46 gssr 10.31703/gssr Global Social Sciences Review gssr 2520-0348 2616-793X Humanity Publications Pakistan 390589 10.31703/gssr.2018(III-IV).16 1058 1.0 article Construction and Validation of Neurotransmitters Scale Ahmad Mumtaz Ahmad Conceptualization Writing – original draft Tahir Asma Writing – review & editing Sohail Nadeem Sohail Writing – review & editing Department of Commerce, The Islamia University of Bahawalpur Assistant Professor Punjab Pakistan Department of Statistics, Forman Christian College University, Lahore Assistant Professor Punjab Pakistan Director, Government College University, Faisalabad Punjab Pakistan Corresponding Author: Mumtaz Ahmad, Assistant Professor, Department of Commerce, The Islamia University of Bahawalpur, Punjab, Pakistan.. Contact: 0

The authors declare that they have no conflicts of interest.

This study did not require formal ethics approval.

Data sharing is not applicable to this article.

 31 12 2018 12 2018 16 02 2022 3 4 Fall 228 253 16 02 2022

The authors received no specific funding for this work.

 2018 Humanity Publications This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License. Appendix:

Appendix:Neurotransmitters (Dopamine, Serotonin, Epinephrine and Norepinephrine) Questionnaire

 Full Text PDF

In this research, we visit literature directed seven steps procedure of scale development and incorporate it in studying dopamine, serotonin, epinephrine and norepinephrine and thus finalized 16 items neurotransmitters scale. We incorporated 6 samples for construction of reliable multi-aspect questionnaire that imitated across the samples. We confirm the content adequacy qualitatively and quantitatively including discriminant and convergent validity. We also established the criterion-related validity through the instrument’s relation with measures of behavioral aspects of individual investors. This research proposes that the neurotransmitters scale is valid and reliable. Neurotransmitters as dopamine, serotonin, epinephrine and norepinephrine have significant use for individual stock markets investors. This investigators hope that the corroborated scale is reliable as well as valid and will be appropriate to utilize in upcoming studies of neurofinance.

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Hu and Bentler (1999) recommended in support of model fit as RMR values close to .09, RMSEA values close to .06 or below, CFI and TLI values close to .95 or greater and along with GFI ≥ 0.90. The cuttoff values for χ2/df (CMIN/DF) is recommended 1 as lower limit and 2 to 3 or 5 as upper limit, AGFI ≥ 0.80, IFI ≥ 0.90, NFI ≥ 0.90, PGFI and PNFI values 0 to 1. (Gulla & Purohit, 2013). Commonly a CMIN/DF statistic lower than 5 is believed satisfactory, as lesser values consider better (Thomson et al., 2005).

Additionally, five models observed the loading as of 18 items on appropriate 4 factors in model-1, as 4 items loaded on dopamine, 4 items loaded on serotonin, 6 items loaded on Norepiphrine 4 items loaded on Epiphrine and detail can be seen in table-2. Furthermore model-2 to 5 showed the loading of 16 items on appropriate 4 factors as 4 items loaded on dopamine, 4 items loaded on serotonin, 4 items loaded on Norepiphrine 4 items loaded on Epiphrine and detail can also be seen in table-2

Table 2: 18 Items Loaded on 4 Constructs (Model-1) and 16 Items Loaded on 4 Constructs (Model: 2 to 5) Table 1

Factors

Items

Loading

1

Items

Loading

2

Loading

3

Loading

4

Loading

5

Serotonin

S5

0.618

S7

0.702

0.851

0.85

0.445

S6

0.606

S8

0.662

0.796

0.797

0.555

S10

0.666

S10

0.654

0.526

0.527

0.797

S14

0.551

S11

0.521

0.408

0.408

0.834

Dopamine

D20

0.569

D20

0.574

0.574

0.574

0.574

D19

0.667

D18

0.834

0.831

0.831

0.831

D17

0.555

D16

0.558

0.559

0.56

0.56

D15

0.578

D15

0.654

0.658

0.658

0.658

Epinephrine

E8

0.801

E8

0.707

0.629

0.629

0.629

E7

0.773

E6

0.769

0.799

0.798

0.798

E6

0.693

E4

0.885

0.839

0.84

0.84

E5

0.746

E1

0.57

0.604

0.604

0.604

Norepibephrine

N8

0.794

N6

0.772

0.797

0.813

0.705

N9

0.881

N7

0.726

0.847

0.814

0.836

N10

0.817

N8

0.847

0.819

0.836

0.814

N11

0.806

N12

0.743

0.75

0.705

0.813

N12

0.805

N14

0.764

Till now all these five models fulfill the criteria of goodness of fit and show appropriate loading of items on appropriate expected factors but which one model is best suitable will be decided later on after completion of further analysis.

Phase 5: Internal Consistency Assessment

Internal consistency is a gauge of reliability and indicates the intensity of items in the construct about the different facet of the similar trait (Revicki, 2014). Internal consistency assesses the steadiness contained by the scale as well as items how fine a depository of statements quantifies a specific attribute (Drost, 2011). Reliability is said to be the degree where a construct cedes the equal value all time when it is governed, all else unchanged (Hays and Revicki, 2005). Most common satisfactory gauge in survey investigation for evaluating internal consistency of scale is Cronbach's alpha with the help of which it is notify that how good the statements assess the similar measure (Price& Mueller, 986).

Cronbach alpha is the coefficient 0 to 1 commonly used to estimate the reliability of instruments based on internal consistency. As Hinkin (1997) said, internal consistency should be assessed after EFA and CFA. After exploratory and confirmatory factor analysis, it was determined internal consistency with help of Cronbach's alpha twice: first, scale with 18 items having Cronbach alpha 0.833 for 4 constructs as values of alpha 0.7, 0.73, 0.92 and 0.88 respectively for dopamine with 4 items, serotonin with 4 items, Norepinephrine with 6 items and Epinephrine with 4 items. Second, scale with 16 items having Cronbach's alpha 0.796 for 4 constructs as values of Cronbach's alpha 0.75, 0.76, 0.87 and 0.80 respectively for dopamine with 4 items, serotonin with 4 items, Norepinephrine with 4 items and Epinephrine with 4 items.

Obviously, the value of coefficient alpha is one of the very significant as well as persistent statistics in investigation concerning scale development (Cronbach's, 1951). According to the Cortina (1993), an instrument having more than 14 statements or items with alpha value 0.7 is satisfactory for freshly constructed scale. Next step is to confirm the validation of scale.

Phase 6: Construct Validation

In the previous phases, content validity and internal consistency of the newly constructed instrument has been confirmed, these two shows the proof of validity of construct. Moreover proof of validity of construct can be provided with the help of convergent, discriminant and criterion-relatedvalidity.

Convergent Validity: Confirmatory factor analysis applied to evaluate validity of construct (Joreskog, 1969). But according to Campbell and Fiske (1959), construct validity assessment has two sides, one is said to be the convergent validity as self-assurance level about the feature which tell us how good construct is assessed by the mentioned observed variables and second, discriminant validity as the extent to which variables of diverse characteristics are dissimilar. Fornell and Larcker (1981) standard usually applied to evaluate the extent of communal variance among the underlying constructs.

In accordance with standard, the convergent validity evaluate with the help of Average Variance Extracted (AVE) and Composite Reliability (CR), whereas the value of AVE 0.5 and value of CR 0.7 are acceptable. But according to Hair et al., (2006) Composite Reliability (CR) value between 0.6 and 0.7 is acceptable. Similarly, Kotcharin et al. (2012); Gulla and Purohit (2013) suggested that AVE value 0.48 is also acceptable.

On the base of methodological recommendation of literature related to convergent validity for five appropriate models of CFA, author calculated the values of average variance extracted (AVE), composite reliability (CR) for dopamine, serotonin, epinephrine and Norepinephrine. The values of AVE and CR of five different models can be seen in table-3

 Table 3. Convergent Validity of Constructs Table 2

(A)

Model-1

Measures

Items

AVE

CR

Dopamine

4

0.4

0.6

Serotonin

4

0.4

0.6

Epinephrine

4

0.6

0.6

Norepinephrine

4

0.7

0.9

 Table 3

(B)

Model-2

Measures

Items

AVE

CR

Dopamine

4

0.4

0.6

Serotonin

4

0.4

0.6

Epinephrine

4

0.5

0.7

Norepinephrine

4

0.6

0.8

 Table 4

(C)

Model-3

Measures

Items

AVE

CR

Dopamine

4

0.5

0.6

Serotonin

4

0.5

0.6

Epinephrine

4

0.5

0.7

Norepinephrine

4

0.6

0.8

 Table 5

(D)

Model-4

Measures

Items

AVE

CR

Dopamine

4

0.4

0.6

Serotonin

4

0.5

0.6

Epinephrine

4

0.5

0.7

Norepinephrine

4

0.6

0.8

 Table 6

(E)

Model-5

Measures

Items

AVE

CR

Dopamine

4

0.5

0.6

Serotonin

4

0.5

0.7

Epinephrine

4

0.6

0.8

Norepinephrine

4

0.5

0.7

Table-3 results indicate that model three and five show better and acceptable values of average variance extracted and composite reliability which indicates that observed variables converge to the latent variables appropriately.

Discriminant Validity: Evaluation of discriminant validity becomes precondition for exploring associations among hidden constructs (Henseler et al.2015). According to Fornell and Larcker (1981), discriminant validity assessment can be achieved by comparing the AVE of latent variable and maximum share variance or squared correlation of constructs. As said by this standard, for each construct the values of AVE must be greater than maximum share variance or squared correlation of other constructs.

For this we use the above mentioned five models from confirmatory factor analysis and determined the square of correlation or maximum shared variance (MSV) of latent variables in each model. For assessment of discriminant validity, we compared the values of square of correlation and AVE. Then it is checked that values of AVE are greater than the values of square of correlation of each construct which indicates that dopamine, serotonin, Epinephrine and Norepinephrine discriminate with each other appropriately.

The values of square of correlation of dopamine, serotonin, Epinephrine and Norepinephrine in five different models can be seen in table-4. From the results of table-4 can be seen that values of AVE are greater than the values of MSV for dopamine, serotonin, Epinephrine and Norepinephrine in all five different models.

Table 4. Discriminant Validity of Constructs Table 7

Correlation^2 or Maximum Share Variance (MSV)

Model-1

Model-2

Model-3

Model-4

Model-5

Dopamine

<-->

Serotonin

0.001296

0.003364

0.001024

0.001024

0.001369

Dopamine

<-->

Epinephrine

0.002401

0.000009

0.000400

0.000400

0.001600

Dopamine

<-->

Nor-epinephrine

0.006084

0.001156

0.000900

0.001600

0.000400

Serotonin

<-->

Epinephrine

0.355216

0.272484

0.207936

0.207936

0.229441

Serotonin

<-->

Nor-epinephrine

0.253009

0.251001

0.226576

0.231361

0.212521

Epinephrine

<-->

Nor-epinephrine

0.180625

0.193600

0.212521

0.207025

0.207025

Till now, the results mentioned in the above tables, indicates that values of average variance extracted, composite reliability and maximum share variance are appropriate and acceptable for convergent and discriminant validity.

Criterion-Related Validity: For the assessment of criterion-related validity, investigator must observe the associations among the fresh construct as well as theorized measure to build up the idea of attention in the research (Cronbach & Meehl, 1955). According to Hinkin (1998), associations among the new measure as well as theorized variables must be supported with the help of theory as well as by observing the correlation analysis and this association must be statistically significant for the confirmation of criterion-related validity. For this, author accumulated the data of five related resulting measures of dopamine, serotonin, epinephrine and Norepinephrine.

As per opinion of Pompian (2006) some behavioral aspects of investors are results of neurotransmitters as dopamine, serotonin and epinephrine. These five resulting variables as investment horizon, risk attitude, Personalization of Loss, confidence and control are evaluated by using the 21 items scale on 5 pint Likert scale (Wood & Zaichkowsky, 2004). The result of correlation analysis between neurotransmitters and behavioral outcome of investor reveals that some of variables are significant at the 0.01 level and some are significant at 0.05 levels. The final phase in development of questionnaire procedure is replication. The concluding items of questionnaire can seen in the Appendix

Phase 7: Replication

In replication phase, it is possibly squabbled that, due to the false variance caused by the measurement technique (Podsakoff, MacKenzie, & Podsakoff, 2003) and prospective complexities due to the common variance method, it is unsuitable to employ the identical set of data for scale construction as well as for the assessment of psychometric features of a newly developed construct (Campbell, 1976). The use of independent data set will generalize the newly constructed variable (Stone, 1978). For this, Anderson & Gerbing (1991) suggested the administration of one more self-sufficient set of data.

For these reasons, researcher collected another independent set of data of 199 sample size from the individuals who have suitable knowledge of content domain. Newly administered scale have 16 items of neurotransmitters as dopamine, serotonin, Epinephrine and Norepinephrine, survived in previous phases of scale development process. Then performed the confirmatory factor analysis, assessment of internal consistency reliability, and convergent, discriminant, and criterion- related validity for evaluation of psychometric features of scale.

Confirmatory factor analysis of previously survived 16 items of dopamine, serotonin, epinephrine and Norepinephrine shows the appropriate loading as seen in table-1, RMR values is .09, RMSEA values is .04, CFI, TLI, IFI, NFI, PNFI and PIFI values are 0.98, 0.97, 0.98, 0.91, 0.72 and 0.77 along with GFI, AGFI and PGFI value 0.93, 0.90 and 0.65. The value for χ2/df (CMIN/DF) is 1.30. These results of CFA indicates that model is fit as per the standard describes in literature.

16 Items Loaded on 4 Constructs, Internal Consistency Reliability and Convergent Validity

Factors

Items

Loading

Cronbach's alpha

AVE

CR

Serotonin

S7

0.51

0.823

0.515

0.709

S8

0.64

S10

0.78

S11

0.88

Dopamine

D20

0.58

0.814

0.511

0.703

D18

0.58

D16

0.83

D15

0.82

Epiphrine

E8

.80

0.737

0.50

0.66

E6

0.77

E4

0.72

E1

0.40

Norepiphrine

N6

0.71

0.784

0.51

0.708

N7

0.84

N8

0.63

N12

0.66

Table 5 indicates that values are acceptable.

Table 6. Discriminant Validity of Constructs Criterion-Related Validity

MSV

Dopamine<-->Serotonin0.082
Dopamine<-->Norepinephrine0.082
Dopamine<-->Epinephrine0.074
Serotonin<-->Norepinephrine0.042
Serotonin<-->Epinephrine0.053
Norepinephrine<-->Epinephrine0.046

Correlation coefficient indicates that an association among the new measure as well as theorized variables is supported and this association is statistically significant for the confirmation of criterion-related validity.

Table 10

Correlations

IH

RA

PL

Confi

Control

D

S

N

E

IH

1

RA

.354**

1

PL

.298**

.518**

1

Confi

.542**

.600**

.449**

1

Control

.382**

.622**

.724**

.480**

1

D

.208**

.210**

.071

.172*

.180*

1

S

.647**

.462**

.385**

.645**

.455**

.169*

1

N

.499**

.690**

.495**

.611**

.631**

.188**

.511**

1

E

.446**

.458**

.392**

.525**

.466**

.199**

.554**

.550**

1

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

IH = Investment Horizon

RA = Risk Attitude

PL = Personalization of Loss

Confi = Confidence

Control = Control

D = Dopamine

S = Serotonin

E = Epinephrine

N = Norepinephrine

Conclusion

Superior investigation initiates with superior scale. Due to this; we have visited the literature directed seven steps procedure for construction of scale of neurotransmitters and finalized that dopamine, serotonin, epinephrine and norepinephrine with 16 items. This study was with anticipation that neurofinance investigators will use this logical advancement to measure the level of dopamine, serotonin, epinephrine and norepinephrine of stock market investor. Above mentioned process of questionnaire development found that constructs which come out will be glowing psychometrically (Mackenzie et al., 1991). This investigation will give the hope that the corroborated scale is reliable as well as valid and will be appropriate to utilize in upcoming studies of neurofinance.

Dopamine

I have episodes of low blood sugar with light-headedness, irritability, extreme hunger, and cloudy thinking.

I get excessive amounts of sleep and still awaken tired.

I am easily angered, irritated, or frustrated.

I need medication to cope with or forget my problems.

 Serotonin

I eat when I am not hungry.

I eat massive quantities of food at one time.

I eat unconsciously and wonder why after that.

I eat such large quantities of food that I get nauseated.

 Epinephrine

I feel difficulties or problems with stress, mental clarity, maintaining my focus, organizing my thoughts, making decisions, and feeling out of control.

I find it difficult to concentrate on my job or projects.

I feel eye fatigue that affects my job, work or reading enjoyment.

I feel difficulty while starting work/job/projects.

 Norepinephrine

I feel out of control, especially with my hunger.

I think about food most of the time.

I have strong desire of breads or pastas rather than sweets or junk food.

I feel down, depressed, or unexciting.

 Conflict of Interest

The authors declare that they have no conflicts of interest.

 Ethics Statement

This study did not require formal ethics approval.

 Data Availability

Data sharing is not applicable to this article.

 Supplementary Materials Appendix:

Appendix:Neurotransmitters (Dopamine, Serotonin, Epinephrine and Norepinephrine) Questionnaire

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