Depressive SymptomsNCT05415306
Emoji-based Attention Bias Modification Training for Depressive Young Adults
A study testing Attention Bias Modification and Deep-breathing training in people with Depressive Symptoms and Mood Disorders, run by Universiti Tunku Abdul Rahman.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 to 30 yearsHealthy volunteers can take part
- Conditions the study is for
- Depressive Symptoms, Mood Disorders
- What is being tested?
- Attention Bias Modification and Deep-breathing training
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- Yes, some participants may receive a placebo
- How many people
- 120 participants
- Where
- No sites listed yet
- Study dates
- Jul 2022to Sep 2024
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 30 years
- All sexes
- Healthy volunteers accepted
- Adult
Who may be able to join
- Aged between 18 and 30 years old
- Give informed consent
Who cannot join
- Past or present diagnosis of other major psychiatric disorders (e.g., suicidality, substance dependence, psychosis)
- Recently started psychotropic or medical prescriptions within the previous two weeks
- Visual impairments that cannot be corrected with contact lenses or glasses
About this study
Official title: An Emoji-based Attention Bias Modification Intervention for Depressive Symptom Severity in Young Adults
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.
Read the 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.
- Conditions
- Depressive Symptoms, Mood Disorders
- Being tested
- Attention Bias Modification, Deep-breathing training, Sham Training
- Keywords
- Attention, Attention Bias Modification
- Medical subject headings
- Depression, Mood Disorders
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Attention Bias ModificationBehavioural
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.
Deep-breathing trainingBehavioural
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.
Sham TrainingBehavioural
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.
| Study group | Role | What they receive |
|---|---|---|
| Attention Bias Modification Training | Experimental | 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. Receives: Behavioral: Attention Bias Modification |
| Sham Training | Sham comparator | 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. Receives: Behavioral: Sham Training |
| Deep-breathing training | Active comparator | 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. Receives: Behavioral: Deep-breathing training |
| No-intervention control | No intervention | Participants in the no-intervention control group will not be required to undergo any intervention. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Attention Bias Index
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.
Measured: Up to 14 days
Post-Intervention Event-related Potentials
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.
Measured: Day 14
Change from Baseline Patient Health Questionnaire-9 (PHQ-9) Score at 14 days
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".
Measured: Baseline and Day 14
Change from Baseline Depression, Anxiety and Stress Scale-21 (DASS-21) Score at 14 days
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".
Measured: Baseline and Day 14
Secondary outcomes (3)
Heart Rate Variability
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.
Measured: Day 1, Day 14
Hair Cortisol
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.
Measured: Day 1
Pre-Intervention Event-Related Potentials
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.
Measured: Baseline
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Jun 2022
- Study startJul 2022 (estimated)
- Primary completionJul 2023 (estimated)
- Study completionSep 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (52)Papers the sponsor has linked to this study.
- Other trials for Depressive SymptomsStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Participant
- Enrolment
- 120 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Universiti Tunku Abdul Rahman
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Poh Foong Lee, PhD, Universiti Tunku Abdul Rahman
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05415306
- Sponsor's protocol ID
- FRGS/1/2021/SKK06/UTAR/02/4
- Status last verified
- Jun 2022
- First submitted
- 24 May 2022
- Last updated
- 13 Jun 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Caldwell C, Victoria HK. Breathwork in body psychotherapy: Towards a more unified theory and practice. Body, Movement and Dance in Psychotherapy. 2011; (2): 89-101.
Huckvale K, Venkatesh S, Christensen H. Toward clinical digital phenotyping: a timely opportunity to consider purpose, quality, and safety. NPJ Digit Med. 2019 Sep 6;2:88. doi: 10.1038/s41746-019-0166-1. eCollection 2019.
PubMed 31508498Irwin 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. No abstract available.
PubMed 32739018Jerath 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.
PubMed 25869930Middleton J. Let's talk about mental health. Nurs Times. 2013 Feb 19-25;109(7):27. No abstract available.
PubMed 23513938Naslund JA, Gonsalves PP, Gruebner O, Pendse SR, Smith SL, Sharma A, Raviola G. Digital Innovations for Global Mental Health: Opportunities for Data Science, Task Sharing, and Early Intervention. Curr Treat Options Psychiatry. 2019 Dec;6(4):337-351. doi: 10.1007/s40501-019-00186-8. Epub 2019 Sep 7.
PubMed 32457823Rojas G, Martinez V, Martinez P, Franco P, Jimenez-Molina A. 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.
PubMed 31921754Vazquez 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. doi: 10.1186/s12888-016-1150-9.
PubMed 27931196Wadlinger 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.
PubMed 20435804Wilson 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.
PubMed 29869819Zhao 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).
Agelink MW, Boz C, Ullrich H, Andrich J. Relationship between major depression and heart rate variability. Clinical consequences and implications for antidepressive treatment. Psychiatry Res. 2002 Dec 15;113(1-2):139-49. doi: 10.1016/s0165-1781(02)00225-1.
PubMed 12467953Akinsola, E. F., Nwajei, A. D. Test anxiety, depression and academic performance: Assessment and management using relaxation and cognitive restructuring techniques. Psychology. 2013; 04(06), 18-24.
Amir N, Beard C, Taylor CT, Klumpp H, Elias J, Burns M, Chen X. Attention training in individuals with generalized social phobia: A randomized controlled trial. J Consult Clin Psychol. 2009 Oct;77(5):961-973. doi: 10.1037/a0016685.
PubMed 19803575Angermeyer MC, van der Auwera S, Carta MG, Schomerus G. Public attitudes towards psychiatry and psychiatric treatment at the beginning of the 21st century: a systematic review and meta-analysis of population surveys. World Psychiatry. 2017 Feb;16(1):50-61. doi: 10.1002/wps.20383.
PubMed 28127931
Study at a glance
From the registry record, last updated by the sponsor on 13 Jun 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- An Emoji-based Attention Bias Modification Intervention for Depressive Symptom Severity in Young Adults
- ClinicalTrials.gov ID
- NCT05415306
- Acronym / sponsor ID
- FRGS/1/2021/SKK06/UTAR/02/4
- Conditions
- Depressive Symptoms, Mood Disorders
- Keywords
- Attention, Attention Bias Modification
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 120 participants (estimated)
- Lead sponsor
- Universiti Tunku Abdul RahmanUniversity, hospital or other
- Study start
- Jul 2022 (estimated)
- Primary completion
- Jul 2023 (estimated)
- Study completion
- Sep 2024 (estimated)
- First posted
- 13 Jun 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
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
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (participant)
- Number of arms
- 4
| Arm | Type | Receives |
|---|---|---|
| Attention Bias Modification Training | Experimental | Behavioral: Attention Bias ModificationParticipants 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. |
| Sham Training | Sham comparator | Behavioral: Sham TrainingParticipants 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. |
| Deep-breathing training | Active comparator | Behavioral: Deep-breathing trainingThe 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. |
| No-intervention control | No intervention | –Participants in the no-intervention control group will not be required to undergo any intervention. |
Who may qualify
- Ages
- 18 to 30 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult
Key inclusion criteria (2 listed)
- Aged between 18 and 30 years old
- Give informed consent
Key exclusion criteria (3 listed)
- Past or present diagnosis of other major psychiatric disorders (e.g., suicidality, substance dependence, psychosis)
- Recently started psychotropic or medical prescriptions within the previous two weeks
- Visual impairments that cannot be corrected with contact lenses or glasses
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Attention Bias ModificationAttention 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. | Behavioural | Attention Bias Modification Training |
| Deep-breathing trainingIn 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. | Behavioural | Deep-breathing training |
| Sham TrainingThis 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. | Behavioural | Sham Training |
Primary outcome
Attention Bias Index
Time frame: 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
Time frame: 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
Time frame: 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
Time frame: 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".
3 secondary outcomes
Heart Rate Variability
Time frame: Day 1, Day 14
Hair Cortisol
Time frame: Day 1
Pre-Intervention Event-Related Potentials
Time frame: Baseline
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 Jun 2022.
- BackgroundCaldwell C, Victoria HK. Breathwork in body psychotherapy: Towards a more unified theory and practice. Body, Movement and Dance in Psychotherapy. 2011; (2): 89-101.
- Background: PubMed 31508498Huckvale K, Venkatesh S, Christensen H. Toward clinical digital phenotyping: a timely opportunity to consider purpose, quality, and safety. NPJ Digit Med. 2019 Sep 6;2:88. doi: 10.1038/s41746-019-0166-1. eCollection 2019.
- Background: PubMed 32739018Irwin 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. No abstract available.
- Background: PubMed 25869930Jerath 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.
- Background: PubMed 23513938Middleton J. Let's talk about mental health. Nurs Times. 2013 Feb 19-25;109(7):27. No abstract available.
- Background: PubMed 32457823Naslund JA, Gonsalves PP, Gruebner O, Pendse SR, Smith SL, Sharma A, Raviola G. Digital Innovations for Global Mental Health: Opportunities for Data Science, Task Sharing, and Early Intervention. Curr Treat Options Psychiatry. 2019 Dec;6(4):337-351. doi: 10.1007/s40501-019-00186-8. Epub 2019 Sep 7.
- Background: PubMed 31921754Rojas G, Martinez V, Martinez P, Franco P, Jimenez-Molina A. 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.
- Background: PubMed 27931196Vazquez 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. doi: 10.1186/s12888-016-1150-9.
- Background: PubMed 20435804Wadlinger 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.
- Background: PubMed 29869819Wilson 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.
- BackgroundZhao 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).
- Results publication: PubMed 12467953Agelink MW, Boz C, Ullrich H, Andrich J. Relationship between major depression and heart rate variability. Clinical consequences and implications for antidepressive treatment. Psychiatry Res. 2002 Dec 15;113(1-2):139-49. doi: 10.1016/s0165-1781(02)00225-1.
- WHO Mental Disorders Fact SheetLink provided by the sponsor.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
Questions about this trial
What is this clinical trial studying?
A study testing Attention Bias Modification and Deep-breathing training in people with Depressive Symptoms and Mood Disorders, run by Universiti Tunku Abdul Rahman.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 13 Jun 2022. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. Some participants in this study may receive a placebo. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Attention Bias Index (time frame: Up to 14 days). The study lists 4 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05415306, which also lists 52 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 13 Jun 2022.