performance
A discriminant validity test was performed to ensure the empirical difference of all constructs. For this, it was proposed by Fornell and Larcker ( 97 ) that the variance of the results is supposed to be greater than other constructs. The second indicator of discriminant validity is that the square root values of AVE have a greater correlation between the two indicators. Hair et al. ( 90 ) suggested that the correlation between the pair of predictor variables should not be higher than 0.9. Table 3 shows that discriminant validity recommended by Hair et al. ( 90 ) and Fornell and Larcker ( 97 ) was proved clearly that both conditions are fulfilled and indicates that the constructs have adequate discriminant validity.
Discriminant validity analysis.
Acd. Strs | 0.835 | |||
Fam. Strs | 0.543 | 0.849 | ||
Std. Dep. Lev | 0.622 | 0.583 | 0.827 | |
Std. Acd. Perf | 0.623 | 0.629 | 0.579 | 0.832 |
Acd. Strs, Academic Stress; Fam. Strs, Family Stress; Std. Dep. Lev, Student's Depression Level; Std. Acd. Perf, Student's Academic Performance .
Kaynak ( 98 ) described seven indicators that ensure that the measurement model fits correctly. These indicators include standardized root mean squared residual (SRMR), root means a square error of approximation (RMSEA), comparative fit index (CFI), normative fit index (NFI), adjusted goodness of fit index (AGFI), the goodness of fit index (GFI) and chi-square to a degree of freedom (x 2 /DF). Tucker-Lewis's index (TLI) is also included to ensure the measurement and structural model's fitness. In the measurement model, the obtained result shows that the value of x 2 /DF is 1.898, which should be lower than 2 suggested by Byrne ( 99 ), and this value also meets the requirement of Bagozzi and Yi ( 100 ), i.e., <3. The RMSEA has the value 0.049, which fully meets the requirement of 0.08, as stated by Browne and Cudeck ( 101 ). Furthermore, the SRMR acquired value is 0.0596, which assemble with the required need of < 0.1 by Hu and Bentler ( 102 ). Moreover, according to Bentler and Bonett ( 103 ), McDonald and Marsh ( 104 ), and Bagozzi and Yi ( 100 ), the ideal value is 0.9, and the values obtained from NFI, GFI, AGFI, CFI, and TLI are above the ideal value.
Afterward, the structural model was analyzed and achieved the findings, which give the value of x 2 /DF 1.986. According to Browne and Cudeck ( 101 ), the RMSEA value should not be greater than 0.08, and the obtained value of RMSEA is 0.052, which meets the requirement perfectly. The minimum requirement of Hu and Bentler ( 102 ) should be <0.1, for the structural model fully complies with the SRMR value 0.0616. According to a recommendation of McDonald and Marsh ( 104 ) and Bagozzi and Yi ( 100 ), the ideal value must be up to 0.9, and Table 4 also shows that the values of NFI, GFI, AGFI, CFI, and TLI, which are above than the ideal value and meets the requirement. The above results show that both the measurement and structural models are ideally satisfied with the requirements and the collected data fits correctly.
Analysis of measurement and structural model.
Recommended value | ≤ 3 | ≥0.9 | ≥0.9 | ≥0.9 | ≥0.9 | ≥0.9 | ≤0.08 | ≤0.08 |
Measurement model | 1.898 | 0.9 | 0.91 | 0.914 | 0.91 | 0.91 | 0.049 | 0.0596 |
Structural model | 1.986 | 0.91 | 0.91 | 0.918 | 0.92 | 0.92 | 0.052 | 0.0616 |
The SEM technique is used to examine the hypotheses. Each structural parameter goes along with the hypothesis. The academic stress (Acd. Strs) with the value β = 0.293 while the p -value is 0.003. These outcomes show a significant positive relationship between academic stress (Acd. Strs) and students' depression levels (Std. Dep. Lev). With the β = 0.358 and p = 0.001 values, the data analysis discloses that the family stress (Fam. Strs) has a significant positive effect on the students' depression level (Std. Dep. Lev). However, the student's depression level (Std. Dep. Lev) also has a significant negative effect on their academic performance (Std. Acd. Perf) with the values of β = −0.319 and p = 0.001. Therefore, the results supported the following hypotheses H 1 , H 2 , and H 3 . The sub-hypotheses analysis shows that the results are statistically significant and accepted. In Table 5 , the details of the sub-hypotheses and the principals are explained precisely. Please see Table 6 to review items with their mean and standard deviation values. Moreover, Figure 2 represents the structural model.
Examining the hypotheses.
-value | |||||
---|---|---|---|---|---|
H | Acd. Strs → Std. Dev. Lev | 0.201 | 2.021 | 0.039 | Accepted |
H | Fam. Strs → Std. Dep. Lev | 0.358 | 3.997 | 0.001 | Accepted |
H | Std. Dep. Lev → Std. Acd. Perf | −0.319 | −3.402 | 0.001 | Accepted |
Description of items, mean, and standard deviation.
Mental health has a valuable impact on students' academic learning. | 3.26 | 1.752 |
Academic pressure leads to stress in students' life. | 3.25 | 1.530 |
I have difficulty in understanding basic concepts. | 2.95 | 1.272 |
I have to revise the things again and again to develop an understanding. | 3.14 | 1.352 |
I have lost interest in academic aspects that used to be important for me. | 2.83 | 1.351 |
Family issues leads to stress in students' life. | 3.37 | 1.504 |
Because of family issues I cannot concentrate on my studies. | 3.19 | 1.468 |
I am not able to sleep properly because of family issues. | 3.02 | 1.424 |
Depression negatively affects a student's motivation to learn. | 3.37 | 1.405 |
Unfair treatment by teachers causes academic depression in students. | 3.12 | 1.620 |
Depression has negatively affected my learning capabilities. | 2.99 | 1.280 |
Depression has negatively affected my academic grades. | 3.19 | 1.201 |
Sometimes I don't see value in my life. I feel depressed in the class. | 2.96 2.91 | 1.398 1.310 |
Structural model.
These findings add to our knowledge of how teenage depression is predicted by academic and familial stress, leading to poor academic performance, and they have practical implications for preventative and intervention programs to safeguard adolescents' mental health in the school context. The outcomes imply that extended academic stress positively impacts students' depression levels with a β of 0.293 and a p -value sof 0.003. However, according to Wang et al. ( 5 ), a higher level of academic stress is linked to a larger level of school burnout, which leads to a higher degree of depression. Satinsky et al. ( 105 ) also claimed that university officials and mental health specialists have expressed worry about depression and anxiety among Ph.D. students, and that his research indicated that depression and anxiety are quite common among Ph.D. students. Deb et al. ( 106 ) found the same results and concluded that depression, anxiety, behavioral difficulties, irritability, and other issues are common among students who are under a lot of academic stress. Similarly, Kokou-Kpolou et al. ( 107 ) revealed that depressive symptoms are common among university students in France. They also demonstrate that socioeconomic and demographic characteristics have a role.
However, Wang et al. ( 5 ) asserted that a higher level of academic stress is associated with a higher level of school burnout, which in return, leads to a higher level of depression. Furthermore, Satinsky et al. ( 105 ) also reported that university administrators and mental health clinicians have raised concerns about depression and anxiety and concluded in his research that depression and anxiety are highly prevalent among Ph.D. students. Deb et al. ( 106 ) also reported the same results and concluded that Depression, anxiety, behavioral problems, irritability, etc. are few of the many problems reported in students with high academic stress. Similary, Kokou-Kpolou et al. ( 107 ) confirmed that university students in France have a high prevalence of depressive symptoms. They also confirm that socio-demographic factors and perceived stress play a predictive role in depressive symptoms among university students. As a result, academic stress has spread across all countries, civilizations, and ethnic groups. Academic stress continues to be a serious problem impacting a student's mental health and well-being, according to the findings of this study.
With the β= 0.358 and p = 0.001 values, the data analysis discloses that the family stress (Fam. Strs) has a significant positive effect on the students' depression level (Std. Dep. Lev). Aleksic ( 108 ) observed similar findings and concluded that many and complicated concerns of personal traits, as well as both home and school contexts, are risk factors for teenage depression. Similarly, Wang et al. ( 109 ) indicated that, among the possible risk factors for depression, family relationships need special consideration since elements like parenting styles and family dynamics influence how children grow. Family variables influence the onset, maintenance, and course of juvenile depression, according to another study ( 110 ). Depressed adolescents are more likely than normal teenagers to have bad family and parent–child connections.
Conversely, students' depression level has a significantly negative impact on their academic performance with β and p -values of −0.319 and 0.001. According ( 111 ), anxiety and melancholy have a negative influence on a student's academic performance. Adolescents and young adults suffer from depression, which is a common and dangerous mental illness. It's linked to an increase in family issues, school failure, especially among teenagers, suicide, drug addiction, and absenteeism. While the transition to adulthood is a high-risk period for depression in general ( 5 ), young people starting college may face extra social and intellectual challenges that increase their risk of melancholy, anxiety, and stress ( 112 ). Students' high rates of depression, anxiety, and stress have serious consequences. Not only may psychological morbidity have a negative impact on a student's academic performance and quality of life, but it may also disturb family and institutional life ( 107 ). Therefore, long-term untreated depression, anxiety, or stress can have a negative influence on people's ability to operate and produce, posing a public health risk ( 113 ).
The current study makes various contributions to the existing literature on servant leadership. Firstly, it enriches the limited literature on the role of family and academic stress and their impact on students' depression levels. Although, a few studies have investigated stress and depression and its impact on Students' academic performance ( 14 , 114 ), however, their background i.e., family and institutions are largely ignored.
Secondly, it explains how the depression level impacts students' academic learning, specifically in the Asian developing countries region. Though a substantial body of empirical research has been produced in the last decade on the relationship between students' depression levels and its impact on their academic achievements, however, the studies conducted in the Pakistani context are scarce ( 111 , 115 ). Thus, this study adds further evidence to prior studies conducted in different cultural contexts and validates the assumption that family and academic stress are key sources depression and anxiety among students which can lead toward their low academic grades and their overall performance.
This argument is in line with our proposed theory in the current research i.e., cognitive appraisal theory which was presented in 1966 by psychologist Richard Lazarus. Lazarus's theory is called the appraisal theory of stress, or the transactional theory of stress because the way a person appraises the situation affects how they feel about it and consequently it's going to affect his overall quality of life. In line with the theory, it suggests that events are not good or bad, but the way we think about them is positive or negative, and therefore has an impact on our stress levels.
According to the findings of this study, high levels of depressive symptoms among college students should be brought to the attention of relevant departments. To prevent college student depression, relevant departments should improve the study and life environment for students, try to reduce the generation of negative life events, provide adequate social support for students, and improve their cognitive and coping capacities to improve their mental qualities.
Stress and depression, on the other hand, may be managed with good therapy, teacher direction, and family support. The outcomes of this study provide an opportunity for academic institutions to address students' psychological well-being and requirements. Emotional well-being support services for students at Pakistan's higher education institutions are lacking in many of these institutions, which place a low priority on the psychological requirements of these students. As a result, initiatives that consistently monitor and enhance kids' mental health are critical. Furthermore, stress-reduction treatments such as biofeedback, yoga, life-skills training, mindfulness meditation, and psychotherapy have been demonstrated to be useful among students. Professionals in the sector would be able to adapt interventions for pupils by understanding the sources from many spheres.
Counseling clinics should be established at colleges to teach students about stress and sadness. Counselors should instill in pupils the importance of positive conduct and decision-making. The administration of the school should work to create a good and safe atmosphere. Furthermore, teachers should assume responsibility for assisting and guiding sad pupils, since this will aid in their learning and performance. Support from family members might also help you get through difficult times.
Furthermore, these findings support the importance of the home environment as a source of depression risk factors among university students, implying that family-based treatments and improvements are critical in reducing depression among university students.
The current study has a few limitations. The researcher gathered data from the higher education level of university students studying in Islamabad and Rawalpindi institutions. In the future, researchers are required to widen their region and gather information from other cities of Pakistan, for instance, Lahore, Karachi, etc. Another weakness of the study is that it is cross-sectional in nature. We need to do longitudinal research in the future to authoritatively assert the cause-and-effect link between academic and familial stress and their effects on students' academic performance since cross-sectional studies cannot establish significant cause and effect relationships. Finally, the study's relatively small sample size is a significant weakness. Due to time and budget constraints, it appears that the capacity to perform in-depth research of all firms in Pakistan's pharmaceutical business has been limited. Even though the findings are substantial and meaningful, the small sample size is predicted to limit generalizability and statistical power. This problem can be properly solved by increasing the size of the sample by the researchers, in future researches.
Ethics statement.
Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.
All authors contributed to conceptualization, formal analysis, investigation, methodology, writing and editing of the original draft, and read and agreed to the published version of the manuscript.
This work was funded by the 2020 Heilongjiang Province Philosophy and Social Science Research Planning Project on Civic and Political Science in Universities (Grant No. 20SZB01). This work is supported by the Scientific Grant Agency of the Ministry of Education, Science, Research, and Sport of the Slovak Republic and the Slovak Academy Sciences as part of the research project VEGA 1/0797/20: Quantification of Environmental Burden Impacts of the Slovak Regions on Health, Social and Economic System of the Slovak Republic.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Authors would like to thank all persons who directly or indirectly participated in the completion of this manuscript.
The history of the model, the major concept of the framework, major assumptions of the theory concerning family and nursing.
A family stress theory is a social abstract that tends to explain the observations concerning family strains, which have occurred over the years. In fact, this is considered as a critical aspect of the social life (Babbie, 2004). Like most theories in nursing, family stress theory is an explanation of observations concerning family conducts that can be used to design clinical intervention strategies, predict the behavior and guide further health studies. Even though stress theories are relatively new and still evolving, it has been widely applied in the social, psychological, psychiatric and healthcare intervention strategies (Babbie, 2004). Stress theories consist of the individual and the family anxiety presumptions. However, the individual, family models, and stress management frameworks are applied and remain critical in most family strain-management interventions (Babbie, 2004).
Various studies on the strain concept have advanced overtime in the domestic arena. The evolution in the study of the family strains and the emergence of the family stress theory has led researchers to divide the family strain preposition into four distinct eras (Babbie, 2004). Even though the stages are distinct, the models are closely related and developed from one stage to the other. Both the family and individual stress theories began in the 1920s with researchers particularly concerned with the strains that affected both the individuals and families. The stress theories were developed through researchers in the fields of psychology, psychiatry, anthropology, and sociology (Babbie, 2004). However, its application span across various fields including health sciences.
The first era in the development of the family stress theory started with the studies in the 1920s and ended in the development of the assumption in the mid-1940s (Babbie, 2004). The first era of the family stress theory is associated with the works of Angel in 1936, Cavan and Ranck in 1938, Koos in 1946 and Hill in 1949 (Babbie, 2004).
The researchers established different stresses affecting families resulting from the economic changes (Babbie, 2004).
The second era in the development of family stress theory was advanced via the works of Hill in 1958. In the study, Hill developed the ABCX model, which became the foundation of the current family stress theory. During the second era most of the researches revolved around testing the Hill’s ABCX model (Babbie, 2004).
In the third era, the focus of the studies was on the family strengths, adaptation strategies as well as the concepts of the family systems (Babbie, 2004). The third era depended on the works of McCubbin and Patterson who expanded the ABCX model to double ABCX and FAAR models in 1982 and 1983 respectively. McCubbin and McCubbin also came up with typology and resiliency models in 1987 and 1991 respectively (Babbie, 2004).
The fourth era in the development of family stress theory also saw a transformation to the postmodern stressors with a lot of emphasis on the changing focus to industrial processes, cultural transformations, shared family meanings and contexts (Babbie, 2004). The fourth era is mainly associated with the works of Boss in 2002.
The current applications of the family stress theory are based on the postmodern studies conducted mainly in the fourth era. The main idea is to utilize the modern family setting in explaining the health phenomena as well as to provide guidance to the nursing practice (Votroubek, 2010). Essentially, the whole concept surrounds a clinical setting in which the family forms an integral part of the intervention. The whole idea is to apply the family stress theory in clinical practice particularly, to support healthcare programs during typical family unit transitions as well as in evaluating changes in the family during one of the member’s heightened or persistent poor health (Votroubek, 2010).
Based on the assumptions that a number of realities and truths exists, postmodern interventions is distinct from the notion that realities can be conceived. The postmodern therapies are founded on the idea that families create meanings in their lives through mutual communications (Votroubek, 2010). In fact, the post-modern approach put more emphasis on determining the strengths and resources of the clients. The post-modern approaches steered clear of the concept of pathologizing the clients and disregarded the issue of diagnosis (Votroubek, 2010). The post-modern approaches also kept away from the processes of searching for the underlying causes of the family problems.
Four major assumptions are associated with the family stress model. The theory assumed that most stresses are due to unexpected events (Babbie, 2004). Besides, the theory assumed that stresses that come from unexpected events cause more disruption to families compared with stressors that result from external events including economic downturn, war and related circumstances. In addition, the concept assumed that the increased awareness of anxiety originates from the deficiency of experience of the preceding stressor. Finally, the theory assumed that the stressors originating from uncertain actions are stressful compared with non-ambiguous events (Babbie, 2004). The assumptions remain critical in understanding how the families cope. Besides, the assumptions help the nurses to determine the stressors and the family coping relationships, which in turn led to the establishment of the resilient outcomes.
Babbie, E. (2004). The practice of social research. Belmont, CA: Wadsworth/Thomson.
Votroubek, W. (2010). Pediatric home care for nurses: A family-centered approach. Boston, MA: Jones & Bartlett Publishers.
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This as-told-to essay is based on a transcribed conversation with Dr. Jennifer J. Bryan, 47, about using an AI voice assistant in the medical field. The following has been edited for length and clarity.
I work in family medicine, treating newborns up to patients in their 90s.
I graduated from my residency in family medicine in 2006. I've been practicing in Mississippi for 18 years and joined the Hattiesburg Clinic a year ago.
I work at my clinic 40 hours a week, but I used to spend a lot of my time documenting patient notes outside those hours. Documentation admin would take an extra 10 to 20 hours a week.
Last fall, I started using Suki AI , an AI-powered voice assistant, to help me make notes from patient interactions. I now use it all the time.
It reminded me of the old days of practicing medicine when I wasn't constantly typing notes into a computer. It's provided a more organic way for me to interact with patients and alleviated a lot of stress about note-taking.
I'm in favor of using AI for notetaking , but do have hesitations about using it for other purposes in the medical field.
When I first started practicing medicine in 2006, I took handwritten notes. I'd get hand cramps sometimes, but I could get my notes done during consultations.
When electronic health records came into effect, doctors could type notes, but typing while interacting with patients was distracting. So, most typing would happen over a lunch break or at home on the couch. This is when the time I spent documenting notes increased significantly, and it also caused burnout for a lot of physicians around the country.
As the president of the Mississippi State Medical Association, I speak to a lot of physicians. They say button-clicking and typing adds extra strain to their lives. Personally, I never burned out, but I was often stressed and looked to alleviate it.
I started using dictation software around six years ago. I would speak into a handheld microphone, and it would type my words out. It was a good product, but verbally recreating each visit took a long time, and it misspelled and misheard some words.
A fellow physician at my clinic encouraged us to try using an AI assistant for note-taking. I signed up to trial Suki AI, which I heard the American Academy of Family Physicians endorsed , and a competitor product. I preferred Suki, and it's the product I still use today.
(Editor's note: A spokesperson for Suki AI told BI that the company has no financial partnership with either Hattiesburg Clinic or the AAFP, and the listing price for the technology is $399 a month per provider.)
Suki is an AI assistant app on my phone that I use for notes. When I walk into a room with a patient, I ask my patients for consent to use the software. I'll hit record and my phone will listen to the conversation with the patient. I'll walk out of the room and stop recording.
Unlike the dictation software I used before, which couldn't produce summaries of what I said to it, Suki generates a summarizing note from the appointment, which I send to my computer.
If my phone dies or I don't have it on me, I can speak directly to Suki about the appointment. It creates a solid note as if it were listening to the exam room interaction, but I think it's more accurate when I have it in the room with the patient.
At the end of the day, I'll spend 15 minutes going through my notes on my computer, making sure the AI spelled the drugs correctly, and cleaning things up. It's a huge contrast from the 10 hours a week I used to spend on notetaking.
I'm very legal-minded, and one of my first questions about Suki was how long it stores patient information. I learned that the audio and transcript from patient interactions are erased from Suki after seven days, so I felt comfortable with how it handles privacy. Before the notes are erased from Suki, I send them to my computer, and they're permanently stored in my electronic records.
I use Suki all the time now. I pay for the service, which is deducted from my paycheck.
It's made my workflow easier. I'm more able to accommodate patients into my schedule. Patients have also noticed that I don't have to type anymore and can keep eye contact without looking over a computer.
It's alleviated stress in my personal life. I'd never miss family events for work because family is my priority, but I did overload myself and would have to stay up late to finish notes. Now, when I'm home, my family and I are watching movies or doing homework, and I don't have to type notes for work on my laptop.
The technology isn't perfect. Sometimes, when it generated notes, there were two paragraphs that almost said the same thing, so I'd cut one out when editing. Every now and then, it will misunderstand a medicine I say and put in something else.
I don't see this as a problem. There are plenty of errors with scribbly doctor's handwriting and some with other dictation software. As physicians, we're responsible for reviewing notes for accuracy. With any technology, there will be an acceptable degree of edits that need to be made.
AI has been part of medical care for quite some time now, particularly in radiology and surgery .
When it comes to medical transcript and scribe work, I see AI as a welcome relief from typing for physicians, who were trained to diagnose and treat, not to type.
I don't see AI ever replacing the physician , but I can see it chipping away at the medical scribe career. Scribes sit in exam rooms and type for doctors, but they're very expensive to have on board.
I cautiously welcome AI in the medical field. There are definitely benefits that can help humans practice medicine , such as using it to detect breast cancer . However I am cautious about errors from AI when it comes to patient lives and patient safety. In medicine, you can never underestimate the value of human interaction and understanding pain and feelings.
I'm all in when it comes to using AI for transcription and summing up visits, but we have to make sure we have appropriate guardrails when going beyond that.
Do you have a personal story about AI in the workplace you want to share with Business Insider? Email [email protected]
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The second section includes 14 items based on family stress, academic stress, students' depression levels, and students' academic performance. Academic and family stress were measured by 3 item scale for each construct, and students' depression level and academic performance were measured by 4 item scale for each separate construct.
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With such knowledge, FNPs can anticipate, reduce, or even eliminate undesirable family stress and better care for all patients in the family Description of Selected Family Theory Berkey, Hanson, and Mischke's Family Systems Stressor-Strength Inventory (FS3I) tool is an important means of assessing families, including the family examined for ...
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A family stress theory is a social abstract that tends to explain the observations concerning family strains, which have occurred over the years. In fact, this is considered as a critical aspect of the social life (Babbie, 2004). Like most theories in nursing, family stress theory is an explanation of observations concerning family conducts ...
Family Stress Case Study. 947 Words4 Pages. CHAPTER I THE PROBLEM AND ITS BACKGROUND Introduction Family is a group of people that consist of parents, children and their relatives. Our parent's role is to take care of us, to teach us good manners, to give our needs and wants. They are considered as our first teachers that can teach us until ...
With your select family in mind, complete the 71 life events Family Inventory of Life Events and Changes scale (Bomar, pp. 416-417). What additional stressors did the scale help you identify, if any? Explain why you consider the pile-up level of stress your select family is experiencing to be high, moderate, or low.
Figure 1: The schematic paradigm used in the study. Statement of the Problem The purpose of the study was to identify the effects of family stress to the second year accountancy students of De La Salle Araneta University regards to their academic performance. Specifically, the study aims to answer the following questions: a.
Dr. Jennifer J. Bryan used to work an extra 10 to 20 hours a week, note-taking for her job. Last fall, she began using an AI assistant to create notes and says it's alleviated her stress. She ...