Emoji-based Attention Bias Modification Training for Depressive Young Adults
Study Details
Study Description
Brief Summary
Globally, the rates of young adults and college students reporting symptoms of depression have been rising over the past decade. There are major obstacles being faced in mental healthcare that prevents many individuals from receiving sufficient and quality mental healthcare services. Current treatments for depression are not able to target the underlying factors causing the disorder. In addition, individuals with depressive symptoms face issues with accessibility and social stigma. Hence, there has been increasing interest in behavioural and cognitive mental health interventions with the potential for remote applications. This study aims to evaluate the feasibility and acceptability of using an emoji-based attention bias modification training paradigm on depressive symptom severity compared with a deep breathing practice protocol, a sham training protocol and a control group. It is expected that participants who undergo the attention bias modification training and deep breathing training paradigms will have reduced depressive symptom scores, changes in attention bias indices, and changes in event-related potential component measures compared to participants who did not undergo the interventions.
| Condition or Disease | Intervention/Treatment | Phase |
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Detailed Description
Depression is a common mental health disorder and is a major cause of disability worldwide. Despite the wide range of treatments currently available, many individuals with depression do not acquire treatment for the disorder. Some patients are concerned about possible negative effects of antidepressants, although there is also a high rate of discontinuation among patients on antidepressant regimens. Relapse is a common occurrence, where at least 50% of the patients who recover from the first episode of depression will experience at least one more depressive episode. The consistent preference for psychological treatments over medication gives particular relevance to research aimed at developing suitable behavioral and psychological treatments for depression.
Digital mental health interventions could potentially improve access to mental health services and help overcome the stigma associated with seeking traditional mental health services. Vulnerable young people, especially individuals in rural or low-resource areas and marginalized communities face unequal access to mental health services. In contrast, there is an unprecedented surge in access to digital technology platforms and mobile devices among young adults worldwide. The mental healthcare access gap can be addressed by the opportunities provided by digital technology to provide better care for youth and young adults. The young adult demographic is a critical target group because it is the group with the highest incidence and prevalence of mood disorders. Many people often find it challenging to communicate about mental health issues, but if left unresolved, these issues can lead to deterioration of mental well-being.
A growing majority of young adults have access to mobile devices and the Internet. Meta-analyses of computerized and Internet-based treatments for depression found that they significantly reduced depressive symptoms compared to control groups. However, some methodological limitations were reported by the analyses, such as lack of follow-up testing, skewed post-intervention data, and lack of participant feedback. A review by Lamb et al. (2019) on the efficacy and practicality of remote psychotherapy for depression and anxiety disorders, reported that interventions that were administered over the telephone, through video-conferencing, or online were generally effective. Remote psychotherapy was reported to improve accessibility and convenience, especially for individuals living in rural and remote areas or individuals with limited mobility.
The dot-probe paradigm is a behavioral task widely employed to measure attention and perception biases. The task can be adapted in different ways to accommodate the investigation of various conditions such as generalized anxiety disorders, eating disorders, and substance use disorders. In the dot-probe task, two stimuli appear on a screen simultaneously in two separate spatial locations. One of the stimuli has an emotional valence, while the other is neutral. The stimuli then are removed, and a dot-probe appears in one of the locations where the stimuli were previously displayed. The subject's response times are recorded and a faster response to the probe when it appears in the previous location of a threatening stimulus is interpreted as vigilance for threat, indicating attentional bias.
Individuals suffering from emotional disorders exhibit negative attentional biases. Notably, this negative attention bias can also be present in non-depressed individuals with high risk of developing depression, as well as individuals who have recovered from episodes of depression. In general, studies on healthy adults show that the prefrontal cortex plays a role in response inhibition, specifically the right inferior frontal cortex region. When presented with competing stimuli, certain responses need to be inhibited in order to make a decision. In the case of attention biases, the lateral prefrontal cortex contributes by modulating responses to emotional information. Deficits in response inhibition result in a bias towards certain emotional information.
A common application of the dot-probe task is in attention bias modification (ABM), an experimental procedure for treatment of depression, with the intention of supplementing cognitive behavioural therapy (CBT) or as a treatment on its own. Besides treating emotional disorders, attention bias modification interventions are also being used to treat eating disorders, alcohol dependency, and social phobias. ABM procedures modify attention biases in emotional disorders, resulting in subjects learning to deploy their attention toward the more positive stimuli. A computerized attention bias modification intervention for depression involves repeatedly redirecting the attention of the subject away from emotionally relevant threat cues, and towards neutral (non-threatening) stimuli. The effects of the attention bias training are assessed by examining the motivational outcomes on the subjects (i.e. depressive assessment scores). Studies examining the effects of ABM on depressive symptoms generally found reduced symptoms where the attentional biases were successfully modified.
Deep breathing is another promising approach to cognitive-behavioral interventions for mood disorders. Deep breathing exercises are known to decrease heart rate and stimulate parasympathetic relaxation. There are observable physical changes associated with breathing relaxation, such as reduced metabolism, muscle tension, brain activity and skin resistance. These effects are associated with lowered anxiety and depression, better quality of sleep, and enhanced concentration. This has led to a growing body of work regarding the use of deep breathing techniques to combat mental health symptoms associated with various physical and mental disorders. Deep breathing exercises have been employed in research on chronic cardiovascular disease, post-traumatic stress disorder (PTSD), pain management, depression, and anxiety.
In most deep breathing studies, the duration and frequency of the breathing patterns are notably different across different studies. In a study on the effect of deep breathing duration on depressive symptoms by Cheng et al. (2019), it was found that deep breathing for 5, 7 and 9 minutes produced higher activation of the parasympathetic nervous system compared to the control group. However, only deep breathing durations of 7 or 9 minutes produced significantly lower self-report depressive scores, with the 9-minute group achieving a larger effect size than the 7-minute group. As for breathing frequency, a rate of 6 breaths per minute has been extensively practiced in numerous studies as it has been found to result in significant differences in heart rate variability measures compared to other rates and natural breathing rates.
Attention bias modification paradigms and deep breathing exercises have potential as both standalone treatments for mood disorders and complementary regimens to pharmacotherapy. A meta-analysis has found that while psychotherapy and medication are both efficacious in improving depressive symptom severity, a combination of both provides significantly better outcomes for patients. The development of interventions such as attention bias modification and deep breathing training would contribute towards creating highly accessible tools for management and alleviation of depression symptoms. When administered in combination with other psychotherapy and antidepressant treatments, these remote interventions could improve the quality of the mental healthcare experience for patients and healthcare professionals.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Experimental: Attention Bias Modification Training Participants randomized to the ABMT group will undergo active attention bias modification training. The emoji-based ABMT protocol will be adapted from the attention bias modification task from Browning et al., 2012. The stimuli used during the task are pictures of emoji displaying emotional expressions that have valences that are either positive, neutral, or negative. The positive, negative and neutral emojis will be chosen from the outcome of a preliminary rating questionnaire. |
Behavioral: Attention Bias Modification
Attention bias modification (ABM) is a procedure for treatment of depression, with the intention of supplementing cognitive behavioural therapy (CBT) or as a treatment on its own. ABM procedures modify attention biases in emotional disorders, resulting in subjects learning to deploy their attention toward the more positive stimuli (Jonassen et al., 2018). A computerized attention bias modification intervention for depression involves repeatedly redirecting the attention of the subject away from emotionally relevant threat cues, and towards neutral (non-threatening) stimuli (Amir et al., 2009). The location of the probe will replace the relatively positive stimulus in the pair with 100% probability.
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| Sham Comparator: Sham Training Participants in the sham control group will receive a sham version of the ABMT task. This condition is identical to the active ABM condition except for the location of the probe, which replaces the positive, negative, and neutral stimuli with equal probability. This control procedure is not expected to modify any underlying biases present. |
Behavioral: Sham Training
This condition is identical to the Attention Bias Modification condition with the except of the location of the probe, which replaces the positive, negative, and neutral stimuli with equal probability. This control procedure is not expected to modify any underlying biases present.
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| Active Comparator: Deep-breathing training The protocol for the deep breathing practice will be adapted from the procedure outlined in (Cheng et al., 2019). Participants randomized to the deep breathing group will undergo mindful deep breathing practice. Participants will be required to follow an instructional video and perform mindful deep breathing. The video guide will be sent to each participant in the deep breathing group, and they will be instructed to perform the exercise once a day at any time of their choice for the 14-day period. |
Behavioral: Deep-breathing training
In most deep breathing studies, participants are required to alter their breathing pattern to a specific frequency for a specific duration of time. In the present study, participants will be required to perform deep-breathing at a rate of 6 breaths per minute for 9 minutes.
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| No Intervention: No-intervention control Participants in the no-intervention control group will not be required to undergo any intervention. |
Outcome Measures
Primary Outcome Measures
- Attention Bias Index [Up to 14 days]
The participant response times from the ABM task will be collected and used to obtain an attention bias index which is calculated using the formula: Attention bias index = ½ [RpLe - RpRe) + (LpRe - LpLe)] where R is right position, L is left position, p is the position of the probe, and e is the position of the emotional (positive/negative) stimulus. A positive score indicates a bias toward emotional stimuli, while a negative score indicates a bias away from emotional stimuli. A score of 0 indicates no bias in either direction. The higher the score value, the stronger the bias.
- Post-Intervention Event-related Potentials [Day 14]
Participants' EEG signal will be obtained using a 32-channel EEG system. EEG power in all bands and the event-related potential waveform will be extracted from the signal. ERP measures are widely adopted as an objective measure of the time course of attention during the dot-probe task.
- Change from Baseline Patient Health Questionnaire-9 (PHQ-9) Score at 14 days [Baseline and Day 14]
The PHQ-9 is a self-administered instrument for screening and monitoring the severity of depression. The PHQ-9 uses the following scale: a score of 0 to 4 indicates a severity of "None", 5 to 9 indicates "Mild", 10 to 14 indicates "Moderate', 15 to 19 indicates "Moderately Severe", and 20 to 27 indicates "Severe".
- Change from Baseline Depression, Anxiety and Stress Scale-21 (DASS-21) Score at 14 days [Baseline and Day 14]
The DASS-21 is a questionnaire designed to assess the dimensions of depression, anxiety and stress. It consists of 21 self-report items. Depression severity is measured on the DASS-21 as follows: a score of 0 to 4 is labelled "Normal", 5 to 6 is "Mild", 7 to 10 is "Moderate", 11 to 13 is "Severe", and 14 and above is "Extremely Severe".
Secondary Outcome Measures
- Heart Rate Variability [Day 1, Day 14]
A photoplethysmogram (PPG) will be obtained from participants to obtain heart rate and cardiac cycle data. From the cardiac cycle, the variation in the intervals between each heart beat can be retrieved, which gives the heart rate variability (HRV). HRV measures are used as an index for the activity of the parasympathetic and sympathetic nervous systems, which are associated with various psychological states.
- Hair Cortisol [Day 1]
Hair samples will be collected from participants for a hair cortisol test. Approximately 20 strands of hair will be collected from the head for the test to determine the cortisol levels of the participant. Cortisol is a naturally-occurring steroid hormone that is associated with the body's stress response. Chronically high levels of cortisol increases the risk of mood disorders such as anxiety and depression.
- Pre-Intervention Event-Related Potentials [Baseline]
Participants' EEG signal will be obtained using a 32-channel EEG system. EEG power in all bands and the event-related potential waveform will be extracted from the signal. ERP measures are widely adopted as an objective measure of the time course of attention during the dot-probe task.
Eligibility Criteria
Criteria
Inclusion Criteria:
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Aged between 18 and 30 years old
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Give informed consent
Exclusion Criteria:
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Past or present diagnosis of other major psychiatric disorders (e.g., suicidality, substance dependence, psychosis)
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Recently started psychotropic or medical prescriptions within the previous two weeks
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Visual impairments that cannot be corrected with contact lenses or glasses
Contacts and Locations
Locations
No locations specified.Sponsors and Collaborators
- Universiti Tunku Abdul Rahman
Investigators
None specified.Study Documents (Full-Text)
None provided.More Information
Additional Information:
- Progressing Social Good by Reducing Mental Health Care Inequality with Persuasive Technology
- WHO Mental Disorders Fact Sheet
Publications
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- Irwin CE Jr. Using Technology to Improve the Health and Well-Being of Adolescents and Young Adults. J Adolesc Health. 2020 Aug;67(2):147-148. doi: 10.1016/j.jadohealth.2020.05.019.
- Jerath R, Crawford MW, Barnes VA, Harden K. Self-regulation of breathing as a primary treatment for anxiety. Appl Psychophysiol Biofeedback. 2015 Jun;40(2):107-15. doi: 10.1007/s10484-015-9279-8. Review.
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- Rojas G, Martínez V, Martínez P, Franco P, Jiménez-Molina Á. Improving Mental Health Care in Developing Countries Through Digital Technologies: A Mini Narrative Review of the Chilean Case. Front Public Health. 2019 Dec 20;7:391. doi: 10.3389/fpubh.2019.00391. eCollection 2019. Review.
- Vazquez C, Blanco I, Sanchez A, McNally RJ. Attentional bias modification in depression through gaze contingencies and regulatory control using a new eye-tracking intervention paradigm: study protocol for a placebo-controlled trial. BMC Psychiatry. 2016 Dec 8;16(1):439.
- Wadlinger HA, Isaacowitz DM. Fixing our focus: training attention to regulate emotion. Pers Soc Psychol Rev. 2011 Feb;15(1):75-102. doi: 10.1177/1088868310365565. Epub 2010 Apr 30. Review.
- Wilson D, Heaslip V, Jackson D. Improving equity and cultural responsiveness with marginalised communities: Understanding competing worldviews. J Clin Nurs. 2018 Oct;27(19-20):3810-3819. doi: 10.1111/jocn.14546. Epub 2018 Aug 1.
- Zhao Q, Lu Y, Zhou C, Wang X. Effects of chronic exercise on attentional bias among individuals with methamphetamine use disorder. Psychology of Sport and Exercise. 2021; 52(8).
- FRGS/1/2021/SKK06/UTAR/02/4