Assignment:Mild Cognitive Impairment Research Analysis Matrix 

Assignment:Mild Cognitive Impairment Research Analysis Matrix

Assignment:Mild Cognitive Impairment Research Analysis Matrix

Mild Cognitive Impairment Research Analysis Matrix 

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Topic of Interest: Testing for cognitive-memory deficits

Mild cognitive dysfunction Identification using Vocal Recognition

Research Article: Include full citation in APA format, as well as link or search details (such as DOI) Mayumi Horie, Toshihide Harada, Tadayuki Iida, Satomi Aoi, & Hiromi Ikeda. (2022). Evaluation of Vocal Recognition for Early Detection of Mild Cognitive Impairment. International Medical Journal, 29(6), 362–365

 

 

Professional Practice Use: 

One or more professional practice uses the theories/concepts presented in the article

Speech has the potential to provide insights into the motoric and cognitive capabilities of individuals diagnosed with Mild Cognitive Impairment (MCI), specifically about their articulation, voice quality, and fluency. The cognitive Montreal scale shares similarities with other scales such as the GAD, PHQ9, Yale-Brown, and OCD scales (Zhao et al., 2022).
Research Analysis Matrix 

Add more rows if necessary

Strengths of the Research Limitations of the Research Relevancy to Topic of Interest Notes
 

·         Clinical research design

·         Objectives are well stated.

·         Outcome measures are specified.

·         The features of the patient are well-defined.

·         The intervention was precisely detailed.

·         The results were well reported.

·         Therapy settings and interventions are reflective of population treatment.

·         Compliance with the intervention is not seen as a possible concern given the nature of the intervention.

·         Describes the length of each enrolled patient’s follow-up.

·         The number of patients at each analysis visit is provided.

·         Multi-center research (10 centers)

·         In comparison to previous research in the area, the sample size is rather substantial.

·         The number of patients at each analysis visit is given.

·         Describes the number of patients who were not followed up on (Mayumi Horie et al., 2022).

·         fewer people with moderate cognitive impairment were tested (Mayumi Horie et al., 2022)

·         It was as challenging to form a definite hypothesis.

·         lacks a declaration of a testable hypothesis that is clearly defined.

·         no control group exists.

·         Inadequate blinding, results, and intervention.

·         not mention if any patients were missed for follow-up. does not include the characteristics of patients who were not followed up on.

·         Lost to follow-up is not taken into consideration in statistical analysis.

·         There is no random population sample used in the process of finding and choosing patients.

·         did not mention if the research had a protocol or whether it had been prepared in advance.

·         does not have a statistical analysis of the results.

·         The selection and identification process for patients is not disclosed.

·         The selection and identification process for patients is not disclosed.

·         small sample size.

·         The adult SMA population is not randomly chosen as part of the sampling technique (Mayumi Horie et al., 2022).

·         did not mention if a protocol was created beforehand or already existed.

·         does not include the characteristics of patients who were not followed up on.

·         Lost to follow-up is not taken into consideration in statistical analysis.

·         A random sample of the population is not used to identify and choose patients, and P-values are not usually reported.

·         No inclusion or exclusion criteria were given.

·         Intervention (usual care) details are not mentioned.

·         Undescribed sample size calculations

·         Number of abandoned or unfollowed cases was not recorded.

·         Limited generalizability; unsure whether research participants were typical of all patients.

·         Retrospective research employing family medical practice data that was not randomly selected (Mayumi Horie et al., 2022).

 

 

 

 

 

Relevant to the identification of mild cognitive impairment by vocal testing (Mayumi Horie et al., 2022).  Through vocal testing, early identification of moderate cognitive impairment (a precursor to dementia) may be made (Mayumi Horie et al., 2022).
·         Objective stated

 

“Objective: As there are few means to stop the progression of dementia after its onset, it is important to delay or prevent the transition from mild cognitive impairment (MCI) to dementia.

Results: A one-second delay in the time to recognize emotions through voices was associated with an approximately 34-fold

increase in the risk of MCI.

·         Conclusion: Using vocal recognition assessment was considered to be effective for early screening of MCI.”

·         Outcome measures.

In this study, we examined whether vocal recognition

evaluation, which uses the time from speech presentation to judging the emotion of speech an evaluation, could be

effective for MCI screening (Mayumi Horie et al., 2022).

 

·         Material methods clearly stated

 

·         Sample size

 

·         randomization

 

·         P values

No control group    
 

Inclusion and Exclusion criteria identified

 

 

 

did not provide a list of the studies that were included and eliminated (Mayumi Horie et al., 2022).

 

In the references section, a bibliography of chosen research was produced (Mayumi Horie et al., 2022). There is no list of included and omitted studies (Mayumi Horie et al., 2022).
 

Objectives were clearly stated. As the vocal recognition assessment screening test and MoCA-J are both screening tests for mild cognitive impairment, therefore evaluate MCI early (Mayumi Horie et al., 2022).

fewer people with moderate cognitive impairment were tested Memory impairment  
Outcome measures.

The purpose of this study was to determine if vocal recognition assessment, which assesses speech emotion after it has been presented, may be useful for MCI screening (Mayumi Horie et al., 2022).

 

 Objective: It is crucial to postpone or halt the shift from moderate cognitive impairment (MCI) to dementia since there are few ways to block dementia’s development once it has begun.

 

Results: A 34-fold increase in the risk of MCI was shown to be connected with a one-second delay in the ability to detect emotions in speech.

Conclusion: The use of voice recognition testing was proven to be beneficial for the early detection of MCI (Mayumi Horie et al., 2022).

 In this study, the researchers spoke about how 21% of middle-aged and elderly healthy volunteer women were found to have probable MCI. Therefore, it is required to look at several clinical instances in which practitioners have established a firm diagnosis of MCI / healthy people to understand the link between MCI and the outcomes of the voice recognition exam (Mayumi Horie et al., 2022).    
Design: Clinical research

The control group was not present.

There was no double-blinding or randomization.

There are no follow-up studies.

·         Female patient characteristics, including ages and outcomes, were given (Mayumi Horie et al., 2022).

·         The intervention was well described

·         In conclusion, findings and materials approaches are defined.

Hypothesis: It is uncertain if there is a link between perceiving another person’s emotions in a speech via auditory cues such as speech prosody and MCI (Mayumi Horie et al., 2022).

There was no control group or randomization.

 Preventive dementia therapies are still unavailable since early MCI diagnosis techniques have not yet been developed (Mayumi Horie et al., 2022).    
·         The criteria for inclusion and exclusion were indicated.  MCI early detection techniques are still being developed;    
·          Analysis specified: To compare the MCI and nonMCI suspect groups, the Mann—-Whitney U-test was used (Mayumi Horie et al., 2022). As a result, dementia prevention strategies are still lacking (Mayumi Horie et al., 2022).    
 Materials and Methods: From the public relations department of a city in Japan, 77 volunteers who were female and middle-aged or older were selected. The Montreal Cognitive Assessment-J (MoCA-J), which is available in Japanese, was used to check for MCI. The MoCA-J scores and neurologist consultation were used to separate the participants into two groups: MCI suspects were those who scored a MoCA-J of 25 or less, and non-MCI suspects were those who had a score of 26 or more. Vocal identification tests included the use of voice samples that represented four distinct emotions: acceptance, rejection, bluffing, and joking.

Vocal identification tests included the use of voice samples that represented four distinct emotions: acceptance, rejection, bluffing, and joking (Mayumi Horie et al., 2022).

Results: A 34-fold increase in the risk of MCI was shown to be connected with a one-second delay in the ability to detect emotions in speech (Mayumi Horie et al., 2022).

Conclusion: Vocal recognition testing was thought to be useful for MCI early detection (Mayumi Horie et al., 2022).

   
Those who were excluded were characterized as unethical.

Inclusion specified ladies from Japan aged 40 and informed permission for all

 

Clinical research without randomization

P values and hypotheses were presented.

The characteristics of the patients, therapies, and results were all reported.

 

Methods and studies

To screen for MCI, the Japanese version of the Montreal Cognitive Assessment (MoCA-J) was employed. By neurologist consultation and Montreal Cognitive Assessment-Japanese scores, participants were separated into two groups (Mayumi Horie et al., 2022).

Weakness:

The institution where this research was conducted was in Japan; clearly, our healthcare system is not comparable to that of this nation, therefore that is something to consider (Liang et al., 2022).

   

 References

Liang, X., Batsis, J. A., Zhu, Y., Driesse, T. M., Roth, R. M., Kotz, D., & MacWhinney, B. (2022). Evaluating voice-assistant commands for dementia detection. Computer Speech & Language72, 101297. https://doi.org/10.1016/j.csl.2021.101297

‌Mayumi Horie, Toshihide Harada, Tadayuki Iida, Satomi Aoi, & Hiromi Ikeda. (2022). Evaluation of Vocal Recognition for Early Detection of Mild Cognitive Impairment. International Medical Journal, 29(6), 362–365

Zhao, X., Hu, R., Wen, H., Xu, G., Pang, T., He, X., Zhang, Y., Zhang, J., Chen, C., Wu, X., & Xu, X. (2022). A voice recognition-based digital cognitive screener for dementia detection in the community: Development and validation study. Frontiers in Psychiatry13. https://doi.org/10.3389/fpsyt.2022.899729

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Week 3-step 1 Charts

Can you completely finish the chart all boxes!

The filled ones are from other two resources. It should be paraphrased or cited with quotes etc.

https://www.ncbi.nlm.nih.gov/books/NBK566621/table/rd0056.app3.tab1/

I do need three citations.

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