You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


1. Introduction/Literature Review {#sec1}
=================================

Depression enduring geriatrics was associated with increased medical morbidity, impaired body working, disturbed social functioning, and dementia \[[@B14], [@B18]\]. Depression is illustrated by insufficient sleeping hours, low or absence of diet, mood swings, glumness or isolation, and suicide ideation \[[@B15]\]. Pathology of depression in older adults has been widely discussed and assessed by researchers in present era. Researchers narrated that comparative to the other age groups elderly experienced elevated prevalence of depression in older people \[[@B24]\] In 2006 more than 400 million sufferers of depression were recorded in the world. Frequency in cases of depression horribly amplified and stood on fourth position according to global burden of diseases. Depression was announced an alarming mental health disorder. In developing countries, it is expected to be on second rank by the year 2020 \[[@B3]\].

Studies conducted by Pakistani researchers revealed that depressive elderly are severely ignored by common population because of lack of awareness. Either they went under or over recognition of depression specifically in developing countries like Pakistan \[[@B8], [@B22]\]. Though, in 2008 almost 30% incidence of depression has been found in local study conducted on elderly \[[@B6]\].

Biological studies quoted number of times about the physical superiority of women but they lack in reporting the emotional instability of women that leads to mental health issues in later life. A series of studies conducted in 2005 and 2006 demonstrated that female older adults are more vulnerable to later life depression as compared to male older adults \[[@B15], [@B4]\]. In 2003 a published research study reported the incidence of depression in women is thrice higher than men \[[@B17]\].

In later life females experienced internal marital conflicts that are responsible of marital distress \[[@B5]\]. Result of longitudinal study explains risk of having depressive episodes in later life is directly associated to marital conflicts caused by aging factors \[[@B10], [@B19]\]. Recently an extensive literature review done in 2011 documented that single elderly, either widowed, divorced, or unmarried are on greater risk of having depression as compared to married and with their siblings and spouse \[[@B21]\].

Family system acts significantly in Asian society. It has been seen that elderly belongs to rural families are less depressed than those of urban families \[[@B7]\]. Furthermore, Pakistani researchers examined that the incidence of having depression in older adults living in extensive family system is four times lesser than elderly living in nuclear family system \[[@B8]\].

Like other countries, the common age of retirement in Pakistan is 65 years. After retirement it has been seen that mostly people get relaxed and start doing the things that they missed for so many years. So, according to researchers phase of retirement is not at all depressive stage \[[@B5]\]. Instead they called it honeymoon period. On the other hand elderly who belong to private sector face the black side of later life because of financial issue caused by unemployment \[[@B13]\].

Sociocultural factors consistently have been recognized as chief factor in signifying the unpredictability in the prevalence of depression in elderly. With the advancement in modernization, cases of physical and mental health issues are increasing day by day and society become mechanical \[[@B12]\]. The lust of fame and money makes an individual deprived of sociocultural values. Because of this novel behavior, elderly are significantly affected by health issues including depression. Additionally, stress full life events, ignorance from family members, loss of loved ones, financial crises, phase of retirement, and inter- or intrapersonal conflicts accompanied with other health issues lead to late life depression \[[@B5], [@B23]\].

1.1. Objective {#sec1.1}
--------------

The main objective of the present study is to see the influence of sociocultural factors on occurrence of depression in older adults.

1.2. Hypotheses {#sec1.2}
---------------

The following hypotheses are presented in the paper.There exists significant difference in depression between men and women of older adults.There exists significant difference in depression between married and unmarried older adults.There exists significant difference in depression between older adults living in nuclear and extensive family system.There exists significant difference in depression between employed and unemployed older adults.

2. Research Methodology {#sec2}
=======================

Data were collected through convenient sampling technique from the twin cities of Pakistan that is, Rawalpindi and Islamabad. Design of the present study was descriptive and quantitative. For data collection face to face survey interview was conducted. 310 elderly were participated in the study by signing written inform consent by significant others on their behalves. Urdu translated 15-item Geriatric Depression Scale (GDS-SF) \[[@B8]\] and demographic profile were used to test hypotheses. 10 to 15 minutes were taken by each individual.

Data of the study was analyzed by using SPSS version 14.0. For elaboration of results tables were used for inclusive view of findings. *P* \< 0.05 level of significance was set for each observation. *t*-test was applied to determine the differences on depression. Where 0.76 cronbach\'s alpha reliability was recorded of the study.

3. Results {#sec3}
==========

3.1. Characteristics of the Participants {#sec3.1}
----------------------------------------

[Table 1](#tab1){ref-type="table"} of the study shows characteristics of elderly participants of twin cities of Pakistan. Category of unmarried elderly also includes 40 widows and 23 divorced. Likely the category of unemployed contains 42 retired older adults. Most of the geriatrics lie in the category of body complaints experienced muscular pains, digestive problems, and gastric issues.

[Figure 1](#fig1){ref-type="fig"} shows the age distribution of older adults participated in present study. 67.24 mean age is recorded of 310 elderly, where 189 were from Rawalpindi and 121 were from Islamabad.

3.2. Role of Sociocultural Factors in Depression among Elderly {#sec3.2}
--------------------------------------------------------------

[Table 2](#tab2){ref-type="table"} indicates the mean differences in various demographic variables among elderly on depression. Results indicate that there are significant mean differences (*P* \< 0.05) between men and women, married and unmarried, nuclear family and extensive family system, and employed and unemployed on depression.

4. Discussion {#sec4}
=============

Present survey was conducted to investigate about the role of sociocultural factors on depression among elderly of twin cities of Pakistan. Like previous literature, findings of the study revealed significant mean differences in gender, marital status, family system, and status of employment. So, all hypotheses of the study prove to be true (see [Table 2](#tab2){ref-type="table"}).

Asian women in later life were not able to cope up with daily life issues and house chore as she did before because of the old age factor. On the other way, unlike older women of western world, mostly Pakistani women are not working nor found of social gatherings so they more rapidly get isolated that in short time converted in to depression. It has been observed that elder women get depressed sooner as compared to men. Feeling of dejection and fear of death is very much prominent in older adult women as compare to men \[[@B16]\].

Marital conflicts are also very prominent in later life. Though, it is really hard for single (widow, unmarried, and divorced) women to survive solely in this world. Everyone needs somebody to share last stage of life. To discuss daily life issues to spend time with someone as a partner. It has been observed that married elderly spend healthy life as compared to unmarried. Absence of partner at the last stage of life pushed an individual in to depression. Single/unmarried older adults are more vulnerable to depression as compared to married older adults \[[@B17], [@B1]\].

Similar to rest of South Asian countries, extensive family system has been practiced in Pakistan by many families \[[@B8]\]. It is assumed that extensive family system is a healthy family system. Number of people was available in joint family system, to play care taker role for their older adults. Love and respect are the main source of happiness for elderly in joint family system. They had been surrounded by their second or third generation and elderly smoothly passed their last stage of life \[[@B22]\]. But in present period several families in Pakistan start adopting nuclear family system because of inflation and growing trend of modernization. They badly indulge in race of mechanical world and forget about the well-being of their assists in the shape of elders of the family. A study conducted Karachi by in Pakistani researchers elaborated that nuclear family system significantly strong predictor of depression for older adults \[[@B8], [@B9]\].

Findings of the present study and Systematic literature review demonstrated that geriatrics who are financial strong, have source of earning, living in their own house, have no tension of billing, feed by significant others and on pension are less susceptible to depression as compare to elders who are un employed, have no source of income and not supported by the family. Study documented that awfully Pakistan ranked on 9th position in the race of low income holder countries with increasing number of population \[[@B2], [@B20]\].

5. Conclusion and Recommendation {#sec5}
================================

It is concluded that elderly women undergo late life depression more than men. Widowhood, family conflicts, unsatisfactory family attitude, financial instability, communication gap, death of significant, unfulfilled early life desires, feeling of guilt, and later life general medical condition collectively act as strong predictorsof depression among older adults.

It is highly recommended to future researchers to design qualitative study along with quantitative study for in depth finds. Some questions of the interview would design open ended for comprehensive analysis.

In the beam of the findings of present study, it is immense need in Pakistan to design community support programs, welfare centers, policies for older adults\' rights, grants or pensions from government sectors, and medical expense arrangements for older adults.

First of all, the author would like to thank families of older adults for their cooperation and all elderly especially who gave themselves for her study. The author would like to thank her parents for their moral support and friends for helping her in data collection and data entry.

Conflict of Interests
=====================

The author declares that there is no conflict of interests regarding the publication of this paper.

![Age distribution of older adults who participated in the study.](CGGR2014-230737.001){#fig1}

###### 

Frequency of various demographic variables.

  Various demographic variables               *f*   \%
  ------------------------------------------- ----- -------
  Gender                                             
   Male                                       158   51
   Female                                     152   152
  Marital status                                     
   Married                                    201   65
   Unmarried                                  109   35.16
  Family system                                      
   Nuclear family                             190   61.2
   Extensive family                           120   38.71
  Status of employment                               
   Employed                                   125   40.32
   Unemployed                                 185   59.68
  Source of income                                   
   Self                                       123   40.32
   Siblings/family                            146   47.1
   Pension                                    39    12.6
  Living in own house?                               
   Yes                                        121   39
   No                                         180   58.1
  Having peer group                                  
   Yes                                        220   70.1
   No                                         90    20.03
  Any physical aliment?                              
   Hypertension                               52    16.77
   Diabetes                                   67    21.61
   Other body complaints                      156   50.32
   Not as such                                37    11.93
  Clinically diagnosed with mental ailment?          
   Yes                                        42    13.55
   No                                         268   86.45

###### 

Mean differences in various demographic variables among elderly (*N* = 310).

  Variables                       M       SD      *t*     *P*     95% CI   Cohen\'s *d*   
  ------------------------------- ------- ------- ------- ------- -------- -------------- -----
  Gender                                                                                   
   Male (*n* = 158)               9.21    2.5     −2.69   0.008   −1.57    −2.44          0.3
   Female (*n* = 152)             101.1   3.41                                            
  Marital status                                                                           
   Married (*n* = 201)            9.25    2.75    −3.24   0.001   −1.83    −0.45          0.4
   Unmarried (*n* = 109)          10.4    3.31                                            
  Family system                                                                            
   Nuclear family (*n* = 190)     10.7    2.3     6.3     0.001   1.14     2.17           0.8
   Extensive family (*n* = 120)   9.01    2.20p                                           
  Status of employment                                                                     
   Employed (*n* = 125)           8.6     1.8     −10.1   0.001   −2.90    −1.95          1.2
   Unemployed (*n* = 185)         11      2.3                                             

\**P* \< 0.05, df = 308.

[^1]: Academic Editor: Moisés Evandro Bauer