Evaluating the Impact of Medication and Physiotherapy on Orthopedic Pain Management

Coursework

The Psychopharmacological Research Unit (PRU) at McGregor University conducted a study on the effectiveness of treatments for orthopedic issues such as sciatica, piriformis syndrome, and other musculoskeletal conditions. Specifically, the study examined the impact of three commonly prescribed medications Gabica (Pregabalin), Gabapentin, and Tizanidine in combination with different physiotherapy regimens. The study aimed to assess how these treatments influence pain reduction, quality of life, and sedation, providing insights into optimizing rehabilitation strategies for patients with chronic musculoskeletal pain.

The study included patients currently receiving treatment at McGregor University Hospital. Initially, participants were randomly assigned to one of two medication groups: Gabica*Tizanidine and Gabapentin*Tizanidine. Within each medication group, participants were further divided into three physiotherapy conditions: no physiotherapy, physiotherapy 1-2 times per week, or physiotherapy 3-4 times per week.

Patients were assessed after a period of 1 month, and individual scores for pain, quality of life, and sedation were recorded using a 1-10 scale, where 1 indicates low and 10 indicates high.

Part A: Descriptive Analysis 

1. Descriptive Statistics

Obtain the sample size, mean, and standard deviation for pain, quality of life, and sedation for each drug and physiotherapy combination. Report the results in narrative form, highlighting which combination performed best for pain reduction, improved quality of life, and minimal sedation.

1. Identification of Ideal Treatment Combination

Based on the descriptive results, determine the most effective drug and physiotherapy combination for orthopedic problems such as sciatica and piriformis syndrome. Provide a clear justification based on observed trends in the data.

Part B: Inferential Statistics 

1. 2-Way MANOVA

• Hypothesis:

  • Null hypothesis (H₀): Drug type, physiotherapy frequency, and their interaction have no significant effect on pain reduction, quality of life, or sedation.

  • Alternative hypothesis (H₁): Drug type, physiotherapy frequency, or their interaction has a significant effect on pain reduction, quality of life, or sedation.

• Interpretation of Findings:
  Present the results of multivariate tests, including significance of main effects and interaction effects. Explain which combination of drug and physiotherapy showed the strongest multivariate effect on the dependent variables.

• Assumptions Testing:
  Check for multivariate normality, homogeneity of covariance matrices, and absence of multicollinearity. Discuss whether assumptions were met.

1. Two-Way ANOVA or Equivalent Non-Parametric Test

• Choice of Dependent Variable: Select one dependent variable, such as pain reduction, for detailed analysis.

• Hypothesis:

  • Null hypothesis (H₀): There is no significant main effect or interaction effect of drug type and physiotherapy frequency on the selected dependent variable.

  • Alternative hypothesis (H₁): There is a significant main effect or interaction effect of drug type and physiotherapy frequency on the selected dependent variable.

• Analysis:
  Present overall model results, main effects, interaction effect, and effect sizes. Justify your choice of test with reference to assumption checks, including normality, homogeneity of variance, and independence.

• Post-Hoc Analysis:
  Conduct post-hoc testing for drug × physiotherapy combinations, report significant differences, and include effect size calculations. Interpret the findings in the context of optimizing treatment strategies.

Assessment Requirements

The assessment focuses on analyzing the effectiveness of orthopedic treatments for conditions such as sciatica and piriformis syndrome, using a combination of medications and physiotherapy. The key requirements include:

1. Descriptive Analysis

   • Calculate sample size, mean, and standard deviation for pain, quality of life, and sedation across each drug × physiotherapy combination.

   • Identify the most effective treatment combination for pain reduction, improved quality of life, and minimal sedation.

2. Inferential Statistics

   • Conduct 2-way MANOVA to examine main effects (drug, physiotherapy) and interaction effects on all dependent variables.

   • Test assumptions: multivariate normality, homogeneity of covariance matrices, absence of multicollinearity.

   • Perform two-way ANOVA (or equivalent non-parametric test) for a selected dependent variable (e.g., pain).

   • Conduct post-hoc analysis for significant drug × physiotherapy differences and report effect sizes.

3. Interpretation and Recommendations

   • Interpret multivariate and univariate results.

   • Recommend the ideal treatment strategy based on statistical outcomes.

   • Demonstrate understanding of research design, statistical methods, and clinical implications.

Guidance and Academic Mentor Approach

Step 1: Descriptive Analysis

• Mentor Guidance:

  • Organize the data by drug and physiotherapy combination.

  • Calculate mean and standard deviation for pain, quality of life, and sedation.

  • Highlight trends, e.g., “Gabica + physiotherapy 3–4 times/week showed the lowest pain scores and highest quality of life with moderate sedation.”

• Learning Objective: Understand data summarization and identify patterns before inferential testing.

Step 2: Identification of Ideal Treatment

• Mentor Guidance:

  • Compare descriptive results across all combinations.

  • Select the most effective combination considering multiple outcomes (pain, quality of life, sedation).

  • Justify choice using clear reference to descriptive statistics.

• Learning Objective: Develop critical reasoning and clinical interpretation skills.

Step 3: Inferential Statistics – 2-Way MANOVA

• Mentor Guidance:

  • Define hypotheses: H₀ (no effect), H₁ (effect exists).

  • Check assumptions:

    • Multivariate normality

    • Homogeneity of covariance matrices

    • Absence of multicollinearity

  • Run MANOVA to test the effect of drug, physiotherapy, and their interaction on all three dependent variables.

  • Interpret Wilks’ Lambda, Pillai’s Trace, and p-values to determine significance.

• Learning Objective: Apply multivariate analysis to understand complex relationships among multiple dependent variables.

Step 4: Two-Way ANOVA / Non-Parametric Test

• Mentor Guidance:

  • Choose one dependent variable (e.g., pain).

  • Check ANOVA assumptions: normality, homogeneity of variance, independence.

  • Conduct two-way ANOVA to examine main and interaction effects.

  • If assumptions are violated, use non-parametric alternatives (e.g., aligned rank transform).

  • Report effect sizes and significance.

• Learning Objective: Learn univariate inferential testing and effect size interpretation.

Step 5: Post-Hoc Analysis

• Mentor Guidance:

  • Perform post-hoc comparisons to identify which drug × physiotherapy combinations differ significantly.

  • Report pairwise differences, p-values, and effect sizes.

  • Relate findings to practical treatment decisions.

• Learning Objective: Develop ability to refine findings and provide actionable recommendations.

Outcome and Learning Achieved

• Outcome:

  • Determined the optimal treatment combination for pain reduction, quality of life improvement, and minimal sedation.

  • Produced a statistical report including descriptive, multivariate, and univariate analyses.

  • Provided evidence-based recommendations for physiotherapy frequency and drug choice.

• Learning Objectives Covered:

  1. Conducting descriptive and inferential analyses.

  2. Testing assumptions of MANOVA and ANOVA.

  3. Interpreting multivariate and univariate results.

  4. Applying statistical reasoning to clinical decision-making.

  5. Understanding research design in pharmacology and rehabilitation.

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