to evaluate the efficacy of app-supported smartphone interventions on a range of mental health outcomes, and to examine whether various features related to the intervention (theoretical orientation, whether professional guidance was offered, whether reminders to engage were sent) and sample (degree of mental health problem) moderated the observed effect sizes

1. Total slides – 93
Presenter
Dr Rachit Sharma
Junior Resident (Psychiatry)
Armed Forces Medical College,
Pune
Moderator
Dr VS Chauhan
Assoc Prof (Psychiatry)
Armed Forces Medical College,
Pune

2. 2

3. Benefit exceeds Risk :Case Vignette
3
Torous J, Roberts LW. The ethical use of mobile health technology in clinical psychiatry. The Journal of nervous
and mental disease. 2017 Jan 1;205(1):4-8.

4. Benefit exceeds Risk :Case Vignette
4
Torous J, Roberts LW. The ethical use of mobile health technology in clinical psychiatry. The Journal of nervous
and mental disease. 2017 Jan 1;205(1):4-8.

5. Risk exceeds benefit: Case Vignette
5
Torous J, Roberts LW. The ethical use of mobile health technology in clinical psychiatry. The Journal of nervous
and mental disease. 2017 Jan 1;205(1):4-8.

6. Risk exceeds benefit: Case Vignette
6
Torous J, Roberts LW. The ethical use of mobile health technology in clinical psychiatry. The Journal of nervous
and mental disease. 2017 Jan 1;205(1):4-8.

7. Why I chose this article?
• Rapid development in the app industry – Multiple
apps are being developed daily
• Recent focus- a shift to Mental health apps
• 2nd National CME on Media and Mental Health –
Delegates were educated about these apps
 Used in what all disorders?
 How effective are these apps ?
 Used Adjunct or alone ?
 How long their effect lasts?
7

8. Why I chose this article?
• Searched – Google scholar, PubMed,
ResearchGate
• MeSH words – mHealth, mental health apps,
e-Health apps, smartphone apps AND
Psychiatric illness, anxiety, depression, stress
AND systemic reviews, meta-analysis
8

9. Overview
INTRODUCTION
• Background
• Related studies
ARTICLE
• Aim and Objectives
• Material and Methods
• Statistical Methods
• Results
• Discussion
• Strengths & Limitations
• Critique
• Legal issues in e-Health
9

10. Background
10

11. Background
• 1,60,000 health-related apps available in the
Google Play and Apple app (2015)
• Nearly 1/3 of disease specific apps have a
mental health focus
• Over half of mobile phone users had
downloaded a health-related app
• Support for a variety of mental illnesses -
Depression, Anxiety, Schizophrenia, Addiction
and Eating disorders
11

12. Benefits
• Reduce barriers to mental health services
1. Cost, distance, wait-times, and stigma
surrounding receiving treatment
2. Improve the mental health support such as real-
time monitoring
3. Promote user autonomy by facilitating an
increase in self-awareness and self-efficacy skills
12
Robillard JM, Feng TL, Sporn AB, Lai JA, Lo C, Ta M, Nadler R. Availability, readability, and content of privacy
policies and terms of agreements of mental health apps. Internet Interventions. 2019 Sep 1;17:100243.

13. Risks
1. Apps may be vulnerable to technical issues that may
disrupt the availability of the services
2. Quality of the services - Whether apps underwent
any any formal technical testing ?
3. Harm potential - Whether information provided is
accurate and evidence-based?
4. Discouragement in seeking professional help -
Believing that the app alone can suffice
5. Potential security and privacy risks
13
Robillard JM, Feng TL, Sporn AB, Lai JA, Lo C, Ta M, Nadler R. Availability, readability, and content of privacy
policies and terms of agreements of mental health apps. Internet Interventions. 2019 Sep 1;17:100243.

14. Background
14
Menon V, Rajan TM, Sarkar S. Psychotherapeutic applications of mobile phone-based technologies: A systematic review of current research and
trends. Indian J Psychol Med 2017;39:4-11.

15. mHealth apps
15

16. Related studies
16

17. Related Study 1
17
-

18. Related Study 1: Abstract
18

19. Related Study 1: Results
19

20. Related Study 2
20

21. Related Study 2: Abstract
21

22. Related Study 2: Results
22

23. Related Study 2: Results
23

24. Related Study 2: Results
24

25. Article in focus
25

26. Article in focus

27. World Psychiatry
• Impact Factor 34.024 (2018)
• Rank 02/ 453 (SJR)
• Triannual
• Editor-Prof Mario Mej
Department of Psychiatry
University of Naples, Naples
Italy
27
http://www.scimagojr.com/journalrank.php?category=2738&area=2700&year=2019

28. Lead Author
28
• Dr Jake Linardon, Ph.D
School of Psychology, Deakin University,
Victoria, Australia
Publications – 38
• Areas of interest –
• Eating disorders, Body image

29. Aim
1. To evaluate the efficacy of app-supported
smart phone interventions on a range of
mental health outcomes
2. To examine whether various features related
to the intervention (theoretical orientation,
professional guidance, reminders to engage) and sample
(degree of mental health problem) moderated the
observed effect sizes
29

30. Material and Methods
• Nature of Study
– Meta analysis of randomized control trials
30

31. Material and Methods
• Intervention
– App based Smart phone intervention to improve
mental health or general well-being.
– Trials of interventions delivered only in part via
smartphone
• Adjunctive designs (smartphone app + standard
therapy vs. standard therapy alone)
• Blended intervention programs (when participants
could access the app-based intervention via
smartphones or computers)
31

32. Material and Methods
Control condition
• Waitlist
• Assessment only
• Treatment as usual
• Informational and
educational resources
• Attention/placebo
controls
Active Intervention
• Standard face-to-face
therapy
• Web-based or
computerized
interventions
• Pharmacotherapy
• Self-monitoring
conditions
32
Comparison conditions

33. Material and Methods
• Main outcome
– Effect of smart phone apps on Depressive,
Generalized Anxiety, Stress levels and Quality of
life (Using self reported proforma)
• Additional outcome
– Effect of smart phone apps on specific anxiety
symptoms (social anxiety symptoms, panic
symptoms, post-traumatic stress symptoms)
General distress, Positive and Negative affect
33

34. Inclusion Criteria
• RCTs (Published and unpublished) with following
criteria
– Language - English
– Studies that examined the effects of an app-
supported smartphone intervention
– Comparison with a control condition or an active
intervention
– Interventions involving adjunctive designs and
blended intervention programs
34

35. Exclusion Criteria
• RCT with following criteria-
– Using interventions that were not based on
mental health or well being
– Using interventions that uses computerized
intervention, a virtual reality exposure treatment,
or a text messaging only
– No relevant comparison condition, no outcome
measure was reported
– If the authors failed to provide the data for effect
size calculation
35

36. Progression of study
36
• Literature Search - December 2018
– Medline, PsycINFO, Cochrane databases, Web of
Science)
– Reference lists of included studies and previous
reviews were also hand-searched to identify
any further eligible studies
– Trial registries - ClinicalTrials.gov and
clinicaltrialsregister.eu.

37. Progression of study
• MeSH words - “smartphone*” OR “mobile phone”
OR “cell phone” OR “mobile app*” OR “iphone” OR “android”
OR “mhealth” OR “m-health” OR “cellular phone” OR “mobile
device*” OR “mobile-based” OR "mobile health" OR “tablet-
based”) AND (“random*” OR “trial*” OR “allocat*”) AND
(“anxiety” OR “agoraphobia” OR “phobia*” OR “panic” OR
“post-traumatic stress” OR “mental health” OR “mental
illness*” OR “depress*” OR “affective disorder*” OR “bipolar”
OR “mood disorder*” OR “psychosis” OR “psychotic” OR
“schizophre*” OR “well-being” OR “wellbeing” OR “quality of
life” OR “self-harm” or “self-injury” OR “stress*” OR
“distress*” OR “mood” OR “body image” OR “eating
disorder*”
37

38. Progression of study
• Data extraction
– Authors independently screened the titles and
abstracts yielded by the search against the
inclusion criteria
– Articles were downloaded and again screened in
detail for the inclusion criteria
– If needed Additional information from study
authors was sought (data for calculation of effect
size)
38

39. Progression of study
• Risk of bias assessment
– Cochrane Collaboration bias assessment tool
– 4 criteria were used
– Low risk - When outcome data used to calculate
effect size were based on ITT analyses
– Unpublished studies by checking pre-registration
of trials
39

40. PRISMA: Flow Chart
40

41. PRISMA: Flow Chart
41

42. Statistical Analysis
1. Comprehensive Meta-Analysis Version 3.0
2. Random effects model with use of standard
mean difference
3. Effect size - Hedge’s ‘g’
4. For Heterogeneity – I2
5. Significance - Q value
6. Publication Bias –
1. Trim-and-fil procedure
2. Begg and Mazumdar rank correlation test
42

43. Tests of significance : Q value
• P-value gives you the probability of a false
positive on a single test.
• Q-value is a P-value that has been adjusted for
the False Discovery Rate (FDR)
• FDR - Proportion of false positives expected
out of a test
• Use of Q-values - If you’re running hundreds
or thousands of tests from small samples
(common in fields like genomics)
43

44. Tests of significance : Q value
44
• P-values tell you the percentage of
false positives to expect and take
into account the number of tests
being run
• Q-value doesn’t take into account all the tests; they
only take into account the tests that are below a
threshold that you choose (i.e. tests reporting a q-
value of 5% or less)

45. Results
45

46. Results
• 66 RCTs
– 38 RCT
• Depression (14), Anxiety (9), Stress (8)
– 28 RCT
• General well-being
• 77 smartphone intervention conditions
• 73 Apps
– Cognitive and/or behavioral principles (35)
– Acceptance- or mindfulness-based principles (38)
• 46

47. Results
• Some RCTs – App v/s Active
intervention/Control
• Some RCTs – App v/s Control/Blended/
Adjunctive
47

48. Results
Effect on depressive symptoms
• Smartphone interventions vs. Controls
• Smartphone interventions vs. active
comparisons
• Additive effects of smartphone interventions
to standard intervention
48

49. Results
Effect on depressive symptoms
49

50. Results
Effect on depressive symptoms
50

51. Results
Effect on depressive symptoms
51

52. Effect on depressive symptoms
52

53. Effect on depressive symptoms
53

54. Results
Effect on Gen. Anxiety symptoms
• Smartphone interventions vs. Controls
• Subgroup analysis
• Smartphone interventions vs. Active
comparisons
54

55. Results
Effect on Gen. Anxiety symptoms
55

56. Results
Effect on Gen. Anxiety symptoms
56

57. Results
Effect on Gen. Anxiety symptoms
57

58. Effect on Gen. Anxiety symptoms
58

59. Effect on Gen. Anxiety symptoms
59

60. Results
• Efficacy of smartphone interventions on stress
levels
• Efficacy of smartphone interventions on well
being/quality of life
60

61. Results
Effect on Stress levels
61

62. Results
Effect on Stress levels
62

63. Results
Effect on Stress levels
• *********
63

64. Results
Effect on Quality of life
64

65. Results
Effect on Quality of life
65

66. Results
Effect on Quality of life
66

67. Results
• Efficacy of smartphone interventions on other
outcomes
67

68. Effect on other outcomes
68

69. Bias Assessment
Bias criteria fulfilled
(More the criteria
less is the bias)
No of studies
(Out of 66)
% of studies
4/4 17 25.7 %
3/4 16 24.2%
2/4 27 40.9%
1/4 6 9.1%
69

70. Discussion
70

71. Discussion
1. Mental health apps - g= 0.28 to 0.58 with
respect to control conditions in improving
various symptoms (depressive symptoms, anxiety
symptoms, stress levels, general psychological distress,
quality of life, and positive affect)
2. Statistically significant effect sizes were
observed in both symptomatic and non-
symptomatic population
71

72. Discussion
3. Apps with professional guidance and
engagement reminders - bolstered the
effectiveness of smartphone interventions
4. CBT based interventions produced larger
effects for anxiety and stress
5. Smartphone interventions did not
significantly differ from active interventions
on any outcome
72

73. Limitations (as per author)
1. Possible negative effects of smartphone
interventions were not assessed
2. Long-term sustainability of effects of
smartphone interventions were not assessed
3. Outcomes were assessed via selfreport
questionnaires - Effect size estimates may be
slightly underestimated
73

74. My comments
• Strengths
1. The study has given comprehensive review of
mental health apps for symptomatic as well as
normal population
2. It has added an update to existing data, which
was very pertinent as far as rapidly developing
m-Health is concerned
74

75. My comments
• Limitations
1. No comment on no. of participants,
Intervention and Control distribution
2. No comment on data on severity of symptoms
on inclusion, types of self reported
questionnaire
3. Population characteristics and Intervention
context not explained
4. Didn’t address the bias adequately
75

76. Sample
76

77. Take home message
• Apps can serve as a easily accessible
intervention for people who has psychological
symptoms of low intensity
• Apps with inbuilt support for professional
guidance or personalized feedback from
therapists or research staff produced larger
effect sizes
77

78. Checklist
Criteria Yes
(2)
Partial
(1)
No
(0)
N/A
1 Question/ objective sufficiently
described?
√
2 Study design evident &
appropriate?
√
3 Inclusion & Exclusion Criteria
characteristics sufficiently
described?
√
4 Sample size appropriate? √
5 Results reported in sufficient
detail?
√
78

79. Checklist
Criteria Yes
(2)
Partial
(1)
No
(0)
N/A
6 Analytic methods
described/justified &
appropriate?
√
7 Conclusions supported by the
results?
√
8 Controlled for confounding? √
9 Outcome measures well-
defined and robust to
measurement/misclassification
bias? Means of assessment
reported
√
79

80. Critique
• Clear message: 3/5
• Contribution to literature: 3/5
• Potential to change thinking or practice: 2/5
• Quality of manuscript: 2/5

81. Legal issues in e-Health
81

82. Legal issues in e-Health
• Examples of e-Health
– Telemedicine
– Robot assisted surgery
– Self-monitoring health care devices
– Electronic health records
– Health service aggregation (e.g. JUST DIAL,
SULEKHA, 1 mg)
– m-Health
– e-Pharmacy (1 mg, NetMeds)
82

83. Where are we?
83

84. Malpractice and Liability
• Duty of care and medical liability
– Laxman Balkrishna Joshi (Dr.) v/s Dr. Trimbak Bapu
Godbole (1968)
• Duty of care in deciding whether to undertake the case
• Duty of care in deciding what treatment to give
• Duty of care in the administration of that treatment
– Indian Medical Association v/s V.P. Shantha (1995)
• Applicability of Consumer Protection Act, 1986 to
persons engaged in the medical profession either as
private practitioners or as government doctors
84

85. Laws applicable to telemedicine
1. Drugs and Cosmetics Act, 1940, and Drugs and Cosmetics Rules,
1945
2. Indian Medical Council Act, 1956
3. Indian Medical Council (Professional conduct, Etiquette and Ethics)
Regulations, 2002
4. Clinical Establishments (Registration and Regulation) Act, 2010 (‘Clinical
Establishments Act’)
5. Information Technology Act, 2000 (IT Act)
6. Information Technology (Reasonable Security Practices and Procedures
and Sensitive Personal Data or Information) Rules, 2011
7. Information Technology (Intermediaries Guidelines) Rules, 2011
8. Unsolicited Commercial Communications Regulations, 2007
9. Telecom Commercial Communication Customer Preference Regulations,
2010 (‘TCCP Regulations’)
85
Ajay Garg. Legal issues in telemedicine. Diplomatic Square 2019 May 19. Available from
https://www.diplomaticsquare.com/ legal-issues-in-telemedicine/ Assessed on 13 Oct 2019

86. Laws applicable to telemedicine
• Section 4 & 5 of IT Act 2000 - Legal recognition to the
electronic record and digital signatures. Amended
Indian Evidence Act, 1872 thereby making the
electronic record admissible in evidence
• Section 2(1)(t) of the IT Act 2000 defines “electronic
record” as data, record or data generated, image or
sound stored, received or sent in an electronic form
or micro film or computer generated micro fiche.
86
Ajay Garg. Legal issues in telemedicine. Diplomatic Square 2019 May 19. Available from
https://www.diplomaticsquare.com/ legal-issues-in-telemedicine/ Assessed on 13 Oct 2019

87. Right of patient
• A conference between the telemedicine physician
and the treating physician has been considered to be
a direct interaction in order to determine the
existence of a doctor-patient relationship (Wheeler v.
Yettie Kersting Memorial Hospital)
• Even minimal contacts between doctors and patients
via telemedicine may establish a sufficient
relationship for malpractice liability
87
Ajay Garg. Legal issues in telemedicine. Diplomatic Square 2019 May 19. Available from
https://www.diplomaticsquare.com/ legal-issues-in-telemedicine/ Assessed on 13 Oct 2019

88. Right of patient
• No relationship will normally be considered to have
arisen-where the doctor-patient interaction arose
because of an emergency situation where the doctor
was forced to treat the patient (Paschim Banga Khet Mazdoor
Samity v. State of West Bengal)
88
Ajay Garg. Legal issues in telemedicine. Diplomatic Square 2019 May 19. Available from
https://www.diplomaticsquare.com/ legal-issues-in-telemedicine/ Assessed on 13 Oct 2019

89. Informed Consent
• Patient’s consent- Patient must be informed about
the nature of the telemedical application, its risks
and any alternative means of transferring their data.
The consent must be in writing and laid down in an
appropriate document
• Must inform the patient of the potential risks,
consequences and benefits of telemedicine
89
Ateriya N, Saraf A, Meshram VP, Setia P. Telemedicine and virtual consultation: The Indian perspective. The
National medical journal of India. 2018 Jul 1;31(4):215.

90. Privacy
• Privacy and Doctor-Patient relationship –
– A doctor cannot disclose to a person any information
regarding his patient which he has gathered in the course
of treatment nor can the doctor disclose to anyone else
the mode of treatment or the advice given by him to the
patient
– Information regarding a person’s physical condition,
psychological condition, healthcare and treatment shall
not be released without the patient’s consent
90
Ateriya N, Saraf A, Meshram VP, Setia P. Telemedicine and virtual consultation: The Indian perspective. The
National medical journal of India. 2018 Jul 1;31(4):215.

91. Grey areas
• Regarding e-Health - The standards of care for the
same have not been determined so far
• Also, medical malpractice case has not yet been
brought against a Cyber Physician (CP)
• It can be argued that because the doctor has not
seen the patient, that the doctor’s duty is not as
strong
• In regard to the same argument, contributory
negligence by the patient could be established
91

92. Grey areas
• If a CP fails to respond to request for medical
attention and the patient suffers injury, it is possible
that a doctor-patient relationship would be deemed
to exist and the physician would be held liable
• If the CP is on vacation and the indl believing to
receive a timely response suffers an injury because of
the cyberdoctor’s failure to respond – No clarity
regarding the responsibility
92
Ateriya N, Saraf A, Meshram VP, Setia P. Telemedicine and virtual consultation: The Indian perspective. The
National medical journal of India. 2018 Jul 1;31(4):215.

93. 93
Thank You