Biomedical Approaches for Understanding Depression

Research Methods Table for TMA02: Understanding Experimental Design

Rosso, I. M., Killgore, W. D. S., Olson, E. A., Webb, C. A., Fukunaga, R., Auerbach, R. R., Gogel, H., Buchholz, J. L. and Rauch, S. L. (2017) ‘Internet‐based cognitive behaviour therapy for major depressive disorder: A randomized controlled trial’,

Depression & Anxiety,

vol.34, no.3, pp. 236-245 [online]. Available at:

https://doi.org/10.1002/da.22590

(accessed 3 January 2020)

In your own words, describe the aim or objective of the study.

(2 marks)

The aim of the study was to use a version of the Australian Sadness program which was based on internet cognitive behavioural therapy (ICBT) to treat major depression (MD) with a monitored attention control (MAC) group. [36]

What was the independent variable?

(2 marks)

See Book 1, Box 2.1; Book 2, Box 2.2

The independent variable is the ICBT program. [7]

What were the conditions of the independent variable? Note: read the boxes referred to immediately below to check your understanding of the term ‘conditions’ before answering this question.

(2 marks)

See Book 1, Boxes 2.1 and 2.2; Book 2, Box 2.2

There are two conditions: ICBT participants and MAC participants. [9]

What assessment scales were used to specifically measure the dependent variable and when were they measured?

(6 marks)

See Book 1, Box 2.1; Book 2, Box 2.2

The assessment scales used to measure the dependent variable was the Hamilton rating scale for depression (HRSD), the patient health questionnaire (PHQ-9) with a score range between 0-52 and the Kessler distress scale (K-10) with a score range between 0-27. The PHQ-9 was used on day 1 and then all scales were used on day 2 and 3. [59]

What was the null hypothesis for this study? Please ensure you write this in the correct format (see Book 1, Box 2.1) and include the specific detail of the measures used and the groups in the study.

(2 marks)

There will be no difference in major depression disorder between the ICBT participants and the monitored attention control (MAC) participants. [20]

What was the experimental hypothesis? Please ensure you write this in the correct format See Book 1, Box 2.1

(2 marks)

There will be a greater reduction in major depression disorder symptoms in ICBT participants compared to the MAC participants. [19]

Where were the participants recruited from in this study? (

2 marks

)

Participants were recruited from an internet advertisement and community fliers. [10]

List two criteria that were used to determine participant eligibility. (

2 marks)

List two exclusion criteria (

2 marks)

See Book 1, Box 2.2

Two exclusion criteria are current alcohol abuse and lifetime history of bipolar disorder or schizophrenia spectrum disorder. [17]

What type of design was used (was it between or within participants)?

(1 marks)

What problem might arise using this type of design?

(1 mark)

See Book 1, Boxes 2.2 and 3.1

In this study was used both designs: between and within participants. [11]

The problem arises is the allocation of participants randomly into the two conditions. [13]

List two types of demographic data collected.

Were there any significant differences in the demographics of the participants?

(4 marks)

See Book 1, Section 4.2.5

The two types of demographic data collected were age and HRSD. [11]

No, there were any differences. ICBT: n= 37 and MAC: n= 40 as shown in table 2 pp. 241. [19]

Were there significant differences in the baseline HRSD scores between participants?

(2 marks)

Were there any significant differences in HRSD scores after treatment?

(2 marks)

Were there any significant differences in self-reported depression and distress measures following treatment. Provide supporting information to explain your answer.

(3 marks)

No, there is no difference in baseline HRSD scores between participants.  [11]

Yes, HRSD score for the ICBT participants were 9.17± 6.92 while the MAC participants were 14.05 ± 5.34. [18]

Yes. There was an improvement in PHQ-9 scores in the ICBT group than in the MAC group: F (21, 63) = 5.32; P = 0.024, and in the distress levels had a greater  improvement in ICBT than MAC as well, F(21, 62.1) = 9.82; P= 0.003 from fig.2. pp.240. [49]

Decide whether the study has external validity – Yes or No. Clearly state this and then explain your answer.

(4 marks)

See Book 2, Box 3.1

Yes. This study has external validity because it can be applied to a larger scale of population. This is shown in the statement: ‘With its potential to be delivered in a scalable, cost-efficient manner, ICBT is a promising strategy to enhance access to effective care’ (Rosso, I. M., et al, 2017). [51]

Decide whether the study results are reliable – Yes or No. Clearly state this and then explain your answer.

(4 marks)

See Book 1, Section 4.2.4; Book 2, Box 3.1

Yes. This study is reliable because is led by different clinicians and they all have the same results and conclusions. This is shown in the statement: ‘Our result is consistent with prior reports on the efficacy of ICBT for depression generally’ (Rosso, I. M., et al, 2017). [47]

State two ways the researchers tried to prevent or reduce confounding/extraneous variables.

(2 marks)

See Book 1, Box 1.2; Book 2, Box 2.2

ICBT group had CBT lessons and homework assignments, while the MAC group had ‘lessons’ consisting in questionnaires. Both groups received weekly phone calls which were limited. [26]

a)

CBT and mindfulness are described as psychological interventions. Using book 2 describe two similarities and one difference between them.

(3 marks)

b)

In figure 2.12, chapter 2, book 2 psychotherapy (and therefore CBT) is considered in relation to the network hypothesis of mood.   Briefly describe the network hypothesis of mood.



(6 marks)

Both CBT and mindfulness deals with the present and they consist in awareness of negative thoughts replacing them by positive thoughts. They both have affective and cognitive components  (Datta 2010, pp. 92 and pp. 142). The differences between CBT and mindfulness is that mindfulness does not take the social side of biopsychological model in account where CBT does (Held, 2004 in Datta 2010, pp. 145). [65]

The network hypothesis of mood was led after limitations of neurotrophic hypothesis. A healthy brain has a network of neurons that process information, but in depression patients, these networks do not function normally because some neurons are damaged or die. Castre’n (2005) suggests that there are different ways to repair this network of neurons including the ADMs, electroconvulsive therapy (ECT) and psychotherapy (Datta 2010, pp.68). This types of treatments enhance plasticity leading for the recovering of connection in damaged network of neurons (Datta 2010, pp.69). [85]

Suggest two potential improvements to this study and explain why these would be improvements.

(4 marks)

A potential improvement for this study could be to get an ICBT app in the smartphone, as everyone nowadays has a smartphone ICBT could be carry on everywhere. Might be helpful for people with crises anywhere they are, instead of waiting until get home and get into their laptops. The other improvement could be getting a rigorous control group to have more efficacy on the study when compared with the randomized group.  [72]

Words: 655

Question 2

‘What the biomedical approach has contributed to understanding depression’.

At one point in life, some people feel sad, hopeless and use the term ‘low mood’ when they feel depressed. Depression can persist for weeks, months or even years and is one of the most common mental illness. It is an example of many types of affective disorders, which affect areas of the brain such the hippocampus and prefrontal cortex (Datta 2010, pp.1). These areas of the brain are important to explain how depression happen in the biomedical approach, which believes that any disease, even if associated with mental distress will be explained by biological factors (Toates 2010, pp.13). First, let’s see how neurons communicate and what causes these alterations to understand Depression (MD).

Neurons send messages to each other by electrical signals called action potential which is a pulse of electricity that triggers neurotransmitters to pass from one neuron to the other through the synaptic gap (Toates 2010, pp.42). Depression is linked with chemical imbalances in the neurotransmitters serotonin and noradrenaline. Serotonin is involved in the control of sleep, eating and mood (Toates 2010, pp.51) and there is evidence that a decrease in the production of this neurotransmitter causes depression. This led researchers to attempt various hypotheses to explain the causes of disorders in the brain. This all started when medications such as antidepressants (ADMs) were discovered by accident in the 1950s when a drug given to high blood pressure called Reserpine developed depression as a side effect (Datta 2010, pp58a).

The first hypothesis was the monoamine hypothesis. This hypothesis started when researchers found that reserpine reduces the levels of monoamines such as serotonin and noradrenaline in order of stopping them from being taken up by vesicles. For this reason, there was an increase of monoamines in the synaptic gap increasing neurotransmissions. Later in the year, it was discovered that isoniazid used for tuberculosis patients was lifting a pre-existing depression. This drug inhibits the enzyme monoamine oxidase (MAO) which breaks down monoamines. MAO was the first ADMs discovered (Datta 2010, pp. 58b). This finding suggests that decreased levels of monoamines cause depression and increase of monoamines lifts depression (Datta 2010, pp. 59). This has been supported by post-mortem studies where high levels of serotonin was found on the prefrontal cortex of depressed and suicidal patients. However, the relationship between the levels of monoamines and depression is not clear yet, because the response of ADMs to the symptoms of depression can take several weeks (Datta 2010, pp 63a).

With the limitations of the monoamine hypothesis, researchers have questioned if the serotonin levels in the brain raised immediately after taking SSRIs, why would not the mood increase immediately as well? Why the long delays? (Human et al., 1997 in Datta 2010, pp. 63b). Was then proposed that the birth of neurons (neurogenesis) and the growth of connections between neurons which are characteristics of plasticity (Datta 2010, pp.63c) are related to brain chemicals such as brain-derived neurotrophic factors (BDNF) which promotes the growth and birth of neurons. The BDNF works in the hippocampus and prefrontal cortex which is involved in affective disorders as mention previously (Datta 2010, pp. 64a). Post-mortem studies show that the levels of BDNF are low in patients with depression (Martinowich et al., 2007 in Datta 2010, pp. 64b). These findings led to the neurotrophic hypothesis where there is a relationship between the levels of BDNF and depression. Duman et al., (1997, 1999) discovered that the hippocampus exhibits neurogenesis. Such evidence shows that neurogenesis in the hippocampus is susceptible to the effect of stress moreover, the neurotrophic hypothesis is linked with psychological factors (Datta 2010, pp. 64b). Experiments in rats show that the use of SSRIs stimulate the production of new neurons in the hippocampus (Malberg et al., 2000 in Datta 2010, pp.65a), meaning that serotonin stimulates the production of BDNF, so ADM’s treatments prevents or reverses reduction levels of BDNF (Datta 2010, pp. 65b). Santarelly et al., (2003) performed tests in rats to show the efficacy of ADMs, however, there are limitations to prove this in humans, as human brains are more complex than mice.

As suggested, both hypotheses have strong evidence of the biomedical approach, but there is evidence linked with psychological factors such as stress. Stressful or traumatic event triggers depression, so the role of the environment determines the behaviour of a person (Datta 2010, pp.70a). Environment is everything outside the genes. Not everyone under stress develops depression, so this led to a gene-environment model which suggests the interaction between biological and environmental factors (Datta 2010, pp. 70b-71), where vulnerable people are susceptible to develop behavioural disorders and people who are not vulnerable might not develop such behavioural disorders. Interaction between gene-environment can explain depression. There are evidences that the environment can affect the working of genes (Datta 2010, pp.74). This was shown in a study performed by Seymour Levnis (Levine, 1957) where rat pups that had extra maternal care, including licking and grooming showed less stress and anxiety as adults (Datta 2010, pp.75a). Later, in Meaney et al., a study showed that rat pups with low licking and grooming mother had higher levels of corticosterone (a glucocorticoid) than those with higher licking and grooming mothers showing a dysregulation on the HPA axis. Meaney and his team found that maternal licking and grooming behaviours made a difference and that early stressful events can affect animal life (Datta 2010, pp. 75b). This means that using a biopsychological approach is important as well to understand depression.

To summarise, the biomedical approach give us a good understanding of depression looking into the biological factors such as chemical imbalances present in the brain but by looking at the hypotheses and the gene-environment model proposed by researchers is possible to understand that the biological factors are not the only factor to take in account and it does not explain the psychological and social factors involved. Provided that, it is an advantage to understand how does the brain work and how to use medications such as ADMs but this is not always the best approach because it is just taking the biological factor in consideration.

References

• Datta, S. (2010)
  
  Mood and well-being,
  
  SDK228 The Science of Mind: Investigating mental health, Milton Keynes, The Open University, pp.1
• Datta, S. (2010)
  
  Mood and well-being,
  
  SDK228 The Science of Mind: Investigating mental health, Milton Keynes, The Open University, pp.58a
• Datta, S. (2010)
  
  Mood and well-being,
  
  SDK228 The Science of Mind: Investigating mental health, Milton Keynes, The Open University, pp.58b
• Datta, S. (2010)
  
  Mood and well-being,
  
  SDK228 The Science of Mind: Investigating mental health, Milton Keynes, The Open University, pp.59
• Datta, S. (2010)
  
  Mood and well-being,
  
  SDK228 The Science of Mind: Investigating mental health, Milton Keynes, The Open University, pp. 63a
• Datta, S. (2010)
  
  Mood and well-being,
  
  SDK228 The Science of Mind: Investigating mental health, Milton Keynes, The Open University, pp.63b
• Datta, S. (2010)
  
  Mood and well-being,
  
  SDK228 The Science of Mind: Investigating mental health, Milton Keynes, The Open University, pp.63c
• Datta, S. (2010)
  
  Mood and well-being,
  
  SDK228 The Science of Mind: Investigating mental health, Milton Keynes, The Open University, pp.64a
• Datta, S. (2010)
  
  Mood and well-being,
  
  SDK228 The Science of Mind: Investigating mental health, Milton Keynes, The Open University, pp.64b
• Datta, S. (2010)
  
  Mood and well-being,
  
  SDK228 The Science of Mind: Investigating mental health, Milton Keynes, The Open University, pp.65a
• Datta, S. (2010)
  
  Mood and well-being,
  
  SDK228 The Science of Mind: Investigating mental health, Milton Keynes, The Open University, pp.65b
• Datta, S. (2010)
  
  Mood and well-being,
  
  SDK228 The Science of Mind: Investigating mental health, Milton Keynes, The Open University, pp.70a
• Datta, S. (2010)
  
  Mood and well-being,
  
  SDK228 The Science of Mind: Investigating mental health, Milton Keynes, The Open University, pp.70b-71
• Datta, S. (2010)
  
  Mood and well-being,
  
  SDK228 The Science of Mind: Investigating mental health, Milton Keynes, The Open University, pp.74
• Datta, S. (2010)
  
  Mood and well-being,
  
  SDK228 The Science of Mind: Investigating mental health, Milton Keynes, The Open University, pp.75a
• Datta, S. (2010)
  
  Mood and well-being,
  
  SDK228 The Science of Mind: Investigating mental health, Milton Keynes, The Open University, pp.75b
• Toates, F. (2010)
  
  Core Concepts in Mental health
  
  , SDK228 The Science of Mind: Investigating mental health, Milton Keynes, The Open University, pp. 13
• Toates, F. (2010)
  
  Core Concepts in Mental health
  
  , SDK228 The Science of Mind: Investigating mental health, Milton Keynes, The Open University, pp.42
• Toates, F. (2010)
  
  Core Concepts in Mental health
  
  , SDK228 The Science of Mind: Investigating mental health, Milton Keynes, The Open University, pp.51