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The Use Of Mobile Healthcare Applications To Aid Medication Adherence Add in library

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Question:

Describe about the Use of Mobile Healthcare Applications to Aid Medication Adherence?
 
 

Answer:

Data analysis

Descriptive

Descriptive Statistics

 

N

Minimum

Maximum

Mean

Std. Deviation

sex

114

1.00

2.00

1.6053

.49095

age

114

1.00

5.00

1.9649

.93060

experience

114

1.00

6.00

3.3070

1.59161

smartphone

114

1.00

2.00

1.0351

.18481

platform

110

1.00

2.00

1.1364

.34474

hours_per_day

110

1.00

5.00

2.8909

1.28752

Valid N (listwise)

110

 

 

 

 


In data analysis part the description of statistics are based on sex, age, experience, smart phone, platform, hours per day respectively. From the given data and statistics the number of responses found is 114. The minimum, maximum, mean and the standard deviation are calculated to analyze to signify the outcome of the given data (12).

The standard deviation of the the regulating parameters are calculated within 0 to 2 in each case.

To make the analysis more efficiently working a descriptive chart has been prepared. The chart shows the said parameters position in a detailed way (1). The X-axis of the chart showing the people of the survey and the Y- axis shows the minimum, maximum, mean and the standard deviation. 

Descriptive Statistics

 

N

Minimum

Maximum

Mean

Std. Deviation

game_based

92

1.00

5.00

3.8696

1.19723

healthcare_apps

87

1.00

5.00

4.0000

1.17136

search_tool

96

1.00

5.00

2.5521

.97192

social_networking

103

1.00

5.00

1.9515

1.34586

news_apps

105

1.00

5.00

2.2476

.96855

using

110

1.00

5.00

1.5818

.86078

monitoring_health

112

1.00

3.00

1.8750

.58702

manage_medication

114

1.00

5.00

2.8333

.67728

consulting_healthcare_professional

114

1.00

5.00

2.9649

.80847

different_medicines

113

2.00

5.00

3.4248

.79961

take_medication

114

1.00

4.00

2.5439

.71816

forget

98

1.00

3.00

1.3469

.64380

side_effects

86

1.00

4.00

2.1279

.76384

feel_well_enough

28

1.00

3.00

2.4643

.74447

lack_of_time

13

1.00

7.00

2.5385

1.45002

no_improvement

24

2.00

5.00

2.5417

.72106

lack_of_understanding

62

1.00

3.00

2.0484

.77729

dosage_form_inappropriate

27

2.00

6.00

3.0000

.67937

strategy_to_take

108

1.00

4.00

1.9167

.54900

helping_adherence

114

1.00

4.00

2.2895

.72532

adherence_to_medication

114

1.00

4.00

2.7807

.80660

recommending_external_device

114

1.00

4.00

2.6140

.65862

promoted_by_professional

113

1.00

4.00

2.3097

.87709

used_app_by_the_public

114

1.00

7.00

1.7807

1.46196

aid_medication_adherece

114

1.00

7.00

2.9035

1.49317

ease_of_use

113

1.00

3.00

1.4071

.63579

reliability_security

108

1.00

5.00

2.9259

1.03854

regulated_information

104

1.00

6.00

3.8077

1.24695


In this segment based on sex, age, experience, smart phone, platform, hours per day respectively the other components stated in the left of the statistical table is optimized for the analytic purpose (4). Each case shows the minimum, maximum, mean and the standard deviation. Also the number of responses has been in the table to show the interest. Few of the vital analysis is made depending on the given chart to conclude a certain decision.


The above mentioned graph shows 5 different parameters and the result out of the given data analysis. In smart phone the uses of game based software or application is showed by the blue line and its related standard deviation is presented according to that (18). The same way the position of health care apps, search tools, social networking apps and news apps are presented in the mentioned color respectively.

Descriptive Statistics

 

N

Minimum

Maximum

Mean

Std. Deviation

cost

103

1.00

6.00

2.4951

1.20354

fun

105

2.00

6.00

5.0381

1.00884

impact_on_battery_life

103

1.00

6.00

5.1845

1.09139

manage_medicine_via_app

114

1.00

4.00

2.6404

.99670

concern

114

1.00

5.00

2.9211

1.68357

regulated

114

1.00

5.00

1.5965

.84894

training

114

1.00

5.00

2.1930

.95822

Valid N (listwise)

1

 

 

 

 


Another descriptive statistics shows the cost, fun, impact on battery life, manage medicine via apps, concern, regulated, training of the health care apps (19). The number of responses, minimum, maximum, mean and the standard deviation are also statically calculated in this scenario as well.

Now here the analytic bar chart shows the number of responses for the cost, fun, impact on battery life, manage medicine via apps, concern, regulated, training of the health care apps. Also mean product is showed in the chart to confirm it statistically (10). The cost, concern and fun have managed to be at the top position in the chart.

Oneway Anova

Analysis of variance (ANOVA) is a specific procedure to analyze the particular differences between means of each group and the related associated variance.

ANOVA

 

Sum of Squares

df

Mean Square

F

monitoring_health

Between Groups

1.620

1

1.620

4.866

Within Groups

36.630

110

.333

 

Total

38.250

111

 

 

manage_medication

Between Groups

5.642

1

5.642

13.681

Within Groups

46.191

112

.412

 

Total

51.833

113

 

 

consulting_healthcare_professional

Between Groups

3.860

1

3.860

6.175

Within Groups

70.000

112

.625

 

Total

73.860

113

 

 

different_medicines

Between Groups

1.372

1

1.372

2.168

Within Groups

70.239

111

.633

 

Total

71.611

112

 

 

take_medication

Between Groups

3.790

1

3.790

7.789

Within Groups

54.491

112

.487

 

Total

58.281

113

 

 

side_effects

Between Groups

.033

1

.033

.057

Within Groups

49.560

84

.590

 

Total

49.593

85

 

 

feel_well_enough

Between Groups

.618

1

.618

1.120

Within Groups

14.346

26

.552

 

Total

14.964

27

 

 

lack_of_understanding

Between Groups

4.700

1

4.700

8.769

Within Groups

32.155

60

.536

 

Total

36.855

61

 

 

strategy_to_take

Between Groups

4.875

1

4.875

18.877

Within Groups

27.375

106

.258

 

Total

32.250

107

 

 

helping_adherence

Between Groups

2.093

1

2.093

4.087

Within Groups

57.355

112

.512

 

Total

59.447

113

 

 

adherence_to_medication

Between Groups

.327

1

.327

.500

Within Groups

73.191

112

.653

 

 

The above Analysis of variance (ANOVA) shows the sum of squares, df, mean square and the f of the given parameters mentioned in the table format.

ANOVA

 

Sig.

monitoring_health

Between Groups

.029

Within Groups

 

Total

 

manage_medication

Between Groups

.000

Within Groups

 

Total

 

consulting_healthcare_professional

Between Groups

.014

Within Groups

 

Total

 

different_medicines

Between Groups

.144

Within Groups

 

Total

 

take_medication

Between Groups

.006

Within Groups

 

Total

 

side_effects

Between Groups

.812

Within Groups

 

Total

 

feel_well_enough

Between Groups

.300

Within Groups

 

Total

 

lack_of_understanding

Between Groups

.004

Within Groups

 

Total

 

strategy_to_take

Between Groups

.000

Within Groups

 

Total

 

helping_adherence

Between Groups

.046

Within Groups

 

Total

 

adherence_to_medication

Between Groups

.481

Within Groups

 

 

ANOVA

 

Sum of Squares

df

Mean Square

F

adherence_to_medication

Total

73.518

113

 

 

recommending_external_device

Between Groups

.054

1

.054

.123

Within Groups

48.964

112

.437

 

Total

49.018

113

 

 

promoted_by_professional

Between Groups

.150

1

.150

.194

Within Groups

86.009

111

.775

 

Total

86.159

112

 

 

fun

Between Groups

.887

1

.887

.871

Within Groups

104.960

103

1.019

 

Total

105.848

104

 

 

impact_on_battery_life

Between Groups

.414

1

.414

.346

Within Groups

121.081

101

1.199

 

Total

121.495

102

 

 

manage_medicine_via_app

Between Groups

1.700

1

1.700

1.722

Within Groups

110.555

112

.987

 

Total

112.254

113

 

 

concern

Between Groups

3.517

1

3.517

1.243

Within Groups

316.773

112

2.828

 

Total

320.289

113

 

 

regulated

Between Groups

1.475

1

1.475

2.066

Within Groups

79.964

112

.714

 

Total

81.439

113

 

 

training

Between Groups

1.991

1

1.991

2.191

Within Groups

101.764

112

.909

 

Total

103.754

113

 

 

used_app_by_the_public

Between Groups

2.527

1

2.527

1.184

Within Groups

238.991

112

2.134

 

Total

241.518

113

 

 

aid_medication_adherece

Between Groups

.039

1

.039

.017

Within Groups

251.900

112

2.249

 

Total

251.939

113

 

 

ease_of_use

Between Groups

1.458

1

1.458

3.693


This is another Analysis of variance (ANOVA) which is purposefully used to show the the sum of squares, df, mean square and the f of the given parameters mentioned in the table format (7).

ANOVA

 

Sig.

adherence_to_medication

Total

 

recommending_external_device

Between Groups

.726

Within Groups

 

Total

 

promoted_by_professional

Between Groups

.661

Within Groups

 

Total

 

fun

Between Groups

.353

Within Groups

 

Total

 

impact_on_battery_life

Between Groups

.558

Within Groups

 

Total

 

manage_medicine_via_app

Between Groups

.192

Within Groups

 

Total

 

concern

Between Groups

.267

Within Groups

 

Total

 

Regulated

Between Groups

.153

Within Groups

 

Total

 

Training

Between Groups

.142

Within Groups

 

Total

 

used_app_by_the_public

Between Groups

.279

Within Groups

 

Total

 

aid_medication_adherece

Between Groups

.896

Within Groups

 

Total

 

ease_of_use

Between Groups

.057

 

ANOVA

 

Sum of Squares

df

Mean Square

F

ease_of_use

Within Groups

43.817

111

.395

 

Total

45.274

112

 

 

reliability_security

Between Groups

3.561

1

3.561

3.375

Within Groups

111.846

106

1.055

 

Total

115.407

107

 

 

regulated_information

Between Groups

7.114

1

7.114

4.741

Within Groups

153.040

102

1.500

 

Total

160.154

103

 

 

cost

Between Groups

4.202

1

4.202

2.957

Within Groups

143.545

101

1.421

 

Total

147.748

102

 

 


The above tabled ANOVA is made to show the sum of squares, df, mean square and the f of the given parameters such as ease of use, reliability security associated with the app, regulated information and the cost regarding to the apps.

ANOVA

 

Sig.

ease_of_use

Within Groups

 

Total

 

reliability_security

Between Groups

.069

Within Groups

 

Total

 

regulated_information

Between Groups

.032

Within Groups

 

Total

 

Cost

Between Groups

.089

Within Groups

 

Total

 

 

Now it is important to say that the partial correlation of the given data is also prepared statically to analyze the importance. Basically partial correlation is used to measure the specific degree of association between two random variables (5).

 

Partial Correlation

Correlations

 

smartphone

platform

hours_per_day

Smartphone

Pearson Correlation

1

.a

.a

Sig. (2-tailed)

 

.000

.000

N

114

110

110

Platform

Pearson Correlation

.a

1

-.090

Sig. (2-tailed)

.000

 

.349

N

110

110

110

hours_per_day

Pearson Correlation

.a

-.090

1

Sig. (2-tailed)

.000

.349

 

N

110

110

110

healthcare_apps

Pearson Correlation

.a

.097

-.143

Sig. (2-tailed)

.000

.370

.187

N

87

87

87

game_based

Pearson Correlation

.a

-.100

-.149

Sig. (2-tailed)

.000

.341

.156

N

92

92

92

search_tool

Pearson Correlation

.a

-.394**

.285**

Sig. (2-tailed)

.000

.000

.005

N

96

96

96

social_networking

Pearson Correlation

.a

.145

.035

Sig. (2-tailed)

.000

.145

.726

N

103

103

103

news_apps

Pearson Correlation

.a

.121

.167

Sig. (2-tailed)

.000

.219

.089

N

105

105

105

Using

Pearson Correlation

.a

-.115

-.166

Sig. (2-tailed)

.000

.231

.084

N

110

110

110

monitoring_health

Pearson Correlation

.206*

-.223*

-.209*

Sig. (2-tailed)

.029

.021

.030

N

112

108

108

manage_medication

Pearson Correlation

.330**

-.251**

.006

Sig. (2-tailed)

.000

.008

.954


This correlation data chart is correlating the smart phone, the given platform and the usage of per hours with the other statistical variables lined into the left side of the chart.

Correlations

 

healthcare_apps

game_based

search_tool

Smartphone

Pearson Correlation

.

.a

.a

Sig. (2-tailed)

.000

.000

.000

N

87

92

96

Platform

Pearson Correlation

.097a

-.100

-.394

Sig. (2-tailed)

.370

.341

.000

N

87

92

96

hours_per_day

Pearson Correlation

-.143a

-.149

.285

Sig. (2-tailed)

.187

.156

.005

N

87

92

96

healthcare_apps

Pearson Correlation

1a

.062

-.444

Sig. (2-tailed)

 

.569

.000

N

87

86

86

game_based

Pearson Correlation

.062a

1

.012

Sig. (2-tailed)

.569

 

.914

N

86

92

88

search_tool

Pearson Correlation

-.444a

.012**

1**

Sig. (2-tailed)

.000

.914

 

N

86

88

96

social_networking

Pearson Correlation

-.358a

-.471

-.271

Sig. (2-tailed)

.001

.000

.008

N

87

90

94

news_apps

Pearson Correlation

-.286a

-.304

-.036

Sig. (2-tailed)

.007

.004

.728

N

87

90

96

Using

Pearson Correlation

-.313a

.035

.309

Sig. (2-tailed)

.003

.740

.002

N

87

92

96

monitoring_health

Pearson Correlation

-.017*

.280*

.162*

Sig. (2-tailed)

.873

.007

.116

N

87

90

96

manage_medication

Pearson Correlation

.016**

.250**

.274

Sig. (2-tailed)

.885

.016

.007


This correlation data chart is correlating the health care app, game based app and the usage of search tool apps with the other statistical variables lined into the left side of the chart.

Correlations

 

social_networking

news_apps

using

Smartphone

Pearson Correlation

.

.a

.a

Sig. (2-tailed)

.000

.000

.000

N

103

105

110

Platform

Pearson Correlation

.145a

.121

-.115

Sig. (2-tailed)

.145

.219

.231

N

103

105

110

hours_per_day

Pearson Correlation

.035a

.167

-.166

Sig. (2-tailed)

.726

.089

.084

N

103

105

110

healthcare_apps

Pearson Correlation

-.358a

-.286

-.313

Sig. (2-tailed)

.001

.007

.003

N

87

87

87

game_based

Pearson Correlation

-.471a

-.304

.035

Sig. (2-tailed)

.000

.004

.740

N

90

90

92

search_tool

Pearson Correlation

-.271a

-.036**

.309**

Sig. (2-tailed)

.008

.728

.002

N

94

96

96

social_networking

Pearson Correlation

1a

-.202

-.045

Sig. (2-tailed)

 

.043

.651

N

103

101

103

news_apps

Pearson Correlation

-.202a

1

-.005

Sig. (2-tailed)

.043

 

.960

N

101

105

105

Using

Pearson Correlation

-.045a

-.005

1

Sig. (2-tailed)

.651

.960

 

N

103

105

110

monitoring_health

Pearson Correlation

-.125*

-.096*

.065*

Sig. (2-tailed)

.211

.331

.503

N

101

105

108

manage_medication

Pearson Correlation

-.208**

-.067**

.126

Sig. (2-tailed)

.035

.495

.188


This correlation data chart is correlating the social networking apps, new apps and the using apps with the other statistical variables lined into the left side of the chart.

Correlations

 

monitoring_health

manage_medication

consulting_healthcare_professional

Smartphone

Pearson Correlation

.206

.330a

-.229a

Sig. (2-tailed)

.029

.000

.014

N

112

114

114

Platform

Pearson Correlation

-.223a

-.251

-.066

Sig. (2-tailed)

.021

.008

.491

N

108

110

110

hours_per_day

Pearson Correlation

-.209a

.006

.116

Sig. (2-tailed)

.030

.954

.229

N

108

110

110

healthcare_apps

Pearson Correlation

-.017a

.016

.109

Sig. (2-tailed)

.873

.885

.316

N

87

87

87

game_based

Pearson Correlation

.280a

.250

.048

Sig. (2-tailed)

.007

.016

.651

N

90

92

92

search_tool

Pearson Correlation

.162a

.274**

-.182**

Sig. (2-tailed)

.116

.007

.076

N

96

96

96

social_networking

Pearson Correlation

-.125a

-.208

.007

Sig. (2-tailed)

.211

.035

.945

N

101

103

103

news_apps

Pearson Correlation

-.096a

-.067

-.102

Sig. (2-tailed)

.331

.495

.300

N

105

105

105

Using

Pearson Correlation

.065a

.126

.106

Sig. (2-tailed)

.503

.188

.269

N

108

110

110

monitoring_health

Pearson Correlation

1*

.463*

-.085*

Sig. (2-tailed)

 

.000

.375

N

112

112

112

manage_medication

Pearson Correlation

.463**

1**

-.075

Sig. (2-tailed)

.000

 

.425


This correlation data chart is correlating the monitoring health app, manage medication and consulting healthcare professionals with the other statistical variables lined into the left side of the chart (9).

Correlations

 

different_medicines

take_medication

forget

Smartphone

Pearson Correlation

.138

.255a

.a

Sig. (2-tailed)

.144

.006

.000

N

113

114

98

Platform

Pearson Correlation

-.091a

.090

.143

Sig. (2-tailed)

.349

.351

.160

N

109

110

98

hours_per_day

Pearson Correlation

.289a

.032

-.268

Sig. (2-tailed)

.002

.743

.008

N

109

110

98

healthcare_apps

Pearson Correlation

-.267a

-.146

.025

Sig. (2-tailed)

.012

.177

.828

N

87

87

78

game_based

Pearson Correlation

-.222a

.189

-.174

Sig. (2-tailed)

.033

.072

.124

N

92

92

80

search_tool

Pearson Correlation

.440a

-.058**

.016**

Sig. (2-tailed)

.000

.576

.883

N

95

96

86

social_networking

Pearson Correlation

-.058a

.132

.080

Sig. (2-tailed)

.562

.183

.449

N

102

103

91

news_apps

Pearson Correlation

.256a

-.100

.020

Sig. (2-tailed)

.009

.309

.848

N

104

105

95

Using

Pearson Correlation

.127a

.204

-.167

Sig. (2-tailed)

.188

.032

.101

N

109

110

98

monitoring_health

Pearson Correlation

.249*

.271*

.142*

Sig. (2-tailed)

.008

.004

.162

N

111

112

98

manage_medication

Pearson Correlation

.280**

.479**

.122

Sig. (2-tailed)

.003

.000

.232


This correlation data chart is correlating the different medicines, taking medicines and the forget mentality with the other statistical variables lined into the left side of the chart.

Correlations

 

side_effects

feel_well_enough

lack_of_time

Smartphone

Pearson Correlation

-.026

.203a

.a

Sig. (2-tailed)

.812

.300

.000

N

86

28

13

Platform

Pearson Correlation

.141a

.030

-.319

Sig. (2-tailed)

.200

.885

.288

N

84

26

13

hours_per_day

Pearson Correlation

-.200a

-.446

.509

Sig. (2-tailed)

.068

.022

.076

N

84

26

13

healthcare_apps

Pearson Correlation

.217a

-.830

.091

Sig. (2-tailed)

.083

.000

.791

N

65

19

11

game_based

Pearson Correlation

-.093a

.071

.284

Sig. (2-tailed)

.455

.760

.370

N

67

21

12

search_tool

Pearson Correlation

-.326a

.152**

-.010**

Sig. (2-tailed)

.005

.522

.973

N

72

20

13

social_networking

Pearson Correlation

.086a

-.048

-.415

Sig. (2-tailed)

.456

.814

.159

N

77

26

13

news_apps

Pearson Correlation

.024a

-.059

.020

Sig. (2-tailed)

.829

.784

.948

N

81

24

13

Using

Pearson Correlation

-.091a

.609

-.348

Sig. (2-tailed)

.413

.001

.243

N

84

26

13

monitoring_health

Pearson Correlation

-.259*

-.030*

-.141*

Sig. (2-tailed)

.016

.885

.646

N

86

26

13

manage_medication

Pearson Correlation

-.025**

-.238**

.563

Sig. (2-tailed)

.816

.223

.045


This correlation data chart is correlating the side effects, feel well enough and the lack of time with the other statistical variables lined into the left side of the chart.

Correlations

 

no_improvement

lack_of_understanding

dosage_form_inappropriate

Smartphone

Pearson Correlation

.

-.357a

.a

Sig. (2-tailed)

.000

.004

.000

N

24

62

27

Platform

Pearson Correlation

-.160a

-.019

-.530

Sig. (2-tailed)

.455

.885

.004

N

24

58

27

hours_per_day

Pearson Correlation

.582a

.545

.250

Sig. (2-tailed)

.003

.000

.209

N

24

58

27

healthcare_apps

Pearson Correlation

-.388a

.280

-.123

Sig. (2-tailed)

.082

.069

.566

N

21

43

24

game_based

Pearson Correlation

.329a

.172

.177

Sig. (2-tailed)

.126

.238

.409

N

23

49

24

search_tool

Pearson Correlation

-.283a

-.132**

.126**

Sig. (2-tailed)

.214

.366

.531

N

21

49

27

social_networking

Pearson Correlation

.296a

-.361

-.122

Sig. (2-tailed)

.160

.009

.545

N

24

51

27

news_apps

Pearson Correlation

-.282a

.202

.000

Sig. (2-tailed)

.203

.147

1.000

N

22

53

27

Using

Pearson Correlation

.503a

.046

.000

Sig. (2-tailed)

.012

.734

1.000

N

24

58

27

monitoring_health

Pearson Correlation

-.079*

-.280*

.231*

Sig. (2-tailed)

.727

.030

.245

N

22

60

27

manage_medication

Pearson Correlation

.160**

-.208**

.581

Sig. (2-tailed)

.456

.105

.001


This correlation data chart is correlating no improvement, lack of understanding and the doses form with the other statistical variables lined into the left side of the chart (11).

Correlations

 

strategy_to_take

helping_adherence

adherence_to_medication

Smartphone

Pearson Correlation

.389

.188a

-.067a

Sig. (2-tailed)

.000

.046

.481

N

108

114

114

Platform

Pearson Correlation

.032a

-.150

.037

Sig. (2-tailed)

.749

.117

.700

N

104

110

110

hours_per_day

Pearson Correlation

-.018a

-.029

.057

Sig. (2-tailed)

.857

.765

.555

N

104

110

110

healthcare_apps

Pearson Correlation

.292a

-.205

.191

Sig. (2-tailed)

.008

.057

.076

N

81

87

87

game_based

Pearson Correlation

.040a

-.042

-.327

Sig. (2-tailed)

.716

.691

.001

N

86

92

92

search_tool

Pearson Correlation

-.281a

-.234**

-.347**

Sig. (2-tailed)

.007

.022

.001

N

90

96

96

social_networking

Pearson Correlation

.108a

.379

.423

Sig. (2-tailed)

.294

.000

.000

N

97

103

103

news_apps

Pearson Correlation

.019a

-.072

-.286

Sig. (2-tailed)

.853

.465

.003

N

99

105

105

Using

Pearson Correlation

-.210a

.032

.084

Sig. (2-tailed)

.032

.737

.385

N

104

110

110

monitoring_health

Pearson Correlation

.218*

.003*

-.378*

Sig. (2-tailed)

.025

.978

.000

N

106

112

112

manage_medication

Pearson Correlation

.190**

.063**

-.278

Sig. (2-tailed)

.049

.505

.003


This correlation data chart is correlating strategy to take, helping adherence and adherence to medication with the other statistical variables lined into the left side of the chart.

Correlations

 

recommending_external_device

promoted_by_professional

used_app_by_the_public

Smartphone

Pearson Correlation

-.033

.042a

-.102a

Sig. (2-tailed)

.726

.661

.279

N

114

113

114

Platform

Pearson Correlation

-.252a

-.207

.231

Sig. (2-tailed)

.008

.031

.015

N

110

109

110

hours_per_day

Pearson Correlation

-.081a

.060

.056

Sig. (2-tailed)

.398

.534

.559

N

110

109

110

healthcare_apps

Pearson Correlation

.132a

.035

.186

Sig. (2-tailed)

.224

.746

.085

N

87

87

87

game_based

Pearson Correlation

-.134a

-.144

-.210

Sig. (2-tailed)

.203

.171

.044

N

92

92

92

search_tool

Pearson Correlation

-.146a

-.116**

-.250**

Sig. (2-tailed)

.155

.264

.014

N

96

95

96

social_networking

Pearson Correlation

.056a

.049

.191

Sig. (2-tailed)

.576

.628

.053

N

103

102

103

news_apps

Pearson Correlation

-.158a

-.038

.171

Sig. (2-tailed)

.108

.704

.081

N

105

104

105

Using

Pearson Correlation

.039a

.073

-.020

Sig. (2-tailed)

.685

.452

.836

N

110

109

110

monitoring_health

Pearson Correlation

.204*

.226*

-.155*

Sig. (2-tailed)

.031

.017

.102

N

112

111

112

manage_medication

Pearson Correlation

.212**

.268**

-.243

Sig. (2-tailed)

.024

.004

.009


This correlation data chart is correlating recommending external advice, promoted by professional and usage by the public with the other statistical variables lined into the left side of the chart.

Correlations

 

aid_medication_adherece

ease_of_use

reliability_security

Smartphone

Pearson Correlation

.012

.179a

-.176a

Sig. (2-tailed)

.896

.057

.069

N

114

113

108

Platform

Pearson Correlation

-.166a

-.154

.121

Sig. (2-tailed)

.082

.110

.222

N

110

109

104

hours_per_day

Pearson Correlation

.318a

-.055

-.317

Sig. (2-tailed)

.001

.570

.001

N

110

109

104

healthcare_apps

Pearson Correlation

-.155a

.254

.171

Sig. (2-tailed)

.151

.018

.118

N

87

87

85

game_based

Pearson Correlation

-.404a

.013

.226

Sig. (2-tailed)

.000

.900

.034

N

92

91

88

search_tool

Pearson Correlation

.282a

-.234**

-.207**

Sig. (2-tailed)

.005

.023

.045

N

96

95

94

social_networking

Pearson Correlation

.338a

-.126

-.037

Sig. (2-tailed)

.000

.207

.714

N

103

102

101

news_apps

Pearson Correlation

-.035a

-.033

-.057

Sig. (2-tailed)

.724

.738

.575

N

105

104

101

Using

Pearson Correlation

.297a

.059

-.022

Sig. (2-tailed)

.002

.542

.824

N

110

109

104

monitoring_health

Pearson Correlation

-.099*

.256*

.093*

Sig. (2-tailed)

.301

.007

.342

N

112

111

106

manage_medication

Pearson Correlation

-.112**

.201**

-.277

Sig. (2-tailed)

.234

.033

.004


This correlation data chart is correlating aid medication adherence, ease of use and security reliability with the other statistical variables lined into the left side of the chart.

Correlations

 

regulated_information

cost

fun

impact_on_battery_life

Smartphone

Pearson Correlation

-.211

.169a

.092a

.058a

Sig. (2-tailed)

.032

.089

.353

.558

N

104

103

105

103

Platform

Pearson (3) Correlation

-.029a

.027

-.095

.021

Sig. (2-tailed)

.773

.789

.345

.838

N

100

99

101

99

hours_per_day

Pearson Correlation

-.194a

.331

.148

.132

Sig. (2-tailed)

.053

.001

.139

.192

N

100

99

101

99

healthcare_apps

Pearson Correlation

.346a

-.356

.041

-.256

Sig. (2-tailed)

.001

.001

.710

.020

N

83

82

84

82

game_based

Pearson Correlation

-.057a

-.067

.150

-.059

Sig. (2-tailed)

.607

.544

.169

.592

N

85

84

86

84

search_tool

Pearson Correlation

.162a

.176**

.002**

.030**

Sig. (2-tailed)

.128

.100

.983

.780

N

90

89

91

89

social_networking

Pearson Correlation

-.369a

.292

.119

.083**

Sig. (2-tailed)

.000

.004

.244

.423

N

97

96

98

96

news_apps

Pearson Correlation

-.108a

.006

-.213

.096**

Sig. (2-tailed)

.292

.953

.035

.353

N

97

96

98

96

Using

Pearson Correlation

-.149a

-.021

.119

.088**

Sig. (2-tailed)

.140

.833

.236

.385

N

100

99

101

99

monitoring_health

Pearson Correlation

-.133*

-.052*

.177*

-.093

Sig. (2-tailed)

.183

.605

.074

.354

N

102

101

103

101

manage_medication

Pearson Correlation

-.338**

.376**

.308

-.114

Sig. (2-tailed)

.000

.000

.001

.254

 

Correlations

 

manage_medicine_via_app

concern

regulated

training

Smartphone

Pearson Correlation

-.123

-.105a

-.135a

-.139a

Sig. (2-tailed)

.192

.267

.153

.142

N

114

114

114

114

Platform

Pearson Correlation

-.214a

-.005

-.040

-.146

Sig. (2-tailed)

.025

.959

.682

.128

N

110

110

110

110

hours_per_day

Pearson Correlation

-.029a

.023

.028

-.062

Sig. (2-tailed)

.763

.812

.768

.519

N

110

110

110

110

healthcare_apps

Pearson Correlation

.173a

.286

.237

-.053

Sig. (2-tailed)

.109

.007

.027

.627

N

87

87

87

87

game_based

Pearson Correlation

-.040a

.155

-.060

.025

Sig. (2-tailed)

.705

.139

.569

.813

N

92

92

92

92

search_tool

Pearson Correlation

-.195a

-.059**

-.150**

-.018**

Sig. (2-tailed)

.056

.570

.145

.861

N

96

96

96

96

social_networking

Pearson Correlation

-.181a

-.198

.042

-.081**

Sig. (2-tailed)

.067

.045

.670

.415

N

103

103

103

103

news_apps

Pearson Correlation

-.038a

.017

.042

-.094**

Sig. (2-tailed)

.697

.861

.672

.342

N

105

105

105

105

Using

Pearson Correlation

.254a

-.334

-.082

.388**

Sig. (2-tailed)

.008

.000

.396

.000

N

110

110

110

110

monitoring_health

Pearson Correlation

.041*

-.101*

.045*

.040

Sig. (2-tailed)

.670

.292

.638

.676

N

112

112

112

112

manage_medication

Pearson Correlation

.186**

-.027**

-.103

.255

Sig. (2-tailed)

.048

.774

.277

.006

 

Correlations

 

sex

age

experience

Smartphone

Pearson Correlation

-.041

.316a

.324a

Sig. (2-tailed)

.664

.001

.000

N

114

114

114

Platform

Pearson Correlation

-.225a

.070

.015

Sig. (2-tailed)

.018

.465

.876

N

110

110

110

hours_per_day

Pearson Correlation

-.054a

-.351

-.244

Sig. (2-tailed)

.578

.000

.010

N

110

110

110

healthcare_apps

Pearson Correlation

-.224a

-.221

-.303

Sig. (2-tailed)

.037

.039

.004

N

87

87

87

game_based

Pearson Correlation

.159a

-.274

-.204

Sig. (2-tailed)

.131

.008

.051

N

92

92

92

search_tool

Pearson Correlation

.187a

-.094**

.053**

Sig. (2-tailed)

.068

.364

.605

N

96

96

96

social_networking

Pearson Correlation

-.223a

.247

.215

Sig. (2-tailed)

.024

.012

.029

N

103

103

103

news_apps

Pearson Correlation

.145a

.031

.074

Sig. (2-tailed)

.140

.751

.455

N

105

105

105

Using

Pearson Correlation

.218a

.475

.512

Sig. (2-tailed)

.022

.000

.000

N

110

110

110

monitoring_health

Pearson Correlation

.261*

-.025*

.006*

Sig. (2-tailed)

.005

.797

.950

N

112

112

112

manage_medication

Pearson Correlation

.306**

-.009**

-.042

Sig. (2-tailed)

.001

.921

.654

 

 

 

 

 


This correlation data chart is correlating sex, age and experience of people with the other statistical variables lined into the left side of the chart.

 

Automatic Linear Modeling

Case Processing Summary

 

N

Percent

Included

114

100.0%

Excluded

0

0.0%

Total

114

100.0%


After analyzing all possible given data the Automatic Linear Modeling shows the above case processing summary which included the all 114 people taken in the survey (17).

The Model summary of the analysis shows the way all the result of the data analysis based on every aspect (6).

Discussion

The discussion part is divided in two different analyses. The Analysis of variance (ANOVA) and Partial Correlation Method is specifically used to discuss the topic of using health care application in smart phone.

Analysis of variance (ANOVA)

Through Analysis of variance (ANOVA) a certain specific procedure to analyze the particular differences between means of each group and the related associated variance. In this analysis the group means help to elaborate the discussion section in a particular and statistical way (13). To relate several parameters under a section it can be said the total statistical part is a little complicated. However, it is very essential for understanding the different responses related with the different people. The variables and the group means helps to understand every aspects of the data part related with the apps. Through the unanimous discussion of the output of the several parameters a conclusive point can be determined. The interrelation of the given data has extracted the importance of the application which can provide medical health care through smart phone at any point or any situation (2). Analysis of variance (ANOVA) which is purposefully used to show the sum of squares, df, mean square and the f of the given parameters like smart phone, the given platform, the usage of per hours, the health care app, game based app, the usage of search tool apps, the social networking apps, new apps, the using apps, the monitoring health app, manage medication, consulting healthcare professionals, the different medicines, taking medicines, the forget mentality the side effects, feel well enough, the lack of time no improvement, lack of understanding, the doses strategy to take, helping adherence, adherence to medication recommending external advice, promoted by professional, usage by the public aid medication adherence, ease of use and security reliability sex, age and experience of people. All the sufficient data and analysis are supporting for the application to be used among the people through smart phone (16).

Partial correlation analysis

Partial correlation is used to measure the specific degree of association between two random variables. In this case the essence of this specific method is quite important to show the importance of the app in the life of common people (8). For the essential statistics needed to sum up the process to obtain the result are very vital for the very cause. Through this method the number of surveyor, Pearson Correlation and significance is concluded of several variables given in the research such as smart phone, the given platform, the usage of per hours, the health care app, game based app, the usage of search tool apps, the social networking apps, new apps, the using apps, the monitoring health app, manage medication, consulting healthcare professionals, the different medicines, taking medicines, the forget mentality the side effects, feel well enough, the lack of time no improvement, lack of understanding, the doses strategy to take, helping adherence, adherence to medication recommending external advice, promoted by professional, usage by the public aid medication adherence, ease of use and security reliability sex, age and experience of people. The results also help to achieve to a certain point to define whether it is important for people to accept the mobile application which provides support heath care (20).

Automatic Linear Modeling and Model summary

Automatic Linear Modeling generally ensures the processing summary of the whole method supporting the decision. The model summary shows the accuracy is 58.4 percent which is quite good response respective of the analysis done on people. These parameters and statistical logistics are also supporting for the use of the heath care application to a certain extent (14).

Questionnaire Designs and Result Analysis

As per the design of the questionnaire, it is prepared in such way that it contains the opinions of the pharmacists in support with the medication application. Out of 250 questionnaires, the pharmacies community of Liverpool provided their specific and valuable views. Mainly the important sections established in the questionnaires are the medication adherence, self-care, background status, demographic data and usability of the application.

Questionnaires

Results

How many of the patients use Smart Phone?

It has been found from the analysis that 58% of the patients uses smart phone. But most of them are not brand concern because the brand does not effects the use of health care application

Do you use the application for at least 4 hours a day ?

We figured out that almost 32 percent of the patients that are using these application for medical help, often uses this for more than 4 hours

Does the health care app provide effective search tool?

The health care app that is used by most of the patients in today’s world. Out of the total respondents only few of them stated that the app provides effective search tool options

Do the health app supports the social media networking?

It was found out that a huge number of people use this health care app as it supports social media networking techniques. Nearly 42 percent of the respondents like the above technique that was figured out in the survey

Does the app also support different medical related news application?

Nearly 65% of the people are in love with the medical application that is supported in their Smartphone as it also provide several news application that I loved by almost 70% of the people using this app

Does the app provide effective monitoring health facility?

Most of the users that are using the health care application feels that the app provides quite effective monitoring facilities that help them in all respect. Almost 51% of the people believe so out of the total respondents that participated in the feedback process

Is the app successful in managing the medication procedure?

The Medicare health app is quite effective in maintaining and managing the medication procedure as there are very few respondents that feel this app to effective enough

Does the app incorporate consultation of doctors?

Most of the users of this app are quite happy with the consultation feature of this app as they receive all the effective feedbacks from the doctors that is much more important than anything else.

Does the app include different consulting healthcare professionals?

Nearly 70% of the respondents feels that this health care application is quite helpful for them as it provides them with all the important tips of the healthcare professionals

Does the app provide the specifications of different medicines?

Many respondents in the survey feel that the app to be quite effective as it provides all the specifications of the medical that is required by the patient.

Does the application state the side effect of different medicines?

The maximum number of respondents like the application for this feature as it explains all the side effects that goes along with the medicine

Does the patient feel good enough after using the application

Most of the respondents feel the application to be very helpful and at the same time quite information that provides them security and safety in all aspects

Does the app run successfully in all smart phones?

There are many people that are using this application. Many of the respondents stated this application to be user-friendly as it is installed in almost every type of Smartphone.

Do the patients feel comfortable using the application?

Most of the patients that uses this application is above 40 years age and hence most of them feel it difficult to use this app irrespective of an user friendly approach

Is the app helpful to adheres medication to the patients?

About 40 percent of the patients believe that this app is quite helpful in adhering medication for the patients in all respect

Does other medical professional suggest other external devices?

There are very few people that are using the app has stated the app which provides many other external devices

How many of you feel the application to be effective?

Nearly 70% of the people that are using this medical application feel the application to be quite effective for medical purpose

Does u feel that the app provides reliability and security?

Only a few percentages of people fill that the medical application provider better security and reliability to the sources.

Does the application provide adequate and regulated information?

Nearly 70% of the people feel that the medical application provide the patient with types of regulated and adequate information

Does the application help the patients with regular tips and advices?

Most of the patients feel that the application provides the user with regular updates and advices on medical techniques

 

 

Analysis of the above questionnaires

It has been found from the analysis that 58% of the patients uses smart phone. But most of them are not brand concern because the brand does not affects the use of health care application

We figured out that almost 32 percent of the patients that are using these applications for medical help often use this for more than 4 hours. The health care app that is used by most of the patients in today’s world. Out of the total respondents only few of them stated that the app provides effective search tool options. It was found out that a huge number of people use this health care app as it supports social media networking techniques. Nearly 42 percent of the respondents like the above technique that was figured out in the survey. Nearly 65% of the people are in love with the medical application that is supported in their Smartphone as it also provide several news application that I loved by almost 70% of the people using this app. Most of the users that are using the health care application feels that the app provides quite effective monitoring facilities that help them in all respect. Almost 51% of the people believe so out of the total respondents that participated in the feedback process. The Medicare health app is quite effective in maintaining and managing the medication procedure as there are very few respondents that feel this app to effective enough. Most of the users of this app are quite happy with the consultation feature of this app as they receive all the effective feedbacks from the doctors that is much more important than anything else. Nearly 70% of the respondents feel that this health care application is quite helpful for them as it provides them with all the important tips of the healthcare professionals. Many respondents in the survey feel that the app to be quite effective as it provides all the specifications of the medical that is required by the patient. The maximum number of respondents like the application for this feature as it explains all the side effects that go along with the medicine. Most of the respondents feel the application to be very helpful and at the same time quite information that provides them security and safety in all aspects. There are many people that are using this application. Many of the respondents stated this application to be user-friendly as it is installed in almost every type of Smartphone. Most of the patients that uses this application is above 40 years age and hence most of them feel it difficult to use this app irrespective of an user friendly approach. About 40 percent of the patients believe that this app is quite helpful in adhering medication for the patients in all respect. There are very few people that are using the app has stated the app which provides many other external devices. Nearly 70% of the people that are using this medical application feel the application to be quite effective for medical purpose. Only a few percentages of people fill that the medical application provider better security and reliability to the sources. Nearly 70% of the people feel that the medical application provides the patient with types of regulated and adequate information. Most of the patients feel that the application provides the user with regular updates and advices on medical techniques. Now if we come in to the result part the Analysis of variance (ANOVA) and the Partial correlation suggests many definite proportion of the result that is shown in the chart. Broader analysis of result is done in the chart section and that showed most of the sections out of the five such as medication adherence, self-care, background status, demographic data and usability of the application giving out positive sort of results by the pharmacies community to implement the application for the Medicare sector. Lots of complicated results have also come out from the process and many of them does not need to be taken under consideration as the result has bare minimum effect on the whole process. Also the model summary shows the accuracy is 58.4 percent which is a moderate result summery though the number is above 50 percent which shows positivity to the most of the 250 questionnaires.

 

Conclusion

As per the analysis and the discussion part it has to be ensured that the healthcare app in the smart phone is a very good technology for mankind. The common people in the busy and hectic sort of life style will find the application more suitable to use. As the data and charts statistically shows the preference of smart phone holder with using the specific apps along with other apps (15). Also by discussing the efficiency of taking medicines at times, the forgetful nature of common people to take medicines and check health related problems the Medicare app will be very important in the near future. Additionally human are depending more and more on technology and gadgets. Therefore it will be easy to maintain the Medicare help in the hectic life. Also the essentiality of measuring many aspects of body is providing support for the application. Monitoring health through the app will prove a success as the specific app can check several physical data like heart beat monitoring, blood pressure, analyzing gasping states of body, excess stress level as well as several reminders like taking medicines, measuring distances covered by walking and running, importance of many biological issues affecting the human body in several circumstances. Following to all of the survey work and the statistical analysis and the discussion portion one have to certainly believe the necessity of the app relating to health care. According to the data it is quite clear that the issuing healthcare application in the smart phone will definitely show the possibilities of the app in several lives saving aspect too. As the developing technology has taken the health care sector to a possible height similarly the possibilities are quite clear that the particular smart phone app has every chance to make a vital impact by guiding human life to maintain a good habit to maintain a healthy life style. The human life will be certainly benefited by using the apps as it can add much important information regarding to the health in an electrical way. Every part of the statistical part is providing support to the possibilities. As in a hectic working life human is used to go through a quite stressful life therefore the possibilities of physical attention is becoming lesser important in the life. In this situation the app can be proved to be most essential support system for human life. However the application can supply most of the vital information to lead a healthy life. The usefulness of it is quite significant that can be rest assured. Therefore after all the analysis it can be concluded that using health care application in smart phone is really an essential suggestion.

 

References

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2. Martin C, Preedy V. Scientific basis of healthcare. Jersey, British Channel Islands: Science Publishers; 2012.
3. Schouten B, Fedtke S, Schijven M, Vosmeer M, Gekker A. Games for Health 2014.
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