.
Age, mindfulness, and resilience were signi – cant predictors of psychological distress. Previous research suggests that resilient employees have the ability to monitor and regulate their emotions, main- tain focus when managing stressful events .
Secondary traumatic stress was not found to be a pre- dictor of psychological distress, however, in support of previous ndings, burnout was shown to predict psychological distress .
Whilst age was not a signi cant predictor of burnout or secondary traumatic stress, it did add signi cant variance to psychological distress. That is, the older the human service professional the less psychological distress they experience.Post hocinterpretation suggests that acquiring the skills and expertise to reduce the risk of experiencing psychological distress may develop with age .
5. Limitations The current study has limitations, which warrant consideration. Participation in the study was not a requirement for employees, as they were invited to participate on a voluntary basis. It is unknown if this resulted in a self-selection bias or if those employees who were perhaps experiencing the greatest levels of psychological distress were too over-extended to par- ticipate. The reliance of self-report data may also be a limitation, as self-report data can result in social desir- ability bias and demand characteristics. In addition, interpretation is limited as the current study employed a cross-sectional correlational design, and as a result, limits the extent to which causal inferences can be made. For example, whilst resilience was found to explain unique variance in psychological dis- tress, it cannot be established whether human service professionals who report low levels of psychologi- cal distress do so as a result of their higher level of resilience. However, the results do indicate that there are signi cant relationships between resilience, 636R. Harker et al. / Exploring resilience and mindfulness as preventative factors mindfulness, burnout, secondary traumatic stress, and psychological distress and future research could establish causal priority by experimentally manipu- lating variables of interest.
Furthermore, experimental manipulation of the variables will allow a cause and effect relationship to be determined, such as evaluation or workplace interventions targeted at reducing levels of psycho- logical distress, burnout, and secondary traumatic stress, and increasing resilience and mindfulness skills.
6. Conclusion Findings from this research contribute to the under- standing of factors that have the potential to reduce the risk of negative psychological outcomes among human service professionals. The results of the current study provide support for the argument to develop programs that focus on cultivating resilience and mindfulness among human service professionals to help reduce the risk of burnout, secondary trau- matic stress, and psychological distress.
Conﬂict of interest The authors have no con ict of interest to report.
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