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Trial of Problem Solving and Depression Treatment

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    Research Critique of “Randomized controlled trial of problem solving treatment, antidepressant medication, and combined treatment for major depression in primary care”




    Research Critique of “Randomized controlled trial of problem solving treatment, antidepressant medication, and combined treatment for major depression in primary care”

    As stated by the Royal College of Nursing (1993), nurses should be able to expand their knowledge and skilled to initiate changes in their practice through reviewing and evaluating research studies.  The foundation of nursing is an evidence-based practice that involves finding, critiquing and applying evidences within the field.

    Critique research involves a careful examination of all aspects of the research so as to judge its strengths, weaknesses, purpose, and importance (Hek 1996).  The aim of this paper is to critique the study of a randomized controlled trial of problem solving treatment, antidepressant medication, and combined treatment for major depression in primary care.  The reason why I selected the mentioned study is because of its relevance to the filed of psychiatric nursing specifically the treatment of depression.

    The current research critique uses the critique tools produced by the Agency for Health Research and Quality (AHRQ).  The critique paper is divided into four sections: its relevance to my topic or question, the conclusions, my confidence in its findings, and how well the findings carry over to the settings I’m interested in (Appendix A).


    Based on the introduction of the study, the research was conducted to examine whether a combination of problem solving treatment with antidepressant medication is more effective than either treatment alone.  The researchers also studied the effectiveness of problem solving treatment administered by practice nurses in comparison to general practitioners having both trained in the technique.

    Its relevance to my topic or question

    My research question is related to the treatment of depression and how nurses can take an active role in partner of the patient in his or her recovery.  The PICO framework can be applied to the study with patients who are depressed as the population; the interventions used are problem solving treatment by research general practitioner or research practice nurse or antidepressant medication or a combination of problem solving treatment and antidepressant medication; the comparison between the subjects as groups were measured using Hamilton rating scale for depression, Beck Depression Inventory, clinical interview schedule, and the modified social adjustment schedule assessed at 6, 12, 52 weeks; and, finally, the outcome showed that patients have clear improvement over 12 weeks, the four kinds of treatments were effective, and the effectiveness of the four treatments regardless whether suitably trained practice nurses or general practitioners administered the problem solving or medication treatments.

      The abstract of the paper showed the objectives, design, setting, participants, interventions, main outcome measures, results, and conclusions of the study.  The researchers utilized a randomized, controlled trial with four treatment groups namely (1) problem solving treatment given by research general practitioners; (2) problem solving treatment given by research practice nurses; (3) antidepressant medication given by research general practitioners; and (4) combined problem solving treatment and antidepressant medication.  The selection of the participants were based on the following criteria: aged 18 to 65 years old, have a depressive disorder that required treatment but not urgent hospital referral, scored 13 or above on the 17-item Hamilton rating scale for depression, and a minimum duration of illness of four weeks.  Some patients were excluded from the study due to the presence of additional psychiatric disorder prior to the onset of depression; were receiving concurrent treatment with antidepressant medication or psychological treatment; had brain damage, learning difficulties, schizophrenia, drug dependence, recent alcohol abuse, or physical illness; have clinical condition inconsistent in the research protocol such as psychotic features or serious suicidal ideation.  As a result, a total of 151 patients met the entry criteria with 144 patients diagnosed to have definite depression while seven patients have probable major depression.  While this is a good sample size, the problem lies with distribution of the sample.  The sample number for patients with probable major depression, specifically, is rather low.  An equal, if not almost equal, sample size with regard to the categories would have supported data analysis, when determining profound differences between the effectivity of various treatment approaches and definite depression diagnosis as opposed to the seven patients who have probable major depression.

    The study addresses the issue concerning my research question of the treatment of depression and the role of nurses as a partner of the client and his or her recovery.  The research study can also be applied to other branches of nursing care such as geriatric nursing where the nurse can take an active role in rehabilitation programs provided that nurses are trained on how to conduct and manage the necessary nursing intervention deemed appropriate to the recovery of the patients.

    The conclusions

    The abstract showed a shorter version of the conclusion that does not explicitly explain the overall findings of the study.   The abstract simply stated the study arrived to a conclusion that problem-solving treatment is an effective treatment for depressive disorders in primary care.  The combination of this treatment with antidepressant drugs is no more effective than either treatment alone.  The conclusion page, however, explained in detail how appropriately trained nurses can actively participate in the administration of the problem solving treatment given to patients.  It also stated that the problem-solving treatment is a goal oriented, collaborative, and active process and focuses on the present.  This process enables patients to gain a clear sense of involvement in the recovery process.  The conclusion also offered a recommendation that the treatment for depression is suitable for primary care because it’s relatively brief and can be given by primary care nurses.  Lastly, the conclusion page stated recommendations for future studies specifically the first challenge for the future is to provide training for interested practice nurses in delivering the treatment as evaluated; and a need to evaluate a briefer adaptation of problem solving techniques can be used by general practitioners in their regular consultation.

    The study results showed tables and figures as data gathered from the groups of participants.  The conclusion were fairly in favor of the recovery of patients who belonged to the groups of problem solving by general practitioner, problem solving by nurse, and the combination of problem solving and medication treatment.  It does not, however, reflect the decline or drop of the percentage of patients who recovered.  Based on the table, it showed a drop of 4% of the number of patients who recovered on the 12th week and the 52nd week.

    The review of related literature showed an accurate basis of the study.  The literature review supports the study mainly because of studies such as problem solving treatment in primary care has been shown to be effective for major depression; the treatment has been shown to be effective when given by general practitioners; and that community nurses can be trained in problem solving techniques.  The research study confirmed that nurses can be trained to administer problem solving techniques.  Furthermore, the literature review also supports the purpose of problem solving treatment as a therapy to treat major depression.

                The results compares to other studies in the sense that it affirms that nurses can be trained to provide psychological treatments successfully.  In primary care, nurses have used behavioral methods to treat obsessional and phobic patients (Ginsberg et al. 1984).  Nurses have also been used in primary care to try to improve compliance with antidepressant medication (Wilkinson et al. 1993).  In hospitals, nurses also have been trained to incorporate problem-solving techniques in the counseling of patients after intentional self-harm (Hawton and Kirk 1989; Salkovskis et al. 1990).  Thus, the quantitative study of the treatment of depression is supported by other studies.

    The researchers chose to focus on the four treatment groups to determine whether there is any difference on the rate of effectiveness whether it is anti-depressant medications alone, solely problem solving treatment given by general practitioners, problem solving treatment given by nurses, or a combination of problem solving treatment and anti-depressant medication.

    My confidence in its findings in the methods section

    My confidence on the findings of the study is mainly on the large sample size, randomized and controlled manipulation of the subject groups, and characterized by PICO or patient, intervention, comparison and outcomes framework.  Additionally, the methods section should have five principal elements that influence the quality of the findings namely the completeness of the model analyzed, the quality of the measures or methods, the quality of the data, the ability to control the differences between groups being compared, and the appropriateness of the statistical analyses.

    The model analyzed pertains to the description of the dependent variable and independent variable.  The independent variable of the study is the primary care of nurses and general practitioner while the dependent variable is the effectiveness of the treatment for depression.  The relationship of the independent variable and the dependent variable correlates to the outcome of the study.  Thus, the more efficient and well-trained the nurses and general practitioner are in the context of primary care then there is a higher rate of effectiveness of a particular treatment, among the four types, for depression.  The study left out important variables such as the background and experience of the nurses and general practitioners and whether the same primary caregivers were rendered the treatment during the course of the 52-week study.

    The study made use of the two most common tools to assess depression amongst adolescents and adults namely the Hamilton Depression Rating Scale (HDRS) as the main outcome measure and the Beck’s Depression Inventory (BDI-II).  .  The statistical analyses were based on the BDI II and HDRS data.  The BDI-II is a self-report measure while the HDRS serves as an assessment used by therapists in clinical interviews to resolve the severity of depression in adults.  The Hamilton Depression Inventory is composed of 38 questions design to determine 23 items linked with symptoms of depression (Reynolds & Kobak 1995).  Participants answered on a rating scale of zero to four.  This assessment, commonly used in clinical research and practice, is doubted in terms of its standardization of scoring criteria and administration.  On the other hand, the Beck Depression Inventory II assesses 21 items connected with symptoms of depression on a four-point scale of zero to three (Osman, Kopper & Barrios 2004).  BDI II is a widely used assessment tool that has been updated in order to keep up with latest diagnostic criteria for depression based on the DSM-IV.  It has been, however, questioned due to its reliability and validity in measuring depression in such individuals.  The location of test administration and the working relationship of the primary caregivers and patients can influence the data gathered.  There is a greater likelihood that participants are biased on giving the expected positive responses to the tests given.  It is because of the fact that the people who gathered data are their primary caregivers.  The participants were not blinded to the purpose of the study hence promotes bias to the study.

    There were four groups of subjects studied in the research.  There are different from each other.  The first group was given problem solving intervention by general practitioners, second group was given the same intervention but given by trained nurses, third group was medications only, and the fourth group was a combination of the problem solving technique and medications.  Thus, the study has a wider range of control made possible by the four different groups to differentiate and compare the rate of effectiveness on the choice of treatment per group.   The only drawback observed in the study is the time series aspect where it is expected that a higher rate of morbidity of participants can happen.  It means there is a higher possibility that participants might withdraw from the research given its long duration of 52 weeks.

    The study observed a randomization to minimize the differences between the groups being compared.  The sample size is sufficiently large to provide a wider scope for comparison on their responses to treatments given to them, respectively.

    The paper imparts a meaningful conclusion to further support other studies on how primary caregivers specifically nurses can participate in giving psychological treatments successfully.  It provides a higher level of nursing care in a collaborative care when in partnership with the patient towards his or her recovery.

    How well the findings carry over to the settings I’m interested in

      The research study was completed at 2000 at Warneford Hospital based in Oxford, Southeast England.  The time or the course of the study was done on a course of 52 weeks.  The treatment was usually given in the patient’s home or local health centre.

    The circumstances involved in the study such as the year, location, duration of the study, selection criteria of subjects, and setting of the treatment (home or local health center) may be different in another cities in United Kingdom.  Other health centers may not have as many willing participants as compared to the research study being criticized. The severity of depression also play a significant role to its treatment and how effectiveness of treatment given to the patient.  Furthermore, some local health centers may not have adequate number of trained nurses who can render psychological interventions.

                The limitations section is not found in the research paper.  An implication of limitations of the study was integrated in the conclusion section.  The researchers proposed that future studies should be made on evaluation of problem solving techniques used by general practitioners in their regular consultations as well as to provide training for interested practice nurses in delivering treatment for depression.  While these points can be further researched in the future, the study failed to specify limitations such as a lack of homogenous sample groups such as severity of depression, consistent number of participants who completed the 52 weeks duration of the study, and the qualifications and experiences of the general practitioners and trained nurses.


    The research paper provides an affirmation that primary care of nurse can be geared to the administration of psychological interventions.  One of the outcomes of the study is that nurses can effectively render an active and positive role in a collaborative goal with patients towards recovery.  Furthermore, the evidences from the research paper showed that depression could be effectively given through a combination of problem solving treatment and anti depressant medications.  It further proved that the treatment of depression is unsuccessful when anti depressant medication is given without any problem solving treatment.

    List of References

    Ginsberg, M. & Waters, H. (1984)  Cost-benefit analysis of a controlled trial of nurse therapy for neuroses in primary care.  Psychology Medicine Journal. 14:683-690.
    Grove, S. (2005)  The Practice of Nursing Research: Conduct, Critique, and Utilization.   Missourri: Elsevier Saunders.

    Hawton K, Kirk J. (1989)  Problem-solving. In: Hawton K, Salkovskis PM, Kirk J, Clark DM (eds.) Cognitive Therapy for Psychiatric Problems: A Practical Guide. Oxford: Oxford University Press, 406-426.

    Hek, G. (1996) Guidelines on conducting a critical research report.  Nursing Standard. 11, 6, p40-43.

    Miller, J. (2007) Using Research and Data: Critiquing a Research

    Article. Agency for Health Research and Quality.

    Mynors-Wallis, L., Gath, D., Day, A., & Baker, F., (2000) Randomised controlled trial of problem solving treatment, antidepressant medication, and combined treatment for major depression in primary care.  British Medical Journal. 320: 26-30.

    Osman, A., Kopper, B., & Barrios, F. (2004)  Reliability and Validity of the Beck Depression Inventory-II with Adolescents Psychiatric Inpatients.  Psychological Assessment.  16-2.

    Reynolds, W. & Kobak, k. (1995) Reliability and Validity of the Hamilton Depression Inventory: A Paper-and-Pen Version of the Hamilton Depression Rating Scale Clinical Interview.  Psychological Assessment. 7-4.

    Salkovskis, P. M., Atha, C. & Storer, D. (1990) Cognitive–behavioral problem solving in the treatment of patients who repeatedly attempt suicide: A controlled trial. British Journal of Psychiatry, 157, 871–876.

    Wilkinson, G., Allen, P., Marshall, E. et al. (1993) The role of the practice nurse in

             the management of depression in general practice: treatment adherence to

    antidepressant medication. Psychological Medicine, 23 229-37.

    Appendix A

    The following tool has been adapted from “Using Research and Data: Critiquing a Research

    Article” produced by the Agency for Health Research and Quality (AHRQ).


    Typically, you will have four questions to ask about a given piece of research. They should be

    approached in the following order, and you may not need to read the report from front to back,

    rather identify key issues/ components of the paper to critically evaluate to determine if further

    reading is warranted.  This tool will allow you to draw conclusions about the paper’s relevance,

    quality and applicability, in order to assist you with making evidence-informed decisions.  These

    four key questions are:

    1. Is it relevant to my question/topic?

    2. What are the conclusions?

    3. How confident should I be about the findings?

    4. How well do the findings carry over to settings I am interested in?

    Here is the strategy expanded:

    1. Is it relevant to my question/topic?

    a. Ask yourself, what are my questions? What do I need to know?

     Your question or issue should be clearly defined and refined.  Good clinical questions are

    characterized by the “PICO” (Patient or Population, Intervention, Comparison and

    Outcomes) or “SMART” (Specific, Measurable, Achievable/Attainable, Realistic, Time-

    Oriented) frameworks.

    b. Look at the abstract, introduction and discussion sections.

    (i) Are your issues discussed there?

    Does it address a related question? How does it relate to your question?

    (ii) Are there reasons to doubt the findings without reading the whole article?

    While the question of how confident you should be about the findings and how well

    the findings will carry over (generalize) to your settings will be examined in detail, you

    may draw a preliminary conclusion that the study is not reliable or generalizable at

    this point.

    c. Does the study address your issues as a side issue or indirectly?

    To answer this you may need to look further into other sections of the article (i.e. the

    results).  For example, you may read a paper on diabetes educational programs in urban

    settings.  This paper may be indirectly related to your issue/interests, even if you are not

    a Diabetes Educator.  The paper could apply to someone involved with Chronic Disease

    Management or a practitioner interested in diabetes education in a rural setting, and

    therefore should not be ignored.  It is helpful to look at the tables and/or figures in the

    paper for information on the variables discussed.

    2.  What are the conclusions?

    a. Look at the abstract and conclusions section.

    The conclusions section is more detailed and precise than the abstract.  Does it appear as

    though there is value to the paper’s overall findings?

    b. Look at tables and figures with the study results.

    Are the results reported in the conclusions consistent with what is reported in the tables?

    They aren’t always.

    c. How well are the results related to other research on the same topic?

    While you may need to look at the other literature, some of this work should have been

    done by the authors.

    (i) Is there a review of the literature or reference to prior studies?

    Based upon what you know, is the literature review complete? Is it accurate?

    (ii) In the conclusion, is there a discussion of how these results compare or

    contrast with prior work?

     Research is cumulative and often needs supporting documentation. You may need to

    look at other articles in the literature to determine if there are similar, supporting

    results elsewhere.

    3. How confident should I be about the findings?

    To answer this question, you will need to review the methods section.

    There are five principal elements of the methods that influence the quality of the findings:

    a. the completeness of the model that is analyzed

    b. the quality of the measures/methods

    c.  the quality of the data

    d. the ability to control for differences between groups being compared

    e. the appropriateness of the statistical analyses

    Here are the five elements expanded:

    a. How complete is the model that is analyzed?

    The model is the description of the outcome (dependent) variables (for example; patient

    injuries) and independent variables (for example: staffing ratios) believed to be

    associated with the outcome, and how the outcome and independent variables are

    mathematically related to one another. It is often, but not always, drawn from theory.

    (i). Are all the relevant factors included in the research?

     Does the model explain the facts as you currently understand them? If not, re-

    examine both critically.  Do the authors present a story that is clear and easy to

    follow?  Do the methods help to answer the questions the authors are asking?

     How complete is the theory? Are important factors left out of the theory? Are

    important theoretical factors left out of the analysis?  All variables and theories should

    be defined or explained clearly.

    (ii). How important are any variables that are left out?

     Does the study consider socioeconomic variables special historical events or


    Are omitted variables correlated with important study measures? Are there

    confounding variables that you can think of?  How would these affect the results?

    b. How ‘good’ are the measures?

    (i). Do the measures accurately reflect what the researcher is trying to


    Measures can be too broad, too narrow or ambiguous (in that they can be interpreted

    as measuring different things). How clear and appropriate are the measures used in

    this study?  Are there any unnecessary variables? Sometimes authors will present a

    large number of variables as an attempt to look for statistical significance in their data

    (often called “data snooping”).

    i. Are the measures well established in prior research or through testing

    by the researcher?  Or are they ad hoc (ie. after the fact)?

    Tools used in the study should be valid and reliable.

    ii. Are the measures relevant to the time, place and circumstances of the

    population or organizations being studied?

    Profit margins, for example, may not be an appropriate measure of the financial

    health of public hospitals or nursing homes.

    c. How ‘good’ are the data?

    How was the data collected?  Are there alternate methods to collect data? Measures are

    only as good as the data used to construct them.

    d. Does the study adequately control for differences between the groups being


     Many studies involve comparison — control versus treatment, insured versus uninsured,

    this province versus national, etc. The study should minimize all other differences

    between the groups being compared other than the factors being studied. This is what

    randomization does in clinical trials. If this is not possible, the study should adequately

    control for differences.

    A special concern is selection — that people who choose to be in one group are often

    different in ways that cannot be measured. An example of a selection problem might be:

    families with children with illness are more likely to enrol in private insurance, while

    healthier families are more likely to remain uninsured. Differences between the uninsured

    and insured on number of doctor visits would overstate the true difference that would be

    observed in visits between patients who were equally ill. There are a wide range of

    methods to control for selection — some practical involving samples (e.g., compare those

    enrolled to those who have been put on waiting lists), some involving statistical

    adjustments to the data (e.g., instrumental variables models, selection models,

    propensity scores to select sub-samples for analysis).

    (i) How similar (or different) are the groups being compared?

    If the groups are different, how would you expect the differences to influence the

    outcome being studied? How have the researchers tried to control for these


    (ii) Is there a risk of selection bias?

    How have the researchers addressed this?

    e. Are the statistical methods used in this study appropriate?

    You may not be a statistician or methodologist, but the following questions can help sort

    out this issue:

    (i) Is the sample large enough to produce significant results?

    Relevant differences may not be “statistically significant” in a small sample, however

    insignificant findings are not necessarily negative.  Statistical significance must be

    weighed against clinical relevance in some cases.

    (ii) Are there things about the data that might require special consideration in

    the analysis?

    Infrequent events, lots of zeros/missing cases and measures that are constrained to

    be between two numbers (like scales that don’t give you an in-between value to

    choose), may require special methods. Is there evidence that these methods have

    been used?

    (iii) Is there a discussion of how the methods relate to those used in other


    Keep in mind that all studies have weaknesses and flaws.  You are trying to judge

    whether the weaknesses are so substantial that you doubt the results. Does it

    give you evidence to make decisions?  Does the paper say something meaningful?

    4. How well do the findings carry over to the setting(s) I am interested in?

    a. Focus on the time, place and circumstances of the population studied.

    b. The key things to look at, which may be described in the abstract or the methods section,

    are when, where and from whom the data were collected.

    (i) How similar (or different) are these from your circumstances?

    (ii) How old is the study? Has anything changed since it was completed?

    (iii) Is there a “Limitations” section?  Do you ‘buy’ the authors’ arguments?


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