| Article Access Statistics|
| Viewed||1940 |
| Printed||26 |
| Emailed||0 |
| PDF Downloaded||264 |
| Comments ||[Add] |
Click on image for details.
BRIEF RESEARCH COMMUNICATION
|Year : 2019
: 61 | Issue : 3 | Page
|Measuring reliability and validity of “Stressometer®”: A computer-based mass screening and assessment tool for evaluation of stress level and sources of stressors
Sandeep Vohra1, Angela Swilley Kelling2, Mrinal Mugdh Varma3, Anand Prakash4, Divyani Khurana5
1 Founder and CMD, No Worry No Tension Healthcare, New Delhi, India
2 Assistant Professor of Psychology, University of Houston-Clear Lake, Alabama, USA
3 Provost and Senior Vice Chancellor at Auburn University at Montgomery, Alabama, USA
4 Professor and Head, Department of Psychology, University of Delhi, New Delhi, India
5 Clinical Psychologist, Vohra Neuropsychiatry Centre, New Delhi, India
Click here for correspondence address and
|Date of Web Publication||16-May-2019|
| Abstract|| |
Introduction: It is essential to develop tools that can identify stress manifestation, source of stressors, and suffering in an effort to bridge the treatment gap and enhance behavioral health in the developing world. To that aim, the Stressometer® (SOM) was developed as a comprehensive scale of stress and behavioral health for use around the world.
Materials and Methods: A validation study of the Stressometer® (SOM) was undertaken with a sample in India that included a nonclinical group and a group of patients at a clinic in New Delhi. For validation purposes, participants were also administered three currently validated scales, including Perceived Stress Scale, Stress Overload Scale (SOS), and Depression Anxiety Stress Scale (DASS).
Results: The Stressometer® (SOM) was found to be reliable and had high correlations with established scales.
Conclusion: Stressometer® (SOM) is a valid and reliable, computer based mass screening tool for evaluation of stress level and sources of stress. Overall, Stressometer® (SOM) creates a robust measurement of stress and behavioral health that is likely culturally neutral and thus has universal applicability. A scale such as this one is ideal for use in the developing world to help bridge the treatment gap created and enhance behavioral health, especially in those suffering.
Keywords: Behavioral Health Screening, Stress Measurement, Stress Screening Scale, Stress
|How to cite this article:|
Vohra S, Kelling AS, Varma MM, Prakash A, Khurana D. Measuring reliability and validity of “Stressometer®”: A computer-based mass screening and assessment tool for evaluation of stress level and sources of stressors. Indian J Psychiatry 2019;61:295-9
|How to cite this URL:|
Vohra S, Kelling AS, Varma MM, Prakash A, Khurana D. Measuring reliability and validity of “Stressometer®”: A computer-based mass screening and assessment tool for evaluation of stress level and sources of stressors. Indian J Psychiatry [serial online] 2019 [cited 2021 May 12];61:295-9. Available from: https://www.indianjpsychiatry.org/text.asp?2019/61/3/295/258335
| Introduction|| |
Many suffering from behavioral health (or emotional /mental health) issues do not receive adequate treatment and may experience stigma or discrimination. In the developing world, there are additional challenges to maintain adequate behavioral health, including an overtaxed health-care system, poverty, illiteracy, stigma, and a lack of knowledge on behavioral health. For instance, the reality of mental health care in India is bleak, with inadequate mental health professionals. Therefore, it is essential to develop tools that can bridge the treatment gap.
Stress, which can threaten behavioral health, is the result of an imbalance between the demands placed and their ability to handle those demands, with large individual differences in reactions. Stress and inability to cope has been related to physical health issues, such as hypertension, and also to behavioral health issues. Theories on behavioral health have been developed and studied mainly from the Western point of view, which focuses on stress and its results from a more biomedical angle. Studies examining behavioral health in other cultures have discovered differences in stress, coping, and behavioral health, thus suggesting that standard Western instruments cannot be simply translated and used across cultures. For instance, many non-Western patients present with somatic complaints, such as aches, pains, and gastrointestinal distress, and not offer cognitive and mood symptoms until asked, possibly because of a cultural difference that physical symptoms are expected from ill people or possibly because of stigma toward the mentally ill.
Many scales related to stress and behavioral health have been developed and validated in diverse cultures. Three scales of interest are the Depression, Anxiety, and Stress Scale (DASS), Stress Overload Scale (SOS), and Perceived Stress Scale (PSS). All three have been used with samples from developing countries (DASS, SOS, and PSS) with focus on specific aspects of stress and overlook aspects of stress manifestation in Indian populations. Likewise, the previous version of Stressometer® (SOM Version 1),, assessed only components of stressed and missed on diagnostic capacity, thus indicating toward a new and revised version with Likert scale. Therefore, the current study attempted to validate a new and more comprehensive scale of stress and behavioral health for use in India.
| Materials and Methods|| |
There were 100 participants: 50 patients from a private clinic in New Delhi and 50 were individuals who had not sought treatment. Patients were recruited directly during the clinic visits. The nonpatients were recruited through E-mails, posts on the private clinic Facebook page and website and were not close friends or relatives of the patients.
- All participants must be above 18 years of age
- Participants for the patient group must suffer from a diagnosable mental health condition as per the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition/International Classification of Diseases, 10th Revision, and nonpatient group participants should not be experiencing severe physical or mental health conditions as assessed on a brief clinical interview.
The Stressometer® (SOM) is a self-administered assessment tool developed by the first author for mass screening to evaluate stress level of individuals and identify the sources of stressors (See attached [Appendix 1]). The scale has been reviewed in the past by experts in the field of psychiatry and psychology. Previous versions (SOM version 1) have been used to measure stress among nurses, paramilitary forces, and medical students and professionals. The previous version consisted of 50 questions divided over five subscales with each comprising ten questions. Theses subscales related to nature (e.g., irritability), circumstances (e.g., recent job change or marriage), body and mind (symptoms of stress, like, anxiety, or disturbed sleep), home life (e.g., lack of family support), and work life (e.g., unsupportive colleagues). The scale allows participants to choose between “Yes,” “No,” “Can't Say,” or “Not Applicable” for the nature and circumstances subscales and between “Never,” “Sometimes,” “Often,” “Always,” “Can't Say,” or “Not Applicable” for body and mind, home life, and worklife subscales.
Inspired by questions in Thorson's Principles of Stress Management by Peiffer, the Stressometer® (SOM) can be administered online or through software installed on computers. It consists of basic demographic questions as well as 55 questions addressing recent possible stressors (Circumstances, Domestic Life, and Professional Life), the participant's nature (Human Nature), and the presence of potential stress symptoms (Clinical Symptoms). All questions use a five-point Likert scale with the additional options of “Can't Say” and “Not applicable.” Four questions identify major symptoms of common disorders and will be used as determinants of need for immediate referral for intervention.
For convergent validation purposes, three currently validated scales were used. The first is the PSS, which consists of 14 questions focused on stress experienced in the last month. The second is the DASS, which consists of 42 questions measuring the negative emotional states of depression, anxiety, and stress in the past week. The third is the SOS, which consists of 30 items examining to what degree a person is experiencing stress overload that may affect their well-being. The SOS is split into two subscales: personal vulnerability and event load.
Data were collected from March to April and July 2017. Participants were informed of the details of the study and written informed consent was obtained from them. Participants were asked to fill out all four scales in a fixed order of demographics, SOM, PSS, SPS, and DASS. All scales were self-administered on provided computers or paper as per the convenience of the participants. After scale administration, to test criterion validity, each participant underwent a brief clinical interview with psychiatrist and/or psychologist, who were blinded as to the results of the tests administered. The clinical interview provided each participant with a rating addressing their need for intervention. Researchers were available for support if needed.
The Institutional Review Board approved the study protocol (reference number: A20/2017). Participants gave written informed consent to take part in the research.
For the four questions that addressed major symptoms of disorders (wanting to leave everything and go away, persistently sad and low, uncontrollable thoughts or compulsive actions, and hearing voices or feeling paranoia), patterns of responses were compared for patient and control groups and a Chi-squared was calculated. Subscale scores for Human Nature, Life Circumstances, Human Body and Mind, Home Life, and Work Life were computed. In addition, ratings for all questions were added to get a total score. Spearman correlations were used to analyze the relationships among the five subscales, total score, and validation scales. Reliability of the scale was established using the Cronbach's alpha test. In addition, a logistic regression analysis was performed to use for prediction of future individuals who need referral for possible diagnosis and treatment.
| Results|| |
Of the 100 participants, 48 (20 patients and 28 nonpatients) were female and 52 (30 patients and 22 nonpatients) were male. The participants ranged in age from 18 to 74, with a mean age of 35.0.
The Stressometer® (SOM) scale was found to be highly reliable (55 items; α = 0.935). Patients were more likely to agree that they wanted to leave everything and go away (χ2(4) = 10.93, P = 0.027), were persistently sad and low (χ2(4) = 18.84, P = 0.001), had uncontrollable thoughts or compulsive actions (χ2(4) = 24.53, P < 0.001), or that they heard voices or were paranoid (χ2(4) = 15.04, P = 0.005). Patients more frequently did not report jobs in the demographics and 25 patients selected “Can't Say” on the Professional Life Subscale. Therefore, that subscale was excluded from the correlation analysis. There were significant correlations between clinical symptoms and patient status (rs = 0.375, P < 0.001), Dass-total (rs = 0.721, P < 0.001), PSS total (rs = 0.503, P < 0.001), SOS personal vulnerability (rs = 0.584, P < 0.001), and SOS event load (rs = 0.385, P < 0.001). There are also significant correlations between the validation scales used [Table 1].
|Table 1: Correlations between the Stressometer® subscales, patient status, and validation scales|
Click here to view
There was a significant logistic regression using the subscales as administered. A logistic regression was calculated to predict if an individual needed intervention based on status as patient or nonpatient [Table 2]. The significant predictors were clinical symptoms subscale, SOS event load subscale, and the reduced domestic life subscale. That combination was also highly reliable (33 items; α = 0.899). A test of the full model against a constant only model was statistically significant, indicating that the predictors as a set reliably distinguished participant group membership (χ2(3) = 41.02, P < 0.001). Nagelkerke's R2 of 0.449 indicates a moderate relationship between prediction and group. Prediction success overall was 76% (72% nonpatients and 80% patients). The Wald criterion indicates that all predictors were significant.
|Table 2: Logistic regression equation to predict group membership as patient or nonpatient|
Click here to view
| Discussion|| |
The Stressometer® (SOM) was identified to be a valid and highly reliable measure of stress. The scale was correlated with other measures of stress (PSS, SOS, and DASS) used in the study, thus suggesting concurrent validity. In other words, stressometer is identified to be a tool with the capacity to gauge stress. The unique subscales of stressometer correlated significantly well with the other scales of stress (PSS, SOS, and DASS), thus indicating the origin of stress from various dimensions of an individual's life. In other words, the tool is comparable with existing global stress scales, besides additionally analyzing the source of stress suggesting that as a whole it can function as a self-assessment of stress and its causes. Based on it being self-administered, if used across the world, can bridge the treatment gap and efficaciously identify those requiring treatment.
In addition, the scale is likely to be culturally neutral with universal applicability, thus making it ideal for use in the developing world to bridge the treatment gap created by an overtaxed health care system and enhance behavioral health. Simultaneously, it helps in cutting down the stigma of mental health by being a self-rated computer-based questionnaire with the potential to be used by the user at his/her comfort zone.
This study has limitation of being mostly based on self-report data, thus can be subject to response bias. The study also had a small sample size with 25 participants selecting “Can't Say” on the professional life subscale resulting in exclusion of the same from the analysis. Future studies can include a full detailed clinical or physical analysis of the participants. Furthermore, the future study can also take into account the professional aspect of the participants so as to understand the level of stress or causation from the same.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.]
| References|| |
Trivedi JK, Sareen H, Dhyani M. Rapid urbanization – Its impact on mental health: A South Asian perspective. Indian J Psychiatry 2008;50:161-5.
] [Full text]
Patel V. Research priorities for Indian psychiatry. Indian J Psychiatry 2010;52:S26-9.
] [Full text]
Lazarus RS. Coping theory and research: Past, present, and future. Psychosom Med 1993;55:234-47.
Smith EM. Ethnic minorities life stress, social support, and mental health issues. Couns Psychol 1985;13:537-79.
Kulesza M, Raguram R, Rao D. Perceived mental health related stigma, gender, and depressive symptom severity in a psychiatric facility in South India. Asian J Psychiatr 2014;9:73-7.
Palsane MN, Lam DJ. Stress and coping from traditional Indian and Chinese perspectives. Psychol Dev Soc 1996;8:29-53.
Sinha BK, Willson LR, Watson DC. Stress and coping among students in India and Canada. Can J Behav Sci 2000;32:218.
Flaherty JA, Gaviria FM, Pathak D, Mitchell T, Wintrob R, Richman JA, et al.
Developing instruments for cross-cultural psychiatric research. J Nerv Ment Dis 1988;176:257-63.
Patel V, Abas M, Broadhead J, Todd C, Reeler A. Depression in developing countries: Lessons from Zimbabwe. BMJ 2001;322:482-4.
Tawar S, Bhatia SS, Ilankumaran M. Mental health, are we at risk? Indian J Community Med 2014;39:43-6.
] [Full text]
Lovibond PF, Lovibond SH. The structure of negative emotional states: Comparison of the depression anxiety stress scales (DASS) with the beck depression and anxiety inventories. Behav Res Ther 1995;33:335-43.
Amirkhan JH. Stress overload: A new approach to the assessment of stress. Am J Community Psychol 2012;49:55-71.
Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav 1983;24:385-96.
Sahoo S, Khess CR. Prevalence of depression, anxiety, and stress among young male adults in India: A dimensional and categorical diagnoses-based study. J Nerv Ment Dis 2010;198:901-4.
Sukadarin EH, Pim NU, Zakaria J, Deros BM, Syazwani N. The prevalence of work-related musculoskeletal disorders and stress level among hospital nurses. Occup Saf Health 2016;1:40-4.
Augustine LF, Vazir S, Rao SF, Rao MV, Laxmaiah A, Nair KM. Perceived stress, life events & coping among higher secondary students of Hyderabad, India: A pilot study. Indian J Med Res 2011;134:61-8.
] [Full text]
Varma MM, Vohra S, Goswami S, Kelling A, Khurana D. Addressing stress among nurses in India. J Nurs Res Soc India 2016;9:63-70.
Kelling A, Varma MM, Vohra S, Goswami S, Khurana D. Fighting the enemy within: Combating stress among the Indian paramilitary forces. IPJ 2017;64:20-9.
Varma MM. Addressing stress among medical students and professionals: Strategies for optimizing student health and success. J Contemp Med Educ 2016;4:159-64.
Peiffer V. Thorson's Principles of Stress Management. London: Thorsons; 1996.
Dr. Sandeep Vohra
Founder and CMD, No Worry No Tension Healthcare, 29/24 East Patel Nagar, New Delhi - 110 008
Source of Support: None, Conflict of Interest: None
[Table 1], [Table 2]